Most of us can’t afford to be late here, either.

Last week we tested to make sure that demand exists in the market. We know it’s there but something is sitting between the buyer and the purchase:

1. Belief blocker: buyers don’t fully understand or trust the category yet

2. Enablement blocker: something outside our control is in the way

While proof points like case studies and testimonials and references can break a belief blocker, data isn’t going to crack an enablement blocker.

This post is about surviving an enablement blocker, backed by an uncomfortable amount of first-hand experience.

1. Position for the future

You can see the wave forming but there’s still time before it breaks. While you wait, that time goes into authoring the category’s vocabulary and future standards. When buyers and practitioners finally show up, the terms they use to think about the problem are the ones you wrote.

dbt launched as data warehouses moved to the cloud. But a warehouse is just infrastructure and nobody had worked out the discipline to operate one at a high level. As a founder put it, the industry “treated data analysts as low-level, non-technical people.” That needed to change for dbt to be successful so the team spent the slow ramp championing an analytics engineer role and defining how the job should be done. As the cloud data stack went mainstream and every company suddenly needed that function, dbt was the pioneer behind the definition.

We had a similar scenario at Recurrent. The used EV market was too small in the US for most to care about but we could see a wave coming: years of new-EV sales meant a flood of vehicles on short leases that would be returned as used cars. We spent the gap codifying the language and success metrics that the industry would one day want to use. When buyers and sellers finally arrived, the playbooks they wanted were already written.

Test it: Write the sentence your buyer will use to describe this problem two years from now. Then work backwards to find the missing pieces: tech, titles, terms, etc. At the very least, you’ve just outlined your content calendar. The goal is hearing those terms repeated by prospects and competitors.

Lesson: A visible gap between today and demand on the horizon can give you just enough time to author the category’s language and success criteria. Whoever defines how buyers judge the category is the obvious default when the judging starts.

Common misstep: Don’t mistake your conviction for future demand. Name the external signal that demand is actually forming (lease-return volume, search queries, a regulation’s effective date) before you fund a year of positioning activities.

2. Relocate to the current opportunity

A chokepoint that blocks demand is only one point. Sometimes you need to go to where it doesn’t exist, even if that somewhere is not the ideal customer or region or deal size. Start there, get momentum, then use that to expand.

Ramp wanted to replace the goliaths of corporate spending with something better and more modern. Although a great idea, it required an even greater switching cost for their prospects.

For a large enterprise, that meant procurement cycles, migration downtime, uncomfortable risk. Switching costs were an incredible hurdle, but only for established companies. A startup in its infancy had nothing to change or break. Ramp shifted its focus down-market (to startups) and only moved upmarket once it had built the controls and integrations to lower enterprise switching costs.

Waymo ran the same logic on geography. It didn’t launch where revenue potential would have been the highest. It launched in suburban Phoenix where flat roads and blue skies and lax state regulations flattened likely blockers. It was years before it took on hilly, foggy, dense, regulated (and lucrative) places like San Francisco.

Test it: Instead of asking who your ideal customer is, ask who has nothing in the way: nothing to rip out, no one to convince, no missing piece they’re waiting on. That may not be the customer you set out to win, but that could be why the segment is still available while you wait on other blockers to clear.

Lesson: You don’t have to clear the blocker everywhere. You need the one place it doesn’t exist, then a route from there to the rest of the market.

Common misstep: Don’t lose sight of the desired destination. You’re relocating to fund survival but the risk is getting stuck there so go in with that in mind.

3. Build or partner to unlock demand

Some blockers can be built around, either independently or by partnering with someone who also benefits from removing that blocker.

Cursor is an AI coding editor that sits on top of incredibly expensive models. When its suppliers, OpenAI and Anthropic, launched their own coding tools, Cursor’s vendors became its competitors. It couldn’t out-spend them to build a rival model, so it announced an acquisition by SpaceX, which now (somehow) owns the Grok models. Cursor’s bridge got it across the blocker, but it wasn’t a moat.

Common misstep: Be careful not to rent a core piece of your product (or moat) from a company whose roadmap runs through you, too.

4. Create momentum with competitors

The Belief Blocker scenario from last week was about one buyer’s doubt, which you can often clear yourself with a pilot project or case study data.

Industry-wide doubt exists too, held by analysts, investors and incumbents. Sometimes the best solution is making the space so obviously real and investable that bigger players enter to help you establish the market. Big names attract analyst coverage, drive awareness with marketing budgets you could never match, and de-risk the decision for early adopters.

Harvey’s AI-native legal product is a helpful example. When the trusted legacy legal-tech brands (Thomson Reuters and LexisNexis) started shipping their own AI products, they helped to alleviate the natural concern of every firm’s managing partner: “Is AI actually safe to use on legal work?”

Incumbent marketing budgets and reputations cleared the industry-wide doubt that Harvey could not have done on its own, and suddenly every firm was looking for a legal AI tool. Harvey was positioned to win the ones who wanted the best product because the AI-native option had better UX and value to users. The incumbents brought the demand so Harvey could capture it.

(The thing I’m watching now is if Harvey can protect itself against the inevitable bundling from incumbents. Think: Slack vs Teams)

Test it: You often can’t control which incumbents show up. Before you make it attractive for them to enter your market, identify the advantage (moat) you’ll still have when they show up with a good-enough version and a bigger budget. That’s where your energy should be going while you wait.

Lesson: A slice of a big, validated market beats owning a sliver of a tiny, unproven one. Let incumbents build the market for you.

Common misstep: Be careful of welcoming giants before you’re defensible. Leadership roles are tough for pioneers to recover once they cede them.

A way across the demand gap

The four moves are more of a diagnosis than a menu.

• If the blocker will clear on its own with some time, position for it.

• If it’s already gone in some corner of the market, relocate there.

• If it won’t clear and you can afford the fix, build it.

• If it’s too big for any startup to move, enlist the giants who can.

Under all of them sits one constraint: stay cheap enough to still be standing when the wave arrives. It won’t matter how incredible the market demand has become if you can’t survive long enough to harvest it.

Arriving too early is simply a gap to cross. As that journalism professor reminded us, early was the only option for us. Make the most of it.

That’s the bad news.

The good news is that the other half didn’t fail. I find that 1993 study even more motivating today as AI shrinks the cost and timelines necessary to bring an idea to market.

The catch is timing. You can have the right idea and still be too early to make it. As a founder put it to me recently: “How do you tell the difference between being early and being wrong?”

In real time, it’s difficult. Early and Wrong give off the same signal: People say they like the concept then don’t follow through. (Keep in mind I’m living some of this right now in the EV sector.)

This post is the diagnosis of being early vs wrong. Next week is the prescription: How to cross the gap once you’ve determined that you’re not wrong.

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The Blocked Demand Test

Demand that hasn’t arrived is either blocked or absent.

• Blocked demand has something sitting between the buyer and the purchase.

• Absent demand isn’t there and may never be.

We’ll start by going through the two common types of blocked demand, followed by what absent demand looks like from a seat inside the company.

1. The Belief Blocker

In this scenario, the demand is real but buyers don’t fully understand or trust the category yet. That’s often the blessing and curse of being early.

Slack is an easy example. When it launched, no one thought of team chat as something worthy of a budget line item. Instead of convincing a CFO that it deserved budget, Slack got the people who’d actually use it hooked first, one department at a time. By the time the invoice reached finance, the belief was already undercut by hundreds of employees who loved the product. Slack’s CEO said the growth was “almost entirely on word of mouth.” Their belief blocker just needed exposure.

Harvey broke through the belief blocker with client logos. It courted the most prestigious firms first, betting that these clients would also be the most persuasive references. Harvey now counts the majority of the Am Law 100 as customers and reached $11B in valuation.

Test it: Review recent deals or customer surveys for recurring doubts, which is how a belief blocker presents itself in the buying process. What happened when you put proof in front of that doubt? (Client reference call, case study, pilot program, testimonials) Did the blockers give way? Belief blockers tend to budge with reassuring evidence, whereas other blockers do not.

Lesson: A belief blocker is something that education and proof can unblock. (We’ll go through how to package it in part 2 next week.)

Common misstep: Resist the urge to treat every objection as a belief problem.

2. The Enablement Blocker

Here the demand is real, and buyers get it, but something outside your control is in the way.

• A missing piece of infrastructure

• A partner who won’t play their part

• A behavior the rest of the chain hasn’t adopted yet

Grocery delivery is a good example. Webvan was the original Instacart. It raised nearly $1B to build its own warehouses and truck fleet, then caved under the costs. A decade later, after smartphones enabled gig driving, Instacart rebooted the idea and it worked. People wanted what Webvan originally offered but the infrastructure didn’t exist to support it in a cost effective way yet.

Michelin built run-flat tires that drivers wanted and carmakers backed, but the product stalled because service garages wouldn’t support it. The blocker was a critical ecosystem partner rather than a buyer issue.

Test it: Go back to those same sales notes to look for conditional language: “once we have,” “we can do X when Y is ready,” “we’re waiting on...” Enablement-blocked buyers are postponing vs rejecting.

Lesson: Every business depends on the health and collaboration of its ecosystem. If the blocker does not live with the product or buyer, other parties may be limiting the free flow of demand. (We’ll get into a whole targeted playbook for dislodging these in part 2.)

3. Absent Demand

If it’s not one of the other two blockers, that’s when I start to look for absent demand.

Quibi is the case study. They raised almost $2 billion, launched in April 2020, and threw in the towel by October. The founders blamed timing: “I attribute everything that has gone wrong to coronavirus. Everything.”

Except they weren’t just early and it wasn’t just COVID.

Short form video exploded on TikTok over that same period and streaming hit all-time highs as screens became our closest friends. People simply didn’t want Quibi’s version of it.

Amazon’s Fire Phone has similar lessons. The smartphone market was mature in 2014 — iPhone was already on #6 at that point? — and Amazon had the brand + distribution. But the market didn’t want it.

Test it: Take your most engaged prospect (the one closest to ‘yes’) and remove the blocker yourself: eat the cost, build the one-off integration, hand them the thing they said they’re waiting on. If they still don’t move, you may have found the reason.

Do the people who do buy keep coming back on their own or only when you nudge them? Read “What not having product-market fit feels like” by Melissa Kwan to double check your gut here.

Common misstep: Being “early” can be easier to stomach than “wrong” so be careful not to find a convenient false positive.

Unblocking the blockers

Each scenario leaves a different constraint on your pipeline.

1. Belief-blocked buyers are hesitating.

2. Enablement-blocked buyers are delaying.

3. Absent demand is curious but needs continuous prodding to maintain interest.

They can look similar at first glance: initial interest that won’t convert. The difference is how they respond when you intervene. Put targeted proof in front of a belief blocker and it moves. Whereas absent demand stays stuck even when you remove the blocker entirely.

I’ve experienced all of them and none are fun. Being early is actually the harder job because now you have to survive the gap while working to break through the blockers.

Next week is the prescription.

We’ll go through the four ways I’ve found to cross the gap when you’re early, including what to do when the blocker is yours to remove, and how to avoid handing the win to whoever shows up after you.

The waitlist did exactly what a waitlist does. It measured curiosity.

For Tesla, the refundable $100 deposit was only 0.1% of the price tag, which ended up nearly 2x over the original estimate. Tesla and auto analysts both confused that waitlist for demand.

But waitlists aren’t the problem.

We’ve used them at Recurrent to launch the company and accelerate cold starts for several new products, and I still recommend them to many of the startups I advise.

• Linear turned a 10,000-person waitlist into a filter.

• Robinhood turned one into a competition.

• Superhuman turned one into a badge of exclusivity.

Using one successfully comes down to what you make people do to get on it and what you do with them while they wait.

Since most teams do neither, here is a new way to think about it so you don’t make their mistakes.

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The Waitlist Matrix

A waitlist has two key variables:

1. What it costs someone to get on. All of them cost something: an email address, refundable deposit, intro call, referral.

2. What you do for people once they’re waiting. You can let them sit while you work or you can work the list while they sit.

Plot the two and you get four kinds of waitlists.

It’s rare that startup teams consider this before publishing their landing page. They end up chasing total signups and find the bottom left without intention. It’s optimized for size so it’s cheap to join and generally put on a shelf until launch.

That’s the Vanity Corner. It makes sense on paper because a big number is hard to argue with. “Hundreds of people want our product so it must be a great idea.”

Two moves help you avoid that misstep.

1. Move right so it costs something.

2. Move up to engage the audience while they wait.

You don’t need both to have a valuable waitlist. But I’d encourage you to pick one thoughtfully. Here’s how you can make that decision.

Move 1: Make the signal cost something

The signal you get is aligned with the cost you charge.

• Quick and free = curiosity but not intent

• Steep investment = intent but limited sample size

But keep in mind that the cost doesn’t have to be money. It can be effort, and sometimes that’s a better currency.

GitHub gated its Copilot preview to people already on a paid plan. The list would be shorter, but everyone on it had already had a credit card on file.

Superhuman charged in effort. Originally you had to book an onboarding call to even get an opportunity to get access. That sounds insane for a prosumer product. But it also got people to invest half an hour with the founders. We value what we work for.

Cognition’s waitlist was a form that asked what you’d want to build so the team could review before sending onboarding invites. The application was the filter, similar to what Linear did with its waitlist.

Waymo limited early access with a Trusted Tester program that included an NDA and request for detailed feedback. The cost of entry was a willingness to do research alongside them.

• “Join the waitlist.” ❌

• “Tell us what you’d use this for.” ✅

Test it: We should be deciding what we want from the waitlist before we build the form. Finish this sentence: “A signup tells me this person ______.” Pick what you actually need to learn and make joining cost that.

Lesson: Build the waitlist signup backward. Start from the signal you want, and the right cost becomes obvious.

Common misstep: Friction for its own sake isn’t a signal. The cost has to select for the customer you’re after rather than just having a hurdle to have one.

Move 2: Work the wait

Intent has a half-life. I can’t find the podcast to attribute it, but I heard Attio founder Nicolas Sharp say that the half life of a waitlist is much shorter than startups expect. He suggests that it is probably measured in days, even though people sit on the list for months.

We have two ways to counter that.

1. Shorten the wait

2. Keep them interested

The mechanics are well documented in academic studies.

1. People work harder the closer a reward feels so a waitlist that shows someone progressing is motivating.

2. Another study shows visible progress nearly doubled completion rate. In the trial, a loyalty card needing eight stamps from zero got redeemed 19% of the time, while a card needing ten stamps with two pre-filled delivered 34%.

That’s what fueled the Robinhood waitlist. You signed up, got your spot in line, and moved up by referring friends. A million people joined before launch. Even as regulatory approval delayed launch, the list stayed warm the whole way.

Folk CRM added a quick 10,000 signups but worked the waitlist by treating it as a conversation. The founders thanked them, asked what they expected the product to do, then granted access slowly. For them, a waitlist was user research that shaped what they built.

• “We’ll email you when we launch.” ❌

• “You’re #840. Here’s what we shipped this week for your use case.” ✅

Test it: Start by getting honest about how long the wait actually is because Attio guessed one year and it was three years. Then map the time between waitlist signup and launch as a journey. How much will they trust you in week #2, week #20 and the week before you launch? The goal is guiding them from a curious stranger to a ready buyer.

Lesson: The wait isn’t dead time. It’s a finite window where attention is high and expectations are low. It has a short half life.

Common misstep: Don’t waste people’s time with shallow updates on progress. A series of “We’re so close!” updates only trains people to ignore you.

Finding your spot on the waitlist matrix

The matrix has four corners so consider where you want to end up.

• Vanity Corner (e.g. Cybertruck) is where lots of startups land by accident.

• Warm Corner (e.g. Robinhood, Folk) keeps a low bar to entry but engineers the wait. It’s right when your bottleneck is awareness and the product explains itself.

• Qualified Corner (e.g. Superhuman, Attio) asks people to invest up-front then keeps them close until you can serve them. This is right when your bottleneck is comprehension or capacity. It trades scale for intent. Clay kept its waitlist until it had millions in ARR for this reason.

• Squandered Corner makes people earn their way in, then goes silent. But as a lot of hardware startups that picked this corner can tell you, a higher cost of entry only raises the price of getting it wrong.

“Grow the waitlist” sounds like a good use of energy but it isn’t a strategy. Choosing the Vanity Corner gives you a number that climbs while the signal underneath it gets weaker.

Before picking that path without intention, ask yourself what you really want from the waitlist.

Curiosity is cheap. It’s better to ask for something or earn the right to keep them. Ideally both. Do neither and you only get a nice number for a press release.

• Add an LLMs.txt file.

• Actually don’t bother because the platforms ignore it.

• Rewrite everything on your blog in Q&A format.

• But content on your site doesn’t matter so focus on Reddit.

I came up through SEO in the early 2010s so this is familiar. When the platform is a black box, the community gets one result from one test and extrapolates it into the must-do tactic of the year.

I watched that cycle repeat for a decade and the results got predictable. The brands that won were guided by a clear thesis, making small adjustments as the market evolved. The brands that lost ended up like ClickUp, chasing tactics like scaling its blog to 7,000+ programmatically generated posts then losing 98% of traffic a year later.

Today I’m sharing a general approach to the AI search era and, more importantly, a framework for adapting it to fit your business, using Gong and a few other successful brands as guideposts along the way. So let’s start with how I think about content.

Shaper vs Chaser Content

Somewhere along the way “content marketing” became synonymous with a blog. Write a post for your ICP, sprinkle some keywords for visibility, and post it on yourdomain.com/blog.

AI has killed that.

But content marketing has always been much bigger than that. Don’t forget that Red Bull dropped someone from space as part of a larger content marketing engine.

In the startup world, content marketing also helps us define our emerging categories. We name a problem people feel but haven’t defined, then hand them the vocabulary they’ll use to evaluate every solution (including ours).

AI isn’t changing that.

Think about the content you produce as two types:

1. Chaser content captures existing demand. It chases the topics and phrases people are already using (”best CRM for startups”) and competes to be the answer. This is what SEO optimized for and what AI now does better than any single source.

2. Shaper content creates the demand that chasers compete for. It shapes a problem your buyer feels and teaches prospects, search engines and LLMs the language they’ll use to evaluate solutions.

Note: Content does other jobs — converting, retaining, etc. — but we are focusing on content’s go-to-market role in this piece.

AI search doesn’t erode shaper content. It actually amplifies it. The models answering your buyer’s questions in 2028 will be trained on whatever language your category settles on between now and then.

That means the play is the same one it’s always been, with much higher stakes.

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The Shaper Content Playbook

1. Diagnose the Job

Do you own the language you’re using or are you renting it?

The answer probably depends on your category’s maturity. Most brands operate in Crowded Waters, where the language settled years ago. They have to compete for and pay to capture existing demand with words some other brand authored.

New categories carry the opposite burden and opportunity: you have to teach your audience the language first, but every term you seed becomes an unfair advantage later. When the category matures, you own the vocabulary and everyone else is bidding on it.

Gong got there after four years of a narrative war in Conversation Intelligence. So Gong ceded the category to its competitor and declared a new one: Revenue Intelligence, a term with zero search volume.

Then they put every ounce of content and budget into establishing it. (More on that later.)

Test it: Pull up your last ten content titles. For each, ask if a competitor could publish it verbatim with their logo on it? Every ‘yes’ is a piece competing for traffic that AI is quickly eroding. As the organic traffic shrinks, that’s traffic you’ll have to pay for in the future. And, arguably, if you have to pay for people to see your content, that’s not content marketing. It’s labor-intensive advertising.

Lesson: A category you don’t guide with language is one you’ll eventually have to pay to participate in. Unique perspectives differentiate, and language is where that starts.

Common misstep: SEO and AEO tools can only see questions that already exist so they will always steer you toward ‘renting’ vs owning the language.

2. Name the Question

The language you shape doesn’t have to be a category name. Moz shaped a metric, HubSpot shaped an “inbound” methodology, and Salesforce shaped an identity. Each of those, regardless of form, installs a question your buyer will be answering.

• A category = “Which of these do we need?”

• A metric = “What’s our number?”

• A methodology = “Are we doing this right?”

In every case, the author of the language is the default source of the answer.

This matters 10x in AI search. A word is something a model can swap for a synonym. A question is something a buyer asks their assistant. When you participate in creating the question, you’re writing the prompts your future buyers will use.

That’s in part why “revenue intelligence” was successful. As Gong exec Udi Ledergor has shared in podcast interviews, “conversation intelligence” was easy for a CRO to delegate, but revenue intelligence had their job title in it. The phrase aligned with a question sales leaders couldn’t ignore: “What’s actually happening in our revenue engine?”

Test it: Write down several questions you want your buyers asking in two years. Then answer each one honestly. If a competitor could give the same answer today, cross it out. Whatever survives is an example of your first shaper content.

Lesson: Identify the key (future) questions before you pick the words to answer them. Gong, Moz, and HubSpot each own different kinds of language, but all three own the question underneath it.

3. Amplify Until They Say It Back

New language becomes a category standard when people with no incentive to help you start repeating it. That usage is what influences the human buyer and the LLM model. Competitor pages, analyst reports, podcast transcripts, Reddit threads… that’s the material AI answers are built from, and you want them written in your language.

But that doesn’t mean “build it and they will come.”

Gong didn’t hit publish on its “revenue intelligence” press release and wait for the market to adopt it. They treated it like a product launch then kept pushing it.

HubSpot relied on similar repetition. “Inbound marketing” is a conference, a certification, an academy and a book, all amplifying the same two words until the market adopted it.

One mention is a data point. Hundreds of consistent mentions across channels and sources you’ve seeded is a definition that people and LLMs can’t ignore.

Test it: Ask a popular AI chatbot “what is [your category term]?” and look at whose framing comes back. If it answers in a competitor’s words, or generic ones, you can see one of the amplification gaps to fill.

Lesson: The SEO era measured traffic. The agentic era measures influence: how often the answer comes back in your words.

Common misstep: Don’t lock your language so tightly with trademarks and branding that nobody else can use it. The point is broad adoption, which means language bigger than you, your product and your company.

Which Half Are You Holding?

AI is eating a lot of what we used to view as content marketing. That’s the bad news.

But if you’re building in an emerging category, your opportunity is the half that AI can’t erode. In fact, you win when AI learns from it. That’s the good news.

AI can synthesize 20 answers to a known question. It can’t name a question nobody has asked.

Whether that question is a category name, a metric, or a method, the naming job can still be yours. Every piece of shaper content you publish and amplify becomes the material that others (humans + bots) use when the category matures.

• “How will AI cite our page?” ❌

• “How will AI say it back in our words?” ✅

The first is a chaser question, and the organic version of that is going away. The second is a shaper question, and in your category, right now, it is wide open.

Last week we looked at the case for staying in an established category. Greenhouse tried to create “recruiting optimization” then retreated back to ATS. Marketo retreated back to marketing automation. Domo retreated back to business intelligence.

But startups do break out and create categories that stick:

• Datadog unified IT monitoring into observability.

• Beyond Meat added plant-based meat to the meat aisle.

We have data on why these creators were successful. Elizabeth Pontikes at UC Davis analyzed 4,500+ software companies over 12 years.

She found that new categories are most likely to stick when the legacy category is constrained, meaning buyers can consistently describe it in a sentence. For example, in the late 1990s buyers could easily define “videoconferencing.” When document collaboration emerged, the contrast was simple to spot. “Collaboration software” had the freedom to create its own category (and charge more).

New categories don’t stick when the old one is lenient, meaning nobody can agree on what the label means. For example, partner relationship management (PRM) tried to break out of CRM. CRM was not defined enough in the late 90s so buyers couldn’t tell what CRM was or what it wasn’t. PRM had nothing to be the opposite of so it faded away.

Here’s a three-part diagnostic based on her research (and work by other academics) that you can use if you’re considering breaking out of an established category.

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1. Is the old category well-defined?

Buyers can describe a well-defined category in short, simple ways that mostly match what other buyers would say. That’s what gives a new category something to be the opposite of.

Datadog had both when it broke out of IT monitoring. Engineers tracked application performance, system logs, and infrastructure health in separate, well-defined tools. Datadog’s pitch was to unify all three under what would become known as “observability.” That pitch worked because each bucket already had clear boundaries to build on.

Beyond Meat had the same advantage in veggie burgers. Shoppers had the decades of experience with veggie burgers: frozen patties for vegetarians made from beans and grain. The consistency from incumbents like Boca and Gardenburger created space to be not-that.

Compare those to “AI assistants” in 2026. Siri, Glean, Gemini’s morning brief, Microsoft Copilot and hundreds of vertical tools all go to market as AI assistants. But ask 5 buyers what makes a product an AI assistant and you’ll get 5 answers. That lacks consistency so a brand trying to break away from AI assistants will struggle to differentiate.

Test it: Google a few variants of “what is [old category]?” to look for trends. Take note of how closely the top results agree on the definition. If they don’t seem to, it may not be well defined yet.

Lesson: The clearer the old category’s edges, the cleaner your break-out can be noticed by buyers.

Common misstep: Don’t confuse your own clarity for the buyer’s. You live in this space and they may only think about it once a year.

2. Can buyers tell you what it’s NOT?

A more reliable signal can actually be what buyers say the category isn’t.

When Beyond Meat launched, they designed it to be easy to see what it wasn’t: a frozen Gardenburger disk. They put it in the meat aisle, gave it beef-section pricing and packaged it to look nothing like a freezer-aisle veggie burger. Having a confident “not-that” helped plant-based meat land as a category.

Datadog could pass a similar test with its niche audience. By the late 2010s, engineers could tell you observability wasn’t just application performance or system logs or infrastructure health. Each piece had clear edges, which is what let observability sit between them.

Run the same test on AI assistants. Ask buyers what isn’t an AI assistant. Is a copilot one? Is an LLM chatbot one? Is a workflow tool one? The boundaries don’t exist to push against for most users.

Test it: Ask prospects what else they are considering. Their answer will tell you how well-defined the old category is.

Lesson: A new category lands when buyers can confidently tell you what it isn’t.

Common misstep: Don’t take “we don’t know what to compare you to” as a compliment. It can mean the old category is too blurry to anchor a new one.

3. Where will the money come from?

A new category doesn’t invent a budget from thin air. Successful creators identify a specific funded pool to siphon from, and position themselves so drawing from it feels obvious to the buyer.

In B2B, those pools are lines in the budget. In B2C, they’re stable household buckets and retailer shelf space. Fuzzy categories are the ones with no obvious place to point, which is why your new category can’t pull money from them.

Datadog’s pitch wasn’t “fund a new observability budget.” It was “consolidate 3 budgets you already have.” Datadog used the gap between those funded buckets to pull money from all of them. Today, “observability” is its own line item, but only because the older categories it absorbed were funded first.

For Beyond Meat, the veggie burger share-of-wallet was tiny when nested in the frozen food section. Especially compared to the amount that the average household spends on meat each visit. Beyond Meat’s pitch to grocery stores was about getting placement in the meat aisle, which meant accessing a much larger share of the grocery receipt. That shelf placement became the budget signal. Now other large players have launched their own plant-based meat lines to codify the placement and category.

AI startups are seeing this right now. Vendors are bidding on “AI assistant” keywords, but the ads are positioned different ways for different buyers. The category hasn’t settled.

Test it: Ask prospects what they are replacing with your product. Their answer will tell you if your siphoning hypothesis is resonating. If they can’t, your product cost may not find a budget to support it.

Lesson: New categories that stick pull money from well-defined categories that already had funding.

Variables You Can’t Control

Pontikes’ direct advice to founders: “No matter how new your technology is, if the categories around you aren’t well-defined, it’s going to be hard to position that product as something new. You’re probably better off saying that you’re exactly like what the other guys are doing.”

Most founders evaluate this decision by looking inward at their product, team or underlying tech. But it’s the shape of the old category (a variable you can’t control) that influences whether your new positioning lands.

Together with last week’s salvageable test, the two-part question is structural before it’s creative:

• “Should we try to create a new category?” ❌

• “Is the old category settled enough for a new label to make sense?” ✅

The good news is that fuzzy categories don’t stay fuzzy forever. They clarify as buyers form expectations and labels become consistent. Until then, patience and language discipline may be the best move.

For now simply figure out which side of that line you’re on.

Greenhouse originally tried to build a new category called “recruiting optimization.” Former marketing VP Barbra Gago shared the story several years ago on Lenny’s Podcast:

• They tried it.

• It didn’t stick.

• They quickly retreated to an established applicant tracking software (ATS) category and became a leader.

Greenhouse isn’t unique. Marketo tried to make “revenue performance management” a category until going back to marketing automation. Amplitude pushed “digital optimization system” then quietly went back to being an analytics platform. Domo pitched itself as a “business cloud,” but never made it out of the business-intelligence umbrella.

For B2B products in particular, it’s a structural problem: it’s easier to tap into an existing budget line item than ask customers to add a new one. Plus, when you abandon a category to invent one, the competitor who stays often absorbs the budget that you left behind.

The penalty for not fitting into a category is well documented by economic sociologists. Markets discount companies that don’t cleanly classify, and buyers devalue products that straddle two categories instead of picking a lane. More on that later.

This is a two-part series on the decision to revive or abandon an existing category. In this first part, we’ll use Greenhouse (and a few others) as examples for grading the potential of an existing category. Next week, we’ll flip it: the startups that ran the same test, got to “no,” and built a new category instead. Both parts share practical lessons from brands you know and what you can borrow.

The Salvageable Category

Under-served categories tend to reward modernizers: a startup that adopts the existing language then sets a new bar for customer expectations. Here are three ways to test if your category is salvageable with questions on whether its buyers can recognize it, fund it and find it.

1. Do buyers describe their problem in the category’s words?

You already know this from your last five sales calls. Hearing prospects say “we need a better ATS” or “our CRM should be smarter” demonstrates that the category’s language is functioning and helping buyers align solutions to their problems.

Greenhouse heard recruiters say they needed a better ATS and could not get them to disassociate that need with the established category.

HubSpot heard the opposite. Marketers told them that outbound was broken and lead generation didn’t work. Hubspot’s approach of using content + SEO to drive demand didn’t have a clean name, and the category label actively misled prospects. That mismatch made their inbound marketing label defensible.

The lesson: It’s difficult to replace the language that your buyers actively use.

The misstep: It’s possible to confuse ‘tired’ category language for misleading language. One is a copy problem and the other is a category problem.

2. Where does the money come from?

The money for products and services has to come from somewhere. For a company buyer, that’s a line in a budget, or even a specific RFP template or procurement code. For an individual buyer, it’s a mental bucket for “groceries” or “vacations” or whatever.

Those budgets are organized by category so a new category asks the buyer to remodel their budget. That’s a big ask:

1. Understand the value of this new product.

2. Assess my current budget.

3. Create a new line item.

4. Move money from something else to fund it.

While that exercise may take a split second for a high-income family in the checkout line, it could take years for a large organization.

Greenhouse found that customers and prospects had an ATS budget and it was growing over time. Decision makers and procurement teams could write the check from it without going to finance. That was the single strongest signal to stay.

Test it: Ask prospects how they are funding the purchase. You’re listening for whether you are slotting into a line item they already have or they’ll have to create one.

The lesson: If your product can fall into a budget line that already exists, the category is doing the funding work for you. If it doesn’t, you’ll need to sell both your product and their budget reorganization.

The misstep: Don’t get a positive response to the vocabulary you test in the previous step then automatically expect the budget to follow. Money moves slower than words.

3. Can buyers find you?

Our product research and purchase decisions are shaped by existing categories more than most people realize.

• Google serves us Wirecutter listicles on product categories.

• ChatGPT builds its answers from analyst reports and category Magic Quadrants.

• Amazon’s menu is organized by categories.

• The App Store sorts by categories.

The systems that we trust to help us shop are organized into categories that already exist. If you don’t fit into one, you’re invisible to prospective buyers and have to generate each ounce of awareness by yourself.

Economic sociologists even have names for it. Ezra Zuckerman calls it the categorical imperative: firms that don’t fit a recognized category trade at a discount because confusion about what they offer depresses demand.

Greenhouse found that the infrastructure for discovery in ATS was too valuable to ignore. There was a Gartner quadrant, a G2 grid, listicles, reviews, subreddits. Building their brand in ATS would not be easy, but it concentrated all of their marketing efforts in familiar places.

It’s more complicated when I talk to AI startups that don’t cleanly align to an existing category. That tempts founding teams toward “we have to create the category.” By the end of our discussions, we often align on a playbook that is more similar to Greenhouse: Picking an established category to modernize as an awareness and distribution shortcut.

The lesson: Existing category maps aren’t the only way buyers find products, but they are the easiest. Slot into one and the category does the discovery work for you. Skip it and we’ll be doing that work ourselves.

The misstep: Don’t grade findability from a biased sample of customers that already know you. We want to know how new customers will discover our solution to their problem… at scale.

One Thing This Doesn’t Measure

This test doesn’t measure whether you can win. You could breeze through all three questions and still abandon the category because an entrenched incumbent already owns the modernized version.

Salvageable is not the same as winnable.

Winnable is a separate question with its own signals (e.g. defensibility, distribution, switching costs) and it’s big enough that I’ve earmarked several posts for it later this year. For now, this salvageable test answers the prerequisite: Is the category even a viable home for what I’m offering the market?

It’s Only the Beginning

A lot of category creation advice treats the decision as largely creative: the right name, the right positioning, the right story. From my experience, it is more of a structural decision: existing language, budget, discoverability.

• “Should we try to create a new category?” ❌

• “Is an existing category serviceable?” ✅

Everybody knows the big winners like Salesforce and Snowflake so we need to be careful making decisions based on survivorship bias. Most of the startups that tried to mint a category got buried and lost to time.

Hubspot left and Greenhouse stayed. Both made the right decision.

I also ended that post with a promise to let people smarter than me on personal branding guide you on packaging and distribution.

This is me delivering on that promise.

I asked three experts on founder brands the same set of questions, then used their answers to triangulate the best takeaways.

• Dianne Wilson writes The Boundless Brand Club and turns founder ambiguity into positioning clarity.

• Alicia Teltz writes The Hype Department and spent years inside LinkedIn before becoming one of its distinct voices.

• Shreya Vaidya writes Grow-th and is a LinkedIn Content Strategist who is also building a community for AI-forward legal professionals at Spryngbase.

Three different vantage points with a mostly unanimous answer: a founder brand isn’t built by simply being louder. It’s built by distilling your unique view of the world into simple, portable ideas.

I’ve witnessed this at Recurrent. It wasn’t the concepts that we pushed the hardest that the industry adopted. It was the ones that distilled complex topics or emotions into things that could be delivered through the CEO that stuck around and put our team on people’s radars.

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Putting Your Ideas to the Test

In last week’s post, we worked on discovering and framing our unique point of view as a leader in a new category.

1. Find the unnamed language that’s already trying to exist.

2. Name what they’re feeling by articulating the problem so clearly that the audience recognizes itself in it.

But a brilliant point of view in your head isn’t a brand. It becomes one when it survives contact with the market and lodges itself into people’s memories. Use these six criteria from our guest experts to pressure-test those ideas.

1. It’s unique.

A point of view everyone agrees with is one nobody remembers.

“Good branding repels as much as it attracts,” says Dianne. It’s more important that “your identity is clear enough that the right people recognize themselves in it and the wrong ones opt out early.”

That doesn’t mean you need to be an agitator, simply to agitate. It’s more that neutrality isn’t memorable. “The market does not remember generality; it remembers distinct interpretations,” Dianne says.

Shreya names why leaders settle for forgettable: They are “so scared of being viewed as ‘unprofessional’ that they veer towards being ultra-safe (read: boring).” Her fix is to gravitate toward the edges on purpose: “What makes them interesting, unique and even (slightly) odd? This is the part that nobody else can imitate.“

That uncopyable part is the personal-brand version of the Belief Moat: the worldview competitors can’t copy without recognizing you.

Test it: Read your last 10 posts on the channel you’re most active on. If no one could disagree with any of them, there’s a chance the view you’re sharing isn’t uniquely brandable.

2. It’s borrowable.

Think back to a meeting where someone told you something that you originally told them. Regardless of whether it was your original thought, it’s an example of a phrase or concept that could be borrowed and used by a different owner.

In other words, it wasn’t limited to you.

Dianne reminds that raw thinking only compounds “once it becomes transferable.” A founder “stops being merely interesting and starts becoming influential when people begin borrowing their language to explain their own experiences.“

The goal here is to compress a complex belief into a reusable mental model that’s light enough for someone else to carry.

She’s specific about what makes language portable: “Compression, specificity, asymmetry, and uncompromising clarity.” A sharp, specific idea is one that can be borrowed and travel without you.

Test it: Take one of your core ideas and shrink it to one sentence or phrase to use in meetings this week. People’s initial reactions will tell you a lot. Maybe you’ll even have someone say it back to you.

3. It’s repeatable.

‘Consistency’ is a common suggestion for branding and social media. Alicia thinks that’s the wrong target.

“Consistency alone does not create compounding. Otherwise every founder posting 5 lessons from building a startup three times a week would be internet famous by now.”

What compounds is recognizable thinking: Returning to the same handful of ideas, questions, and frustrations — “packaged in different ways over time” — until your audience starts associating them with you.

Shreya is specific: “Begin with a rough idea of your signature style and positioning, and once you learn from experimentation… begin applying your learnings to recurring formats.” It’s how you find the few formats worth repeating.

A better way to think of consistency is stamina. The thing that quietly kills compounding, Alicia says, is “building a content system that makes you miserable.” You’re not going to succeed by suffering your way through years of low feedback in a format or position that you quietly hate.

Test it: Take one of your core ideas and see how many distinct angles you can pull from it: a contrarian take, a prediction, a customer story, a hard-won frustration. Finding 10 is a theme that is repeatable.

4. It’s matched to the messenger.

The right format is the one that best complements you as a messenger

Alicia again: “Some founders are incredible writers. Some are awful writers but brilliant speakers. Some need conversation to unlock their best ideas.”

It’s easier than it used to be because the platforms have all converged. LinkedIn, Twitter, Instagram all offer the same menu of short posts, long-form, comments, vertical and horizontal video. The format isn’t trapped on one platform anymore.

Set yourself up for success by choosing a format you’re comfortable in, especially if publishing isn’t a natural part of your personality.

Test it: Name the format where your best ideas actually come out (writing, scripted, live conversation, etc.) and you feel like you have a comparable advantage.

5. It’s findable.

The right channel is wherever the specific people who need your idea already pay attention. If that sounds overly simple, it is.

Dianne’s caution: “Founders often over-index on platform selection before they have developed message–audience fit. But a platform cannot compensate for unclear positioning.” Avoid that misstep by starting with who needs your perspective and where they already gather, then aim narrow for “resonance with the specific person who most needs the message.”

Then commit. Alicia’s rule is to “go all in on one first” and expand to other channels later, once you have a team and content worth recycling. Spreading across five channels on day one is how you stay invisible on all of them.

Shreya’s approach is “adding your ideal customer to your network” one person at a time, with your point of view in every post, so the clear idea is what does the pulling.

That’s the thing all three keep returning to: clarity before channel. “Clear thinking and a strong point of view create pull long before scale does,” as Dianne puts it.

Test it: Name the one person, role or persona who most needs your idea and the single channel where they already spend time.

6. It’s a story.

Stories travel better than facts. When a category has no shared language yet, it’s your stories that carry the idea.

Alicia reminds that stories don’t sound like a tidy case study. It’s more like you’re noticing something out loud, in real time. “The founders who build momentum early are usually the ones publicly noticing tensions before everyone else has words for them.” She’ll open a post with “Something weird is happening here,” or “Everyone thinks AI will replace X, but we’re actually seeing Y.” As she puts it, “nobody has ever remembered a human being for saying ‘unlocking efficiency.’“

Dianne adds the strongest stories often aren’t about you at all. It’s stronger when “the right people recognize themselves in it.” It’s working when people apply your idea to their own situation or problem.

Test it: Try exercising this muscle by writing your next post as a real-time observation rather than a conclusion: “Here’s something I keep seeing…” Then hold it to Dianne’s bar: Does it give the reader language for their own situation?

Common Missteps

Across all three conversations, the same three missteps kept surfacing:

• Don’t reshape your worldview to fit the audience until there’s nothing unique. As Dianne puts it, trying to be likeable is what makes you blend in.

• Don’t hide behind the company brand. People attach to a person with a point of view so put yourself forward, knowing it’s best for the company, too.

• Don’t outsource your thinking to AI. Once you’ve defined your perspective and tone, you can use AI tools to brainstorm new angles or adapt your copy for different mediums. But that’s much later.

Be the Spring

Last week I called your personal brand the spring that one day fills your company’s moat. Authoring the point of view is the spring. These six tests are how the water actually reaches the moat.

A massive thanks to Dianne Wilson (The Boundless Brand Club), Alicia Teltz (The Hype Department) and Shreya Vaidya (Grow-th). Subscribe to their newsletters for more brilliant perspectives from them.

The modern founder media strategy is engineered for noise. Build a personal brand, maximize reach, chase virality on the channel that owns your audience.

• Adam Robinson posts a cease-and-desist letter on LinkedIn to rack up 1,600 likes.

• Andreessen Horowitz (a16z) uses an in-house media team to turn portfolio company founders into celebrities.

Isaac Peiris did a deep dive on the Andreessen Horowitz playbook and his takeaways were solid.

• Owned distribution matters.

• Founders need to be visible.

• Don’t depend on traditional media.

But these examples aren’t drag-and-drop. Startups in emerging categories don’t have that foundation yet. They have scattered people who feel a problem nobody has named for them. Building an amplification machine on top of that just broadcasts confusion to a wider audience.

Here’s a playbook for owned distribution when your category isn’t codified, drawn from how Clay authored a $3.1B category one word at a time.

Authoring Your Audience into Existence

The first step is organizing a scattered group into an audience that recognizes itself and how you support it.

1. Find the unnamed

Before Clay coined “GTM Engineer,” the people who would later wear that title were already there. They were SDRs learning Python and marketers stringing together data enrichment tools. These people were already doing the job.

Clay’s co-founder Varun Anand found them by going where they already gathered. He joined GTM groups and online communities to listen to their challenges and frustrations.

As the Four Waters Framework illustrates, Uncharted Waters is the stage where the category isn’t a category yet and the audience doesn’t identify itself. It’s also when the vocabulary and the way that people form mental models about the solution is most up for grabs.

Test it: Spend 30 minutes a day for 2 weeks in the places where your ideal audience already gathers. Slack groups, subreddits, LinkedIn comment threads. Document the consistent phrases, especially the ones that don’t quite fit what they’re trying to describe.

Lesson: The job isn’t inventing language for a category you imagine. It’s surfacing the language that’s already trying to exist.

Common misstep: Let’s avoid the urge to conflate our products with the category. The category needs language bigger than your SKU so someone would use it even if they bought from your competitors.

2. Name what they’re feeling

Listening in Step 1 surfaces a scattered set of signals: words, workarounds and perspectives of the same underlying problem. Step 2 takes what we hear and articulates the problem the audience feels but hasn’t been named for them.

• Clay’s Kareem Amin and Varun Anand helped technical marketers and SDRs form a united identity as high-value “GTM Engineers.”

• ProfitWell’s Patrick Campbell turned scattered SaaS health metrics into a shared vocabulary that organized SaaS operators.

• RB2B’s Adam Robinson named “person-level website visitor ID” to articulate the gap that incumbents had been ignoring.

These founders didn’t invent the problem. They named the problem so clearly that the audience recognized it as theirs.

Test it: Repeat the synthesized phrases you heard in Step 1 back to the people you heard them from. We are looking for positive signals that we’ve named what they were feeling.

Lesson: Inventing a name is easy. The difficult part is articulating the problem so clearly that the audience recognizes itself in the articulation.

Common misstep: Don’t outsource this step. You need to hear it from the audience directly so you 100% stand behind it.

3. Distribute for recognition

A Belief Moat is a worldview that protects a company as its category matures. It’s something competitors can’t credibly copy.

You don’t have one yet and I don’t think you need one yet, either. Your job in Step 3 is to be the visible spring that will one day fill your company moat.

Each founder from above did this.

• Kareem (Clay) claimed “GTM Engineer” in his own name on LinkedIn.

• Patrick (ProfitWell) published pricing research under his own byline for years before the vocabulary attached to the company.

• Adam (RB2B) does every ounce of marketing from his personal accounts.

Using a personal brand creates a traceability that the company can eventually compound into a moat: a worldview that competitors can’t claim without acknowledging it came from you first.

You are putting the words into the world from your seat, in your name, repeatedly, wherever your audience already gathers. While the form will adapt for different platforms, the messenger will not.

Test it: Drop this prompt into Claude (or your AI chat of choice). It will ask you context questions covering what you’re hearing in Step 1, what you’re naming in Step 2, and how you’re surfacing it in Step 3. Then it runs research behind the scenes to test your logic on 3 dimensions: viability now, resiliency against competitors and whether your work is contributing to a future company moat.

Steal this prompt: audience authoring with AI

You are a strategic PR and brand advisor with deep experience
helping founders in emerging categories author vocabulary that
organizes scattered audiences. You've watched companies become
category leaders by getting this right, watched others lose
their words to competitors within 18 months, and watched
startups disappear because they never authored anything
specific enough to stick.

Be a sharp thought partner, not a cheerleader. Push back on
vague answers, strategic-sounding language, and pitch-deck
phrases. Ask for concrete examples, real community names,
actual quotes from problem-feelers. Don't move forward until
you have material you can actually pressure-test.

The conversation runs in four phases.

PHASE 1 — CONTEXT

Batch context questions into no more than three turns. Cover:

1. Who I am, my role, the company name and domain (if any).

2. STEP 1 work — Where I'm listening for problem-feelers.
   Which specific communities, Slack groups, forums? What
   scattered words, hedges, or workarounds have I noticed?
   The smallest, most acute group who feels this problem.

3. STEP 2 work — The word or phrase I've synthesized. Why
   this word and not the alternatives I considered. Who I'm
   explicitly NOT for. What vocabulary incumbents already
   occupy.

4. STEP 3 work — How I'm currently surfacing this as the
   visible author: which platforms, what cadence, founder
   name attached, whether company brand or founder brand is
   the front door.

If any answer is thin or generic, push back before moving on.
I should feel slightly uncomfortable with how specific you're
asking me to be.

PHASE 2 — RESEARCH

Once you have concrete answers, run the following:

- Web search for the exact vocabulary I'm trying to author.
  Who else uses it? In what context? How recently?

- Search for how problem-feelers in my space talk about this
  pain when they're NOT using my words. What workarounds and
  alternative framings exist?

- Search for analogous moments — where else has a founder
  named a problem that organized a scattered audience? What
  worked and what didn't?

- Identify alternative vocabulary I haven't considered that
  might be more precise than what I've proposed.

- Look for early signals my vocabulary is being used back to
  me, or evidence it isn't.

Share a brief summary of findings before advising. Ask me to
react to anything that contradicts my assumptions.

PHASE 3 — PRESSURE-TEST

Deliver a pressure-test on three dimensions, using evidence
from your research and from what I shared.

VIABILITY. Does the vocabulary actually organize a scattered
audience around a defined problem, or is it a marketing slogan
in disguise? What's the strongest counterargument to my
current word?

RESILIENCY. Can a competitor absorb this vocabulary in 18
months without acknowledging it came from me first? What
about my authorship is traceable, and what isn't?

FUTURE MOAT. What worldview is this vocabulary scaffolding?
What does the eventual Belief Moat look like — the worldview
competitors can't easily copy — and is my current authorship
work pointing toward it or away from it?

After the pressure-test, ask me how I'd like to refine. Is
there a sharper word? A narrower audience? A clearer
worldview to point at? Iterate with me until the positioning
is the strongest version of itself, not the easiest.

PHASE 4 — POSITIONING DELIVERABLE

When the positioning is locked, ask how I'd like the final
statement delivered. Offer these formats:

- A one-line vocabulary claim for a LinkedIn headline or
  about-page tagline.

- A paragraph-length positioning statement for use across
  founder content.

- A longer brief covering the vocabulary, the audience, the
  worldview, the path to defensibility, and the surfaces
  where it should be authored.

- A glossary of related terms I should use consistently
  across founder surfaces.

Once I pick a format, deliver the final positioning based on
everything we've worked through together.

Be the Spring

I’ll let people much smarter than me convince you that personal brands aren’t optional for modern startups. But, for anyone building in an emerging category, I can credibly tell you that your company’s future moat can be reinforced by your personal brand.

While some like a16z may be able to get there by amplifying, we need to get there by authoring the audience into existence.

I spent the last 2 weeks studying AI wedges from CRM startups. At almost every turn were billboards.

Startups buying expensive San Francisco billboards is nothing new but it tends to happen much later in the growth journey.

• HubSpot: 5 years after IPO

• Monday.com: 2 years after IPO

• Notion: 9 years and 20M users after founding

• Slack: $5B valuation

This year half the billboards in SF promote AI startups at early (Series A/B) funding stages. Lightfield has fewer than 30 employees.

What’s going on here?

There are way more efficient ways to target tech executives and I don’t think it’s general brand advertising. What they are buying is actually far more interesting:

They're not selling to buyers. They're staking a claim as category leaders that's visible to every stakeholder: investors, customers, recruits, media and competitors.

Every emerging category has a 1- to 5-year window when the “leader” designation is up for grabs. “Which of these companies is going to be the company?”

The billboards that Attio, Lightfield and Clay are buying aren’t selling to buyers. They are attempting to plant their flags halfway through a 2-year AI challenger window that is quickly closing.

Here are five lessons every startup in an emerging category can take from this moment, whether you’re AI-native or not.

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Lessons from the AI Land Grab

1. The land grab decides who makes the consolidation cut.

Four Waters Framework ends in Crowded Waters when the category eventually consolidates. The market doesn’t give oxygen to dozens of credible players forever. It promotes 1–2 incumbents (who acquired or shipped their way into a slot) and 1–2 challengers (who claimed a spot during the wave).

The land-grab moments determine who makes the cut.

The CRM category is reorienting around AI startups (Lightfield, Attio, Reevo) and incumbents with strong AI additions (Salesforce, HubSpot). In the next 12-18 months, the consideration set will settle on 3-4 finalists to recognize as leaders. The rest won’t disappear, but they won’t have a wind assist from the category, either. (Example: There’s OpenAI, Anthropic and everyone else.)

Many other SaaS categories are in a similar spot as challengers compete for those Leader slots.

Lesson: Categories consolidate. The land-grab window decides which challengers make the final cut.

Common misstep: Don’t default to looking at the competition as “startup vs incumbent” or “startup vs startup.” The finalists will likely include both.

2. The window is shorter than you think but varies by industry.

Different categories consolidate on different timelines. AI-native categories are uniquely compressed because the underlying tech is evolving rapidly and competitors can respond with new features in weeks.

I think the window for AI-native challengers claiming leadership spots in established categories is roughly 18–24 months from the wave’s start. Many challengers are already halfway through it.

Other industries take longer.

Recurrent provides EV battery analytics for the used car market. After we established our leadership claim, the auto industry took another 2 years to mature to the point where it wanted to recognize a leader. The full window was closer to 4 years.

Lesson: Each window is temporary, varies by industry and is generally shorter than you’d expect.

Common misstep: These leadership windows are not tied to you, your product or your funding stage. The category and market decide the timeline and set the consolidation clock.

3. Leader claims should look disproportionate to your stage.

Making a leadership claim may feel premature when you’re building with small teams and small revenues.

That shouldn’t stop you.

A claim that’s perfectly proportional to your stage is just a description. Planting your flag as a leader is a claim that will outpace the metrics. You’ll need to deliver on it later.

Lesson: A leadership claim may feel premature. The signal that you’re claiming is territory that nobody has fully earned… yet.

Common misstep: Don’t wait patiently to earn the recognition before making the claim. Your bold stance is what triggers the substance to catch up.

4. The judges who crown leaders vary by industry.

A leadership claim is only durable if (1) the judges see it then (2) begin to recognize it. But the field of judges varies by industry.

• Enterprise SaaS: Placement on a Magic Quadrant matters more than any customer logo.

• AI-native B2B: The stakeholder wall of customer logos and investors illustrates your momentum.

• Automotive (from Recurrent): Traditional media and trade publications play an outsized role.

If you’re spending on signals visible to the wrong judges, you’re paying for impressions that don’t reinforce your claim.

Lesson: The right judges in your industry are a small set. Find them first then determine how to get in front of them.

Common misstep: Don’t default to whatever signals are loudest in other categories. What works in B2B SaaS is likely irrelevant in healthcare.

5. Claims need time to compound.

The substance of your claim takes time to compound until the industry is ready to award (or cede) the designation. That gap can be months or years.

But billboards alone don’t make a leader. There are startups with expensive signs along the 101 right now that won’t make the cut.

Progress comes from a stack of small signals: trade press mentions, new customer logos, conference panel slots, podcast appearances, original research, founder thought leadership. Individually, each is small. Together, they accumulate into a body of evidence for judges.

The job during this gap is remaining committed. Again. And again. And again.

Lesson: Patience is part of it. Compounding signals come from persistence + time.

Common misstep: Don’t mistake silence for failure. Keep beating the drum until the industry can hear it.

Planting the Flag Before Someone Else Does

People will tell you to let the product speak for itself. But this year thousands of amazing AI products will be passed then lapped by the leaders of their respective categories.

Attio, Lightfield and others are demonstrating how to invest now to make sure you’re one of the leaders at the front of the race.

Recently we covered growth loops to avoid ads. Land-grab signals aren’t ads. They’re claims to a status that determines whether your company makes the consolidation cut.

• “How should we build brand awareness?” ❌

• “What leadership claim made today then reinforced for the next 24 months keeps us in the consideration set?” ✅

These billboard ad buys aren’t reckless spending. They’re part of a race to claim a leadership spot before the window closes.

Find the signals and claim them so you’re ready for your category’s land-grab moment.

What are your challenges right now?

Hit reply to share the things you’re wrestling with in growth and marketing. If you’re stuck on something, someone else in this community probably just got unstuck from it.

The one thing I’d ask:

If the growth lesson today resonated with you, send it to one person or team that it could help. That’s who built this community, and that’s who belongs in it!

It’s tough to break into mature categories because incumbents have years or decades of compounded advantages.

Salesforce makes $40 billion a year and counts 90% of the Fortune 500 as customers. Their annual conference draws 45,000 people, many with “Salesforce” in their job title. That’s called defensibility.

Except AI shattered Salesforce’s architectural advantages and birthed dozens of ankle-biter startups. The CRM category has been cracked open, and the company with “CRM” as its stock ticker is on its heels.

But incumbents aren’t all teetering.

The well-prepared ones are striking back by shipping AI products backed by their data advantages, refactoring pricing models and self-disrupting before challengers can get a toehold.

Almost every software category is experiencing some version of this.

On the one end is legal tech. Startup darling Harvey.ai is doing $200M ARR in its first 4 years with +60% of the top US law firms already paying. Incumbents Westlaw and LexisNexis are blocked by their own architecture and pricing.

On the other end is customer support. Incumbent leader Intercom shipped Fin within weeks of ChatGPT’s launch and rebuilt pricing around AI-assisted outcomes before challengers could find traction.

Somewhere in the middle is CRM. Salesforce acquired and launched its own AI bolt-ons. Attio reoriented around AI. Day.ai, Lightfield.ai, Clarify.ai, and Reevo.ai have each raised $20M+ to chase CRM wedges.

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The AI Wedge Framework

The most successful AI startups are breaking into mature categories by attacking the constraints that no longer apply. When incumbents can’t defend without breaking their own business model, the startups have found a durable wedge that:

• Exploits an ex-constraint. These are deeply embedded product, pricing or org structures that used to be economically or technologically necessary and are no longer essential with AI-native products.

• Requires the incumbent to cannibalize. Reorienting a business model is both painful and distracting: fragmented customer base, dual product lines, margin compression.

This framework helps you find a wedge that meets both characteristics of a durable AI wedge.

1. Map the Category

We need to understand how the incumbents in your category make money. For each major incumbent:

• What’s the primary revenue model? Example: Salesforce subscriptions are tied to “Seats” across core products.

• What constraints does that model depend on? Example: Salesforce’s seat-based pricing worked because humans had to operate the CRM.

• Which of those constraints can AI eliminate? Example: AI can populate the CRM without a human in the seat.

• How are incumbents responding to challenger attacks? Example: Salesforce is responding with M&A and its Agentforce product.

We’re trying to uncover where the category is primed for a wedge and whether incumbents have structural defenses.

Test it: Pick your category’s largest incumbent. Respond to each of the four questions as specifically as possible.

Lesson: A wedge starts with understanding the incumbent’s economics. Most AI startups skip this step and end up with interesting products that don’t threaten anybody.

2. Find the Ex-Constraint

A constraint is a structural condition that shapes the incumbent’s product, pricing or organizational design, and is (presumably) no longer necessary with AI.

• For CRM, humans had to enter information and maintain the system. AI automates those steps and questions seat-based pricing.

• For legal tech, experts searched databases and interpreted results. AI cuts out everything between query and deliverable, while some incumbent platforms are still pricing by search volume.

• For customer support, people responded to tickets in a queue. AI can resolve many customer questions independently.

Each of these constraints were foundational and permanent. Now they aren’t.

Test it: Complete these sentences with specifics in every blank.

1. “[Incumbent] was built when [constraint] was unavoidable.”

2. “AI eliminated [constraint] by [specific mechanism].”

3. “Without [constraint], [incumbent’s pricing / architecture / org] no longer makes sense.”

Lesson: The wedge is an ex-constraint, but not every ex-constraint is a wedge.

Common misstep: Don’t mistake product disruption (cleaner UI, lower price, faster onboarding) for structural disruption.

3. Identify What Breaks

A good wedge forces the incumbent to choose between defending and protecting their business model.

Intercom broke their seat-based model with $0.99-per-resolution pricing with Fin. They are privately held and most public companies can’t afford to make that dramatic shift.

For bigger and less dynamic organizations, it’s more often a slow bleed:

• A fragmented customer base that juggles new and old pricing models

• Dual product lines that split attention

• Slowing overall growth as business shifts from one bucket to the other

That creates opportunities for startups. While incumbents navigate internal complexity, your challenger brand can ship features.

• Harvey uses per-lawyer pricing to make search-volume-based pricing look antiquated in legal tech. Westlaw can add tiers with AI features but it won’t fire its sales force and abandon 50 years of sales-led growth.

• Day AI uses per-assistant pricing to make seat-based economics look antiquated in CRM. Salesforce can’t disrupt its enterprise contracts to respond to that.

Test it: Complete this sentence with two deep business-model pains.

“When [your startup] wins, [incumbent] has to either ___ or ___.”

Lesson: The wedge isn’t a differentiated product. It’s a structural threat the incumbent can’t defend without leaving behind a trail of blood.

Common misstep: Don’t mistake a product feature for a wedge. A wedge should force the incumbent to dramatically reprice, rebuild or repair.

Cracking Open Your Category

The final “Crowded Waters” stage in the Four Waters Framework is not a finish line. AI reminds us that mature categories aren’t closed when the underlying technology is disrupted.

But the wedge isn’t AI itself.

Your wedge should be the specific ex-constraint AI eliminates and the specific cannibalization the incumbent has to overcome to defend.

The category label is sitting there (CRM, legal tech, customer support) and the former constraints have disappeared. Your job is finding the durable wedge that forces incumbents into defense mode so you can exploit it before they can stop you.

A new founder told me he isn’t worried about landing customers 1,000 through 10,000. It’s getting customers 0 to 100 that keep him up at night.

That’s a common confession in emerging categories.

The first paying customers are the most intimidating because there’s no playbook, no brand recognition, no demand.

Conventional wisdom suggests building a funnel:

• Ads for reach

• Content for consideration

• Drip campaigns for conversion

That approach assumes educated buyers who are already searching for what you sell. But our first 100 customers aren’t searching.

AI-native CRM, Lightfield, found itself in the same situation. I spoke with head of growth Matt Serna, after hearing CEO Keith Peiris on Mostly Growth, to understand how they thought about it.

From what I dissected, they found their first 100 customers in stages:

1. First ~10 from their network

2. Next ~40 from communities

3. Next ~50 from creative growth loops

That pattern isn’t unique to Lightfield. Stripe, Airbnb, Tinder, Product Hunt and dozens of other now-famous companies followed a similar progression.

Here’s the lesson for founding teams to steal.

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Laddering to Your First 100 Customers

Think of your first 100 customers as climbing rungs on a ladder. Each rung requires a different approach. While it is tempting to skip a rung, they aren’t optional because one (almost) always leads to the next.

Rung 1: Customers 0-10

Your first customers don’t buy your product. They buy you.

These are people in your existing network who trust you or your reputation enough to try something unproven. They aren’t evaluating features against competitors. They’re doing a favor for a person they know.

• Lightfield’s first 10 customers came from the founders’ personal networks.

• Stripe recruited their first customers from other Y-Combinator counterparts.

On Rung 1, you are the distribution channel. That’s not scalable and not PMF, but that’s okay. The goal is getting people using your product so you can learn what to fix before the next rung.

Test it: List 20 people in your extended network who (1) fit your ideal customer profile and (2) would take a call this week. If you can’t get to 20, lean on your closest relationships to borrow their credibility and expand the list.

Lesson: You’ll find your first 10 customers because they trust you. Keep that trust by listening to their suggestions and helping them feel invested in the company so they stay customers long enough to learn from them.

Common misstep: Don’t spend money to acquire your first 10 customers. If the people who already know you won’t use the product, strangers probably won’t either.

Rung 2: Customers 11-50

You still don’t have brand awareness, case studies or inbound demand at this point. You’ll likely need to borrow credibility from an institution, community or network that your prospects already belong to.

Lightfield’s next batch of customers came from 1:1 outreach to other YC companies. Stripe’s initial adoption followed the same path. When a fellow YC founder asks you to try something, there’s built-in pressure to say yes.

Product Hunt launched as a daily email. The founders spent the first hour each day contacting the product owners who appeared in it, recruiting them into discussions about their own products. Those product owners shared the discussions with their audiences, which brought new people and products to the site.

Clay’s cofounder joined GTM groups. When people said something intelligent on a related topic, he would start a conversation with them. Whenever anyone mentioned challenges in Clay’s sweet spot, he’d give thoughtful and complete answers to their question. This also created an opportunity to learn how prospects talked about the problem, which shaped how Clay positioned itself.

Existing communities were our primary growth driver in the early days at Recurrent. Passionate EV owners don’t announce themselves, but they congregate in specific and predictable places. Being part of their groups gave us the temporary credibility we needed for them to try us.

The specific community varies. Startup groups, industry Slack channels, conference circuits. Find where your ideal customers already trust each other and show up there.

Test it: Name 5 communities where your ideal customers already congregate. Join the top 2 where people are actively asking questions about problems you can solve. Spend 30 minutes a day for two weeks answering those questions without pitching.

Lesson: You’re trying to embed yourself (rather than your company) in existing networks where trust already exists at this stage.

Common misstep: Don’t invest in your own community yet. You don’t have the center of gravity for it.

Rung 3: Customers 51-100

Your network and community growth motions reach diminishing returns at some point.

For mature categories with educated buyers, this is where paid acquisition takes over. For emerging categories, that’s rarely an option. We couldn’t generate scalable returns from advertising for the first 3 years at Recurrent.

The alternative is a repeatable growth loop that creates value for prospects before they ever evaluate your product.

Lightfield’s version is one of my favorites. They hosted readings at their office from prominent authors on GTM. The authors agreed because each attendee got a copy of the book, courtesy of Lightfield. Everybody won:

• The events attracted founders who cared about the topic.

• Lightfield got a room full of ideal prospects in a relaxed setting.

• The authors sold a bunch of books.

Lightfield has run at least 3 of these events and plans to hire a dedicated person to increase the frequency. They treat it as a pure GTM investment because roughly 25% of event attendees sign up for a Lightfield trial within the first month.

That’s a lot different than spraying banner ads and cold emails. Those customers came from delivering genuine value through proximity. When you’ve assembled a room full of your ICP, some of them will want to know what you do. That’s a repeatable loop that doesn’t rely on founder sales.

Tinder built a different loop on the same principle. They worked with sororities at multiple universities to throw exclusive parties where admission required downloading the app. If women joined, men would follow. The value was the party and the product was the ticket.

Airbnb built theirs on the supply side. They sent professional photographers to the apartments of early host signups to improve listing quality. It helped the host get their first bookings, and it also created a this-is-legit moment that locked in supply while attracting more demand.

The common thread is that each company found a way to make their product the natural next step after an experience the prospect already valued.

Test it: Start by documenting what your first 50 customers value most about working with you. How could you deliver a version of that value to prospects who don’t know you yet? Those answers are the start of a potential growth loop.

Lesson: Repeatable growth loops are the bridge between scrappy founder-led sales and scaled growth. They work because they lead with value rather than a pitch.

Common misstep: Don’t default to traditional paid acquisition channels because the creative alternatives feel too small.

Climbing Your Ladder

“Build a funnel” is the right advice for Customer #800. It’s the wrong advice for Customer #8.

Think about early customer acquisition in stages rather than getting your first X customers.

• “How do I get my first 100 customers?” ❌

• “Which rung am I focused on right now?” ✅

Lightfield’s team understood this. They didn’t try to run a Series B growth playbook with their product launch. They climbed the ladder one rung at a time and matched their tactics to their stage.

Your ladder is waiting. Figure out which rung you’re on and commit to the work that rung demands. The next rung reveals itself when you’re ready.

The tactics that keep you afloat in the early days of a new category can capsize you as the market matures.

Slack’s path from category pioneer in 2013 to today is one of the clearest illustrations of this. It shows how dramatically the right moves change at each stage, and what it costs when you don’t adapt in time.

This post walks through each stage using Slack as the lens. If you want the full framework first, start with The Four Waters Framework.

Evolving with Your Category

Category creation follows predictable stages. As the waters around you change, the playbooks and tactics you use must change, too.

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Stage 1: Uncharted Waters (2013)

The idea that companies would pay for workplace chat was unproven when Slack launched. Existing platforms had chat products (AIM, Google Hangouts) but they were seen as places for casual, unstructured messages.

Enterprise communication happened through email. That meant there was no existing budget or line item for team messaging, outside of some small dev-focused tools.

That constraint turned into an advantage. No established playbook gave Slack permission to build differently:

• No MVP. The early product was polished enough that initial users helped peers see the potential and create the internal business case.

• No IT. Focusing on end users let Slack bypass IT leaders who had no dedicated budget and could quickly smother adoption.

• Ecosystem first. Slack invested in integrations early, positioning as a multiplier rather than another standalone tool.

The lesson: In Uncharted Waters, you’re building belief rather than capturing demand. Traditional growth channels and tactics may not help you yet.

Stage 2: First Voyage (2014–2016)

Slack reached 1 million daily active users within 2 years. At that point, tech company prospects got it immediately. That drew attention from serious competitors, who reacted with product pivots (Microsoft Yammer) and bolt-on acquisitions.

Slack used its head start well. Rapid releases (e.g. threading, emoji, integrations) kept competitors focused on parity while Slack kept moving the target. By the end of this stage, “slack” had become a verb and corporate FOMO created inbound demand.

The lesson: First Voyage is when you make clear to the market who is winning. Get it wrong and you educate the market for the competitors chasing you. (Think: 2nd mouse gets the cheese.)

Stage 3: Charted Course (2017–2019)

The category was undeniably real. Mainstream companies across industries adopted structured real-time communication and nobody was saying “we’ll just stick with email” any longer.

Then Microsoft launched Teams by bundling into Office 365 at no additional cost.

The Charted Course trap emerged: Slack had built a strong product and a loyal user base, but hadn’t built enough defensibility against a distribution-based attack. What had looked like network effectings and switching costs for Slack suddenly didn’t appear as strong.

Microsoft’s bundling move was predictable in hindsight. The category was valuable enough to attract a platform player, and platform players compete with distribution rather than features.

The lesson: Charted Course is when you solidify defensibility. Network effects, ecosystem lock-in and brand moats begin to matter. While Slack built some of these, they didn’t have an answer for Microsoft’s bundling.

Stage 4: Crowded Waters (2020–2021)

COVID accelerated adoption of all workplace tools — one of the happiest professionals I ever met was a Zoom sales manager in 2022.

As Microsoft Teams exploded growth through bundling, Slack needed to bulk up to survive in the saturated market.

Result: Slack sold to Salesforce in 2021 for $27 billion. Slack couldn’t win the Crowded Waters fight independently. The acquisition reoriented the competition between two platforms rather than two products.

The lesson: In Crowded Waters, operational excellence and corporate development (including M&A) matter more than innovation. Sometimes the right move is redefining who you’re fighting with rather than who you’re fighting against.

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What Slack Got Right and Wrong

Slack executed the early stages masterfully. They built the right product for Uncharted Waters, ran the right playbook in First Voyage and became synonymous with a category they created.

The costly missteps appeared in Charted Course. They didn’t build defensibility fast enough when the window was open. Even if Microsoft’s bundling advantage was foreseeable, Slack didn’t have an answer for it.

The tactics that made Slack great in the early 2010s weren’t enough to protect them by 2020. Understanding which stage you’re in is essential to running the right playbook.

Now you’ve got the framework to avoid the same mistake.

Products in mature categories can activate new customers in minutes because they’re dealing with educated buyers. For a company like Dropbox, everybody understands file storage. Upload a doc, create a password, done.

Webflow couldn’t do that because nobody had experience using a visual designer.

Users signed up, opened the editor, and fumbled through layout properties and the CSS box model. They didn’t have the context or experience to value the possibilities.

That’s a defining challenge of emerging categories: Our prospects are encountering an entirely new way of addressing a problem, and that requires a learning curve before value can be recognized.

Melissa Tan, Webflow’s head of growth, came from Dropbox where growth engineering was programmatic. She shared that activation at Webflow happened over several sessions with lots of learning along the way. The standard onboarding playbooks and optimization tactics didn’t work.

I experience this at Recurrent every day. None of us grew up with an electric car. For a first-time EV owner, our product solves problems they don’t know they have yet. People need to understand some pretty intimidating basics on battery health and degradation before they can appreciate the value of the data at their fingertips.

The task for us is to fully appreciate how and when comprehension happens for our customers. Here’s a playbook that I derived from Webflow (and Notion and Clay) that your team can steal.

The Aha Sequence Playbook

Most growth playbooks assume your prospects already understand the problem you solve. Essentially, the conceptual groundwork is in place for them thanks to competitors and lots of prior experience.

In less developed categories, that groundwork doesn’t exist. The prospect has to understand the problem and solution before they can value what you offer.

1. Map the Comprehension Gap

People exploring Webflow for the first time needed to understand the design model, layout properties, and visual development principles before the product could deliver on its promise. It sounds like a product problem, but it’s really a comprehension problem.

The team ran two-week user diary studies — screen recordings with play-by-play narration — because traditional analytics couldn’t capture where onboarding broke down.

They discovered that new users consistently got stuck just before critical breakthrough moments. It wasn’t because the onboarding flow was bad or the product was buggy, but because the concepts were totally new.

Prospects didn’t understand enough to know how to find value.

Test it: Make a list of the concepts your customer needs to grasp before your product clicks for them. For Webflow, it was the CSS box model. For Recurrent, it’s battery degradation basics.

• Where are your customers supposed to learn those concepts?

• Do they need them before, during or after onboarding?

That’s your comprehension gap.

Lesson: Prospects without the experience or context needed to appreciate what you’re offering is more of a comprehension barrier than a conversion barrier.

Common misstep: Don’t treat confusion like a UX problem. Cleaner design and crisper calls-to-action won’t necessarily fix it.

2. Sequence the Moments

There’s no single “aha moment” when users lack the foundational understanding to appreciate your product. Instead, we need to orchestrate a sequence of smaller realizations that build on each other.

Webflow’s onboarding checklist has 6-10 items, each designed to deliver a different moment of understanding. They explain the purpose of each one before diving in to set the expectation that this is more of a learning journey than a product tour.

The sequences are also tailored to the path. Users starting with a blank site get a different sequence than users starting from a template.

• Blank-site users need a preview of what’s possible before they care about building it.

• Template users can see what’s possible so they need to experience the ease of modifying it.

Whether you have a product or service business, it’s different from the standard playbook of “get people to the core action ASAP.” Rushing to the destination is counterproductive when comprehension is the bottleneck. We have to sequence the learning that makes the outcome meaningful.

Notion faced a version of this with the blank canvas problem. A new user opening an empty workspace doesn’t know what’s possible, let alone what to build. “What will you use Notion for?” became the first step so the product could pre-load workspaces with relevant templates. This shows people what’s possible before asking them to create it themselves.

Test it: Sequence the essential concepts from Step 1 into the (ideal) order of operations: Which understanding enables the next? That’s the sequence taking shape.

Lesson: Each small realization should guide customers to the next one. Even if customer activation takes weeks, we can deliver bite-sized understanding in a series of moments.

Common misstep: It’s rare that one-size-fits-all. Different customers arrive with different levels of comprehension so it’s best if we can meet them where they are.

3. Clear the Path

Customer patience is often correlated with understanding. In other words, is the destination worth reaching?

• I’ll spend 90 minutes setting up a new TV, including painfully logging into each of the apps with the tiny remote.

• An AI app with bold promises on efficiency gets 90 seconds before I cancel the account.

Webflow’s diary studies uncovered what the head of growth described as “death by a thousand paper cuts.” These were small friction points that individually seemed minor but collectively drove users to quit before comprehension could take hold.

For example, users consistently got stuck on the layout feature because it required understanding a specific model. The team formalized a Webflow University and built onboarding offramps to get people the context they needed to be successful.

Test it: Think about the last 5 customers who didn’t make it.

• Where did they get stuck?

• Was it because the concepts were confusing or the experiences were confusing?

Those are different problems.

Lesson: Comprehension problems need education, whereas friction problems are often in need of simplification.

Common misstep: It’s easy to see customer education as a support function that should be automated as much as possible. Imagine it as a strategic asset rather than a CS cost.

4. Bridge the Sessions

Education takes time. Since time and customer adoption are enemies, that means builders in emerging categories need to be very intentional.

Webflow uses a variety of tactics to signal progress and possibility.

• Tutorials explain their purpose before diving in.

• Users check off milestones as they build.

• Estimated completion times set expectations.

Clay confronted this by forcing early customers into a public Slack channel. Users who might have quietly abandoned the product instead saw peers working through the same learning curve. The shared channel shortened learning curves while providing proof that the journey was worth finishing.

As we covered in Clay’s ecosystem playbook, that Slack channel evolved from a support hub into the peer community that became Clay’s powerful growth engine.

Clay also flipped sales demos into live onboarding calls. Instead of pitching the product, they had prospects share their screen then walked them through solving their own real problem inside Clay. The customer left with an actual, valuable outcome. That’s a session bridge to bring them back.

Notion pre-loaded workspaces with templates based on user goals that gave people something to return to immediately. That gap between “I can see it” and “I can make it” was a reason to come back.

Test it: Walk through your customer’s first week from their perspective. After their first real interaction, whether that’s a product session, a sales call or a demo, what specific reason do they have to come back tomorrow?

Lesson: Patience isn’t finite. It’s a resource you can replenish.

Common misstep: There’s a tendency to fill the gap between sessions as a marketing problem with generic drip campaigns. The best bridges aren’t reminders, they foster reasons to continue by:

• Connecting to something the customer already learned

• Previewing the next realization they’re close to reaching

Building Your Sequence Playbook

Our customers likely don’t have the context they need to fully appreciate what we’re offering them. We can’t fall into the trap of viewing it as a product flaw to fix, a marketing message to push or a growth lever to dial.

• “How do we get prospects to activate faster?” ❌

• “How do we guide prospects through understanding why this matters?” ✅

Webflow’s product takes weeks to learn. That complexity could/should have stunted their growth. Instead, they built a $4 billion company by treating education as the product experience.

Your users are out there. They just don’t understand why to appreciate you yet.

Intent-based outbound is the #2 investment area for growth teams this year. Everyone’s buying the same tools, using the same signals and automating the same outreach.

The brands finding an edge aren’t necessarily doing it with better tools. They’re capitalizing on their proximity to the customer and how they can spot things that competitors can’t.

“I found that the biggest returns from growth actually come from a deep intuition about what will work coupled with deeply understanding your buyer,” said Brandon Camhi, former VP of Marketing at Rippling, on the GTM Engineer podcast.

That’s different than signing up for Apollo and filtering by company size.

We’re also using signals at Recurrent to drive a lot of our growth right now. The signals we track look at historical market metrics from publicly accessible data combined with signals from the executive team at prospects that show they’re ambitious and progressive with technology. Everything is technically public. All sourced with Claude Code running daily checks.

That’s the inversion.

Most signal-based playbooks are built for mature categories where buyers know they have a problem and are actively shopping for a solution.

In emerging categories, your prospects don’t know they have a problem yet. The signals you need aren’t at the bottom of the funnel. They’re at the top to identify who is likely to be receptive to education, in order to one day be in the market to buy.

Here’s a framework to help you find them.

The Signal Inversion Framework

Prospects already know they have a problem and what solutions look like in mature categories. They’re shopping. The job is to intercept them or at least become part of their consideration set.

That signal doesn’t exist yet in newer categories. The prospect isn’t searching because they don’t know there’s something to search for.

That’s a much different question:

• “Who’s ready to buy?” ❌

• “Who’s about to have a problem they don’t know about yet?” ✅

That is the foundation of the Signal Inversion Framework. Instead of looking for purchase intent, we’re looking for the conditions that precede the problem so we can start the education process before your competitors even know the prospect exists.

1. Identify the Pre-Problem Signals

When Brandon Camhi joined Rippling, the company was doing what most startups do: blasting non-personalized emails and spending a little on paid ads. Only 10-15% of demos came from campaigns with any intent signal behind them.

A year later, that number was 60-70%. And when COVID hit and everything else went to zero, the only campaigns still producing were the ones driven by signals.

Good/bad news: the signals that worked weren’t sitting in a tool.

Camhi built Rippling’s signal engine by listening to Gong calls, talking to sales reps and studying what was true about customers before they became customers. He started from the destination and worked backwards.

You’re not looking for buying intent. You’re looking for the conditions, behaviors and situations that exist before the prospect realizes they have a problem worth solving.

The signal is not intent. It’s more like a precondition.

Test it: Look for patterns in the conditions that preceded awareness in your last 10 closed-won deals. You can include demographics, firmographics and psychographics but I’ve found that those can distract rather than aid the process. We’re looking for patterns more than criteria.

Lesson: The most valuable signals are indicators of inevitability. If X-> Y-> Z, we’re trying to solve for X.

Common misstep: Don’t confuse pre-problem signals with broader ICP criteria. “SaaS company with 200 employees” is a firmographic filter. A signal should tell you something is in motion.

2. Source Signals from Behavior

The standard data tools (Clay, Apollo, ZoomInfo) are powerful, but if you and your competitors are all pulling the same signals from the same vendors, those signals stop being an advantage.

In the best case scenario, they’re table stakes. More often, they’re distractions.

Kyle Poyar’s research reveals that intent-based outbound is one of the top investment areas in 2026. That means the signal commons is getting more crowded.

The edge comes from going up-funnel to where those platforms can’t see or don’t know what they are looking at.

At Rippling, Camhi listened to 3-5 sales call recordings every week in Gong. He discovered that:

1. Brand investment was systematically undervalued in attribution.

2. Prospects displayed similarities that were not visible in firmographic filters.

At Recurrent, our signals work similarly. We combine publicly accessible data that individually aren’t very meaningful, but together paint a picture of a prospect whose business trajectory makes our solution increasingly inevitable.

Test it: Take the pre-problem patterns from Step 1. Think beyond the obvious or readily available to answer these questions.

• What kind of quantifiable data could serve as a proxy for this condition?

• What combination of two or three of these, taken together, would give you high confidence that this prospect is approaching the problem your product solves?

• Which investors, advisors, AI companions, vendors or distant LinkedIn connections could help you find the data sources behind these signals?

Lesson: A proprietary composite doesn’t require proprietary data. It requires proprietary thinking about what combinations of public data actually mean something.

Common misstep: Teams often build composites that are too complex to maintain or too abstract to act on. It’s better to hone in on one signal that you’d bet money on.

3. Trigger Education

In a traditional signal-based workflow, the signal causes the output: email, LinkedIn DM, even direct mail like Rippling.

1. Signal: Buyer is ready

2. Output: Tailored pitch

For those of us building in emerging categories, the signal should be saying “this person is about to encounter a problem they don’t know about yet.”

The response needs to match.

1. Signal: Problem is emerging

2. Output: Helping prospect name or recognize the problem

It’s too early for the output of your signal to be a pitch. It’s only the beginning of an education process.

Test it: Map your signal triggers to ideal educational touchpoints. “When we see [signal], the prospect sees [educational content].”

Lesson: Companies that use signals to start educating will build demand that their competitors don’t even know exists.

Common misstep: “Education” doesn’t mean a generic drip campaign. Relevance is what separates education from noise.

Building Your Signal Inversion

The intent data gold rush is real. That’s because it works for companies in mature categories with known buyers and established purchase behaviors.

But if you’re in an emerging category, the standard playbook has it backwards. We’re looking for prospective learners who, with the right information, will become buyers.

• “What signals tell me who’s ready to buy?” ❌

• “What signals tell me who’s about to need something they don’t know exists?” ✅

Rippling’s story is valuable because the underlying principle can be adapted for you: Success came from getting close enough to the customer to identify what preceded conversion. Only then did they go on a scavenger hunt to find data to inform the signal.

That’s a path available to most founding teams willing to do the work.

Your prospects are out there. They just don’t know they need you yet. The signal is how you find them and education is how you earn the right to help them.

What it became is far different from how it started.

Clay didn’t start with a partner program. There were no tiers or certifications. For years, their entire community infrastructure was just a Slack channel they forced people to join.

The vibrant ecosystem sprouted and grew because of Clay’s approach. CEO Kareem Amin even told his team to engage with their product, customers and community like gardeners. “We’re nurturing growth, not directing it.”

I’ve spent dozens of hours studying Clay alongside Notion and Figma, two other brands with world-class customer communities. The big difference is that Notion and Figma are horizontal tools with massive addressable markets, and the lessons aren’t universally applicable.

Most of us are building brands that don’t fit that model. Clay’s playbook is more transferable because it built around a narrow ICP, and that constraint is actually what made it work.

At Recurrent, we think a lot about our customer community and I’d put it up against any other company our size. But ours looks like a seedling compared to Clay’s thriving forest.

After tons of research and years of lived experience, here’s the 4-phase sequence for knowing when and how to build an ecosystem for emerging products and services startups.

The Gardener’s Sequence

Most ecosystem case studies focus on the tangible outputs: Slack groups, ambassador programs, the templates. Less has been written about what had to be true about the product and the ICP before the community could form and compound.

That’s the gap this framework attempts to fill.

1. Prepare the Soil

Before Clay had an ecosystem, there was a constraint: a narrow user base with lots in common and incentive to learn together.

This wasn’t accidental. Clay kept a waitlist active even after scaling past millions in ARR. Co-founder Varun Anand said they dropped the waitlist at one point, but “one of the best decisions we made in the early days” turning the waitlist back on. It gave them the ability to be hyper selective about onboarding a narrow customer persona. Every customer had lots in common.

They also made a choice that seems borderline reckless: Clay stopped providing email support and web chat. The only way to get help was a public Slack channel. Every early customer was onboarded with a 30-minute Zoom call, and Varun wouldn’t let them off the call until they joined the channel.

This did three things at once:

• It limited the frivolous support requests since people were surrounded by 200 peers.

• It created a space for participation and collaboration among peers.

• It helped customers feel seen because everyone in the channel had similar challenges and the same goals.

The Slack channel organically evolved from a support channel to a peer group. Customers were learning from each other.

Test it: Imagine a room filled with only your most engaged users.

• How much do they have in common?

• Do they share enough context to help each other without your involvement?

• What would make them more likely to be collaborative vs competitive?

Lesson: A homogeneous early community is the soil that everything else grows from.

Common misstep: Don’t worry about community size here. Clay’s patience to stay narrow is what created the value that kept people coming back.

2. Spot the Organic Growth

Clay’s early ICP was agency owners. These people had clients, so they could pull through the product and Clay could grow with them. With their curated and narrow customer base, Clay was able to pay close attention to them and began noticing how they talked about the product:

1. Agency owners used LinkedIn to show off their creative Clay workflows and position themselves as experts in the emerging tech. Sharing about Clay helped the agency attract more customers, which helped Clay add more brands to its platform.

2. Power users went deep in private WhatsApp groups. GTM people wanted to learn with peers but did not want to share every trick publicly.

3. Slack users answered questions in the channel before the Clay team could respond.

4. People promoted themselves as “Clay experts.” If people could build a career on Clay expertise, those people would become motivated advocates with aligned incentives.

The infrastructure only works if organic energy already exists. The Slack threads, LinkedIn posts, WhatsApp groups, and self-appointed experts are only examples of signals that tell you the soil from Phase 1 is fertile.

Test it: Make a list of the places that people talk about your product or the problem that you solve. Social listening tools like Sparktoro or Google Alerts can be a good start, but they are not great at identifying uncommon or private channels. That’s where it’s helpful to talk to customers and query the collective wisdom of AI tools to flesh out your list.

Lesson: You can’t manufacture organic energy. But you can miss it. The signals are often in places that won’t show up in your dashboards.

Common misstep: Don’t interpret current customer silence as a signal of long term potential.

3. Feed What’s Growing

Clay founders (and an industry influencer early hire) started partnering with customers behind the scenes:

• Telling them about new features

• Sharing lessons to help them win new business

• Creating personalized content for them to share

Clay realized UGC is most powerful when people are creating something, because then they can share what they made. Since Clay is a tool for building workflows, it gave their audience of builders something to show off. The content wasn’t testimonials or reviews. It was “look what I built.”.

Clay spent “a considerable amount of time supporting our experts with their own marketing campaigns, from promoting new business lines, to webinars, to one-off promotions,” the Clay team explained. They even use internal software to help creators design personalized videos about Clay features in their own voice. “At the end of the day, we want to help them look legit because if they grow, we grow.”

That last line is the governing principle of this phase. You’re investing more in your community’s success than you’re extracting from it.

Test it: If organic signals from the previous stage to find where you can enable those people without directing them. What would it look like to help your most active customers grow — their business, reputation, whatever?

Lesson: The key to success is aligned incentives, like we found in the Tesla referral program. You help your customers grow, which helps you grow.

Common misstep: Clay’s “gardener” philosophy nurtured authentic excitement at a time when structure and guidelines would have smothered it. Don’t try to over-engineer UGC.

4. Build the Trellis

Only after organic growth was undeniable did Clay formalize the ecosystem with the structure required to scale it.

• Programmatic Community: Clay Clubs are events with a dedicated non-employee host. Clay helps them find a venue, covers the cost, and assists with promo and attendance.

• Incentivized Content: Clay Creator programs gave customers formal reasons to post about Clay, but the real incentive was that the content helped customers grow their own businesses.

• Credentialed Expertise: A partner program launched with escalating benefits and requirements, including affiliate rev share so partners earned from bringing on new Clay customers.

• Official Role: Clay created a “GTM Engineer” job title, posted public job listings, and watched the market adopt it. Today there are hundreds of GTM Engineer postings at companies like Cursor, Webflow, and Notion.

• Literal Alignment: Clay let its community invest at the same $1B valuation as top VC firms like Sequoia. Priority went to community members that reinforced the benefit of the ecosystem, both today and in the future.

Each of these moves would have totally bombed if they launched too early. The partner tiers work because there are enough successful partners to populate them. The expert directory works because the experts already had credibility. The equity offering works because the community already felt ownership.

The trellis simply supports growth that already exists.

Test it: It’s only after your customers have reached diminishing returns in Phase 3 that Phase 4 should be explored. Specifically, try to identify:

• Where could program formalities help customers extract additional value?

• How could structure deepen your relationship and further elevate with power users?

• What would be the most minimum viable and most extreme version of each program? (Clay let people invest in the company.)

Lesson: The infrastructure should formalize what’s already happening.

Common misstep: In the Test It step above, I intentionally referenced your customer’s diminishing returns, not your company’s. The signal you’re looking for is not your own scale or efficiency or margin.

Gardening > Engineering

Most ecosystem programs fail because they try to start at Phase 4. Six months later, the partner program has 12 members and no momentum so it gets sunset.

Take inspiration from Clay that ecosystems are most vibrant when cultivated.

They constrained their community until it was dense enough to sustain itself. They watched for organic signals instead of manufacturing them. They invested in their users’ success before formalizing any program. And only when the growth was undeniable did they build the infrastructure to support it.

• “How do I build a partner program?” ❌

• “Is my product and ICP ready for one?” ✅

The companies that get this right won’t be the ones that copy Clay’s partner program. They’ll be the ones that copy Clay’s perspective.

Every AI notetaker has some version of user generated content as a growth channel. Otter, Circleback and Fireflies all encourage users to share meeting recaps with participants.

1. Notetaker grabs emails from calendar invite

2. Sends the meeting recap to demonstrate product value

3. Loads up on CTAs and remarketing to drive new adoption

It’s interesting but not new.

Granola’s iteration found a way to make that moment more powerful by front-loading the product’s aha moment for non-users. Existing users are actually delivering it to people who haven’t signed up, don’t know who you are, and aren’t even in the market for a solution.

It’s something I think about (and am actively borrowing) at Recurrent. We create vehicle insights that EV owners share when selling a car or helping fellow owners. Our product reaches non-users constantly, and we think a lot about user generated content, but I’ll admit we haven’t fully engineered sharing to front-load the most impact.

Adam Fishman called it user-distributed content. That’s helped me reframe how I think about it, so here’s a framework to help you turn your outputs into potent acquisition channels.

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The Distributed Demo Framework

1. Design the Artifact

Every company has at least one output that reaches non-users. That’s true across sectors for both product and service providers.

Granola’s artifact is the shared meeting note. After every call, the user gets an AI-enhanced summary with action items, key decisions, and a prompt bar to go far beyond a TL;DR.

They didn’t have to create a new sharing behavior. They helped users by embedding in a behavior that already existed.

This is what separates strong distributed demos from forced ones.

A counter example is something I noticed when onboarding Fyxer. They prompt users to invite coworkers at every opportunity you could imagine, and a few that you couldn’t. (Their growth team said the tactic won an A/B test.)

But that’s not a demo, not an aha moment.

Test it: Make a list of outputs that reach non-customers through customers. Don’t prioritize by frequency or expected impact, but document some of that:

• How often does that happen?

• Is the output valuable on its own or does it require context?

• What’s the best possible reaction you could expect?

• What’s the likelihood of that reaction happening as it stands?

Lesson: The highest impact artifacts align with existing, frequent user behaviors. If we can focus less on creating the habit, our energy can go into upgrading an existing one.

Common misstep: I think marketers and growth teams are particularly prone to thinking about what people should be doing, rather than what people are actually doing. People should floss each day, but there’s a reason we call it the Toothbrush Test instead.

2. Front-Load the Aha

People who attend a meeting with an Otter or Fireflies bot get a readout. It’s useful, but predictable and static.

Non-users who get notes from Granola get an interactive page. They can use “Ask Granola” to query far deeper than the transcript: “Where in the meeting did I demonstrate the most leadership?”

Since Granola researched you based on your contact info, and can tailor responses to your role and professional context, the insights tend to be incredibly impressive.

That’s an aha moment for a non-user.

Test it: Go back to the list you made in Step 1. For each opportunity, revisit the questions with a focus on the aha moment:

• Is the output value tangible and impactful on its own?

• What’s the best possible reaction you could expect?

• What’s the likelihood of getting the best possible reaction?

Common misstep: Don’t gate it. Granola deliberately lets non-users interact with shared notes without an account.

3. Remove Sharing Friction

Most collaboration tools default to private. That protects privacy, but it also adds friction at the exact moment where distribution happens.

Granola optimized for distribution because meeting notes are inherently collaborative for the people who were in the room.

Beyond sharing links, Granola prompts to integrate with team tools. Notes can be pushed to Slack, Notion or your CRM.

That is different than “click to email” or “copy and paste,” which are both opportunities for the growth loop to die.

Test it: Decide up front how you’ll evaluate the impact of your new growth channel. A few ideas:

• Share rate: What percentage of your artifacts get shared?

• Signup rate: What percentage of non-users who view an artifact take steps toward conversion?

• Retention rate: Of those who convert from a shared artifact, how does retention compare to other channels or averages?

• Time to distribution: How long does it take a new user to share their first artifact with a non-user and continue the loop?

Lesson: The distributed demo loop is measurable, but only if you’re looking at the right part of the funnel (which is often before the funnel starts).

Common misstep: It’s easy to add more Share buttons. It won’t move the needle if you’re not removing the friction around them at the same time.

Building Your Distribution Loop

It’s tempting to read this framework and think it only applies to software products.

• A consulting firm’s slide deck is an artifact.

• A financial advisor’s portfolio summary is an artifact.

• An agency’s campaign brief is an artifact.

Any time your IP lands in front of a member of your target market that isn’t your customer, I think there’s a distributed demo opportunity.

Most companies have the raw materials. What they’re missing is the intentional design.

Granola didn’t invent meeting note sharing. They engineered the moment when a non-user receives a shared note and thinks, “Daaaaang, I need this.”

That’s the distributed demo doing its thing: a product experience that happens before signup, delivered by your existing users, with zero marginal cost.

Audit your outputs. Front-load the aha. Remove the friction. Measure the handoff.

Your users are already distributing something. The question is whether you’ve made it worth receiving.

The marketing team at Lovable says they invest 95% in unproven growth levers and only 5% on optimizing what already works.

Two different companies. Two different allocations. Both finding success and outpacing their peers.

I spent a lot of time over the past week on which approach was “right.”

It turns out that’s the wrong question. The right question is asking where each company is in its category and where the category is in its maturity.

At Recurrent, I’ve watched our own allocation shift dramatically as the EV market matured, and early entrants found their traction in different corners of it. What people know and think about electric cars is much different today than 5 years ago, and so is how we allocate our growth investments.

After studying the growth models at more than a dozen high-growth companies, including those with my fingerprints on them, here’s a framework you can use to treat your growth channels like an investment portfolio.

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Venture-to-Bond Budget Model

When it comes to investing, 25- and 65-year-olds shouldn’t have the same portfolio mix. Financial advisors would tell you that a younger investor can absorb volatility and be more aggressive with growth stocks. The older investor needs predictable returns because there’s less time before retirement to recover from a bad quarter.

Growth channels work the same way.

An early-stage company in an emerging category can (and should) bet heavier on unproven channels because (1) there’s often no proven playbook to follow and (2) the potential upside outweighs the relative cost. No bets, no rewards.

Meanwhile, a publicly traded company can’t boom in Q1 and bust in Q2 because their marketing experiments didn’t pan out. They need channels that deliver predictable, repeatable pipeline.

But most growth teams don’t think about their channels this way. Instead of treating channels as a line item in a budget, we need to be thinking of it as an investment portfolio with a specific risk/return profile.

The Venture-to-Bond Budget Model uses three channel classifications that we’ll map to your company’s maturity stage (drawing from the Four Waters Framework) to help you find the right allocation for where you are now.

1. Blue Chips are proven channels with predictable returns. You know the CAC, you know the conversion rate, you can forecast with confidence. These are the bonds and index funds of an investor portfolio.

2. Growth Stocks are channels showing early promise but unproven scale. These will need to be nurtured to determine if they’ll graduate to Blue Chip status.

3. Venture Bets are totally unproven channels, new experiments, emerging platforms, unconventional plays. Most will fail. And we’re ok with that.

Now let’s build and manage your portfolio.

1. Diagnose Your Stage

Category maturity is the single biggest input to your allocation. It’s the equivalent of your age in a financial portfolio.

I covered category maturity stages in the Four Waters Framework, and those stages map directly to how aggressive your growth portfolio should be:

• Uncharted Waters is full of Venture Bets. You don’t have proven channels yet because the category barely exists. Lovable reports having to rediscover product-market fit every 3 months so that puts their 95/5 mix into context.

• First Voyage is when your early Venture Bets begin producing signal. Some are graduating to Growth Stocks and it’s getting easier to identify and cut losses faster. This is where Recurrent is today.

• Charted Course is when your early Growth Stocks are graduating into your first Blue Chips. This is where Attio sits today with 60% in Blue Chips, 20% in Growth Stocks and 20% in Venture Bets.

• Crowded Waters is when your portfolio is overwhelmingly Blue Chips with a focus on optimization. Venture Bets are smaller, more targeted, and designed to find an edge in an increasingly competitive landscape.

Test it: Plot your company on the Four Waters Framework. Then list every growth channel you’re investing in and classify it as a Blue Chip, Growth Stock, or Venture Bet.

Lesson: The channel mix that got you where you are today is almost certainly not the mix that gets you to the next stage. Understanding that is enough to put you ahead of most of your competitors.

Common misstep: The maturity stages don’t have perfect delineators so I’ve found that most teams don’t realize when they’ve advanced to the next stage. Attio’s 60/20/20 split isn’t permanent. Two years ago it looked different. Two years from now it will look different.

2. Land and Expand

Time and money are precious resources in the early days. It always makes sense to start with the most logical (often manual) growth levers to extract as much as possible before deliberately expanding.

Attio’s leadership team (Nicolas, Alexander and Alex) described how the company started by building in public on Twitter and LinkedIn.

Next, the inherited cohort of VC users from their previous product created a slow but valuable organic feeder that compounded without paid spend.

Only after that did they experiment with search marketing. They tried SEO and it didn’t work. They tried paid search to find pockets where the economics were right and, as we’ll see, got more aggressive over time.

Test it: Write down your current channels in the order you adopted them. Look for sequences that follow a logical and insightful progression, and where you deviated.

• What did you try too early that you could potentially revisit now? For Recurrent it was paid social.

• Which Venture Bets have failed to mature and need to be replaced?

• What would you need to see from one of your Growth Stocks to double down as a Blue Chip investment?

Lesson: Seeing your entire portfolio written out and categorized should surface 1-2 immediate opportunities. I’ve never done this exercise with a marketing leader and not found an actionable outcome.

Common misstep: “This didn’t work when we tried it” is an opportunity to revisit if the company or category have evolved.

3. Grade Your Positions

The hardest part of managing a growth portfolio is having the confidence to double down on a Growth Stock or abandon a Venture Bet, even when the team wants it to win.

It helps to set the criteria before you place the bet:

• Target metric and threshold: What specific number is needed to signal this is working?

• Time horizon: How long will you run the bet before making a graduation / abandon decision?

• Maximum investment: What’s the ceiling on dollars or hours before you require positive signal?

When Attio tested paid search, they were competing with incumbents whose marketing budgets were larger than Attio’s company valuation. Bidding on “best CRM” was unlikely to pencil.

But large competitors and budgets always have oversights and inefficiencies.

I’ve lived this at Recurrent. We operate in the automotive space, so we bump into some of the most recognizable brands in America — companies that run Super Bowl ads and sponsor the popular podcasts on your playlist.

We can’t compete in the same places. But we have been able to find opportunities in places that might not be important enough for them to care but have a material value to us.

One example is that Recurrent invests early and often in rising stars on YouTube. Instead of buying transactional air time from massive influencers, we found creators just getting started. To us, their success was inevitable. To them, Recurrent believed in them before anyone else and contributed to their success by growing with them. Their growth became our growth.

That’s the mindset startup teams need. We’re not trying to win the channel. We’re trying to find the sliver of the channel that the rest ignores.

Test it: Treat each channel like a pitch competition. If you had to pitch each channel to an investor, would they buy it as a Blue Chip investment? Look for the places that you have strong defensibility, repeatability, scalability. And where you don’t.

Lesson: Most startups can’t compete head to head with incumbents. But we don’t do this because we like fair fights.

Building Your Portfolio

There’s no “right” allocation. That’s the whole point.

Lovable’s 95/5 split toward innovation works because they’re in an AI category that’s moving so fast that last quarter’s proven tactic is this quarter’s legacy approach. Attio’s 60/20/20 works because they’ve found channels that deliver while still needing room to discover what’s next.

• “What’s the right ratio?” ❌

• “Does my current ratio match where I actually am?” ✅

The answer changes. Lovable’s allocation will look different a year from now as their category matures. Attio’s already has.

If you’re in an emerging category and 80% of your budget goes to proven channels, you’re investing like a retiree.

If you’re scaling toward predictable revenue and 60% of your budget goes to experiments, you’re investing like a 20-something day trader.

Your growth portfolio should mature with your company. The teams who figure that out will spend less time wondering why last quarter’s playbook stopped working.

Linear added 10,000 people to a waitlist before launching its platform. Jira, Asana and a dozen others were meeting basic needs, but Linear spoke to their beliefs: software tools should be built for the people who actually use them.

That belief became a manifesto and philosophy on how software should be built, rather than a blatant pitch for adopting their product.

As the category competed on features and pricing, Linear rallied people to a conviction. “The brands in our market are non-existent or negative… it’s hard to even say what these companies stand for,” said CEO Karri Saarinen in a First Round interview.

I’ve witnessed the power of strong corporate beliefs at Recurrent. It unites the team and gives all of our stakeholders a clear view of the world that we’re trying to create in an emerging category. When everyone understands what you believe, positioning the brand in the market gets much easier.

That’s why Linear’s growth is a positioning story. Here’s a framework that any team can use to build its own belief moat.

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The Belief Moat Framework

B2B companies tend to position themselves around features and benefits. That works until a competitor inevitably copies the features, matches the price or in some other way dilutes the differentiation.

Belief-based positioning operates on a different plane.

We’re not asking prospects to evaluate products. We’re asking them to share our view of how the world should work. That’s a stickier commitment and more difficult to replicate.

Here are four steps to find your moat.

1. Identify the Unspoken Compromise

Every category has a tradeoff that everybody accepts but nobody likes.

• For emerging categories, it could be a limitation.

• For mature categories, maybe it’s just been there so long it’s become invisible.

In project management, the compromise was that tools were built for managers rather than contributors. No shade, but if you’ve ever used Jira, you know what I mean.

Saarinen and his co-founders were individual contributors at Airbnb, Coinbase, and Uber. They lived that compromise daily. As Saarinen described it, “A lot of the tools that we were using were not optimized for the individual contributor; they were optimized for the buyer.”

That’s where belief moats start. It’s a structural and tangible frustration that the market shares, even if it’s quiet or silent.

Test it: Ask 10 customers in your category what they tolerate but quietly resent about the existing options. You’re listening for a complaint with the status quo that (indirectly) 8/10 reference.

Lesson: The unspoken compromise is a philosophical friction that can hide at different levels of an org and with different stakeholders.

Common misstep: Lots of frustrations are real but shallow. “The UI is ugly” is an opinion but I’d argue it isn’t a rallying belief.

2. Write the Counter-Narrative

Once you’ve identified the compromise, codify the alternative. Publicly.

Linear published The Linear Method, a set of principles for how software should be built. It was a declaration of values that resonated with their core audience.

Founding and leadership teams often share beliefs internally. Publishing them is the syndication step needed to reach the rest of the stakeholders.

Saarinen was direct about this: “Your brand is what you stand for. It’s your take or manifesto. What do you hold dear? What do you care about? Then put your work in that context.”

Linear’s early blog post articulating this philosophy helped to add 10,000 industry peers to a waitlist. It’s nauseating to calculate the advertising cost equivalent of that, particularly for a young brand.

Test it: Write a one-page document that describes how your category should work. If you can’t articulate it in a way that you’d be comfortable sharing externally, even with a few testers, you may not have a strong enough belief to build around.

Lesson: An unpublished belief is an opinion, maybe even a smart opinion. A published belief can be a positioning strategy.

Common misstep: I tend to see counter narratives end up as a feature pitch disguised as philosophy or a concept that’s too narrow to resonate with the market as the company scales.

3. Curate Your Feedback Loop

When you publish a conviction, the people who respond are self-selecting. They already share your view of the world. That means their feedback is directionally aligned.

Linear used their 10,000-person waitlist as a selection mechanism. They added roughly 10 users per week, individually selecting the people they thought would be most motivated. Those early users shaped the product through a shared lens of what “good” meant.

This isn’t just a pre-launch tactic.

Saarinen’s design philosophy reinforced this: “In order to be really good for the user… you have to be opinionated. It’s more of the Apple way.”

Test it: Product feedback has a tendency to be viewed as squeaky wheels from a small segment of outspoken users. Look at your last 10 pieces of product feedback. How many came from ideal customers that share your core beliefs about the category? If the ratio is low, you don’t have a helpful feedback loop.

Lesson: The belief doesn’t just attract customers. It filters for the right customers to learn from.

Common misstep: Treating all user feedback equally. The user who wants you to become more like the incumbent is not the user who will help you become the incumbent.

4. Animate the Belief

Linear’s belief shows up everywhere, a characteristic of other strong positioning statements. Linear even chose “issue tracking” over “project management” because it better spoke to engineers: “It doesn’t attract people that don’t know what issue tracking is,” said Saarinen.

From hiring to marketing to sales, Linear tries to embody the belief at every opportunity. Each is a signal to the market that reinforces what the company stands for.

For teams in earlier-stage categories, it’s also worth connecting this back to the Four Waters Framework. The company that first animates a belief often sets the category narrative for everyone who follows. By the time competitors realize that philosophy matters, the position is taken.

Test it: Audit each step of your sales and onboarding. Find the places that are strongest, weakest or nonexistent.

Lesson: The belief has to be continuously legible as customers develop their early impressions of your product or service.

Common misstep: Animating the belief in marketing material is easier, but it needs to live in the product, too. Customers notice when early expectations are not met by reality.

Digging Your Belief Moat

Most categories are still philosophically unclaimed. The incumbents have optimized for features, pricing, and sales motions, sometimes to avoid taking a strong position.

That’s the opportunity.

Linear isn’t eating into Jira’s market share with features or pricing. They orchestrated an authentic belief and let the believers rally to them.

If you can’t articulate what your company believes about your category, you’re often competing on differentiators that lack durability.

Beliefs will always outlive features.

Canva founded itself to democratize design for billions of users. That’s an ambitious market size to chase.

But they very intentionally didn’t market to “everyone” at launch. They spent months obsessing over one tiny audience.

I’ve been analyzing Canva’s growth playbook, and that early restraint is a key part of their success as they build toward a billion users.

The everyone trap

We’re told our entire lives to dream bigger. This is especially true in the startup world where value is so closely dependent on addressable market and customer adoption.

“Go big or go home,” we’re told.

Except that almost never works on Day 1, and it’s especially dangerous in an emerging category.

Canva CPO Cameron Adams described the problem in an interview with First Round Review: when products are pushed out for “everyone,” the messaging becomes impossible. You can’t write a homepage, an onboarding email, or an ad that resonates with a real estate agent and a YouTube creator and a nonprofit director. You end up speaking to none of them.

We understood this at Recurrent and focused on the nerdiest and most passionate EV owners. These are the people who sign up for every app, join every forum, and talk your ear off about their car. By focusing on them, our messaging clicked and our early growth accelerated.

Going wide doesn’t just dilute your message. It dilutes your product signals, your feedback loops, and your ability to build the organic advocacy you need before you can afford paid channels.

Here’s their audience selection framework that any founding team in an emerging category can steal.

First Audience Framework

Ahead of Canva’s 2013 launch, the founding team chose social media managers as their core audience. Notice the specificity there.

• Not “small businesses” = tens of millions of potential customers ❌

• “Social media managers” = thousands of potential customers ✅

Here are the five criteria that I uncovered from that decision and how to use them to eliminate potential audiences until you’re left with the right one.

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1. Feedback Velocity

Social media managers needed professional-quality graphics constantly. Pinterest and Instagram were exploding at the time and the people creating that content were doing it dozens of times per day.

This frequency would give Canva rapid feedback velocity.

Daily users generate more data and stress-test more edge cases than someone logging in once a month. Canva’s team could ship an update on Monday and be able to iterate by Wednesday. This is in part why Larry Page made business decisions with the toothbrush test.

Test it: Look at your pilot customers or waiting list. Make a short note on frequency and variety of use from each potential audience segment.

Lesson: 500 daily users will teach you more in a month than 5,000 quarterly users will teach you in a year.

Eliminate: If the audience needs your product monthly or less, you probably can’t learn from them or keep them engaged long enough to fuel growth.

2. Revenue Signal

Social media managers were professional users. Professional users can quickly realize product ROI and justify product expenses. I would also imagine that people in social media at the time were less blocked by traditional IT gatekeepers or worked as solopreneurs without budget blockers.

Lesson: Early users need an easy way to value ($) the product. For a lot of us, that means finding professional audiences and a way to draw a direct line to increasing revenue or decreasing costs.

Common misstep: Free user growth sounds great in a press release, but if your first audience has no incentive to pay, you’ll struggle to prove unit economics when you need them most.

Eliminate: If your audience is solving a nice-to-have problem with no budget pressure, you won’t have the urgency you need to build a base.

3. Organic Distribution

Not many target audiences have more attractive organic reach than social media managers. They are on social media all day sharing their work.

Adams described this dynamic in his interview with Lenny Rachitsky: these users loved being on social media, telling people about the tools they were using, and introducing Canva to others.

“[Early users] need to want to talk to other people about it, because in the early days of your startup you don’t have marketing dollars. You need to really foster the first people that are going to use your product. They’re going to be the ones that are going to spread it and they’re going to set the foundations for your growth.”

Superhuman followed a similar playbook. The email startup launched with a narrow positioning for founders of high-growth tech companies. That audience was comparatively small. But founders talked to other founders. The narrow audience had natural paths for organic growth.

Test it: Find the communities where your potential first audiences already gather: FB groups, Slack communities, Reddit, Discord, industry forums, etc. Are they actively making recommendations or do they see what they do as “secret sauce” to hide from the world?

Lesson: The best first audiences don’t need referral programs or ambassador incentives to spread the word. They share because that’s part of their identity or part of their success.

Common misstep: If your first audience doesn’t naturally share with peers, you’ll have to manufacture every ounce of awareness yourself.

4. Acquisition Cost

Canva found that social media managers gathered in predictable (and affordable) places. Many subscribed to the same public Facebook groups, attended the same conferences, and read the same niche publications.

No part of Canva’s early acquisition strategy required a massive media budget. They knew where to find their target audience and designed every piece of messaging to speak to them.

Test it: For each potential audience, list the 3 ways you would put your product in front of them. It should not take long for the contrasts to jump off the page at you.

Lesson: The constraint isn’t just financial. Expensive channels have slower feedback loops and higher stakes per experiment.

Common misstep: The audience that scores best on the other 4 criteria but requires $50,000 in sponsorships to reach is probably the wrong first audience.

5. Market Bridge

After social media managers, Canva expanded to startup founders with lean teams by adding a Presentation feature designed, in large part, specifically for them.

That created a “yes, and…” opportunity compared to an abrupt pivot in positioning and messaging. Tech founders were among the earliest adopters of social media, so they were hiring the same social media managers.

Test it: Create a relationship map for your first audience. Who do they naturally influence? Who do they share with outside their immediate peer group? We’re trying to identify at least two adjacent audiences that interact with your first audience.

Lesson: It’s best when your first audience sits at a network crossroads vs a cul-de-sac.

Common misstep: A highly engaged vertical audience that doesn’t interact with other verticals can trap you in a niche.

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Choosing your first audience

Run each of your prospective beachhead audiences through these five filters. The audience that survives all five is probably your starting point, even if it feels uncomfortably narrow.

Canva’s founding team always intended to serve billions. They are well on their way today with 265 million monthly active users.

But they had the restraint to serve thousands first, and to serve them so well that those thousands became the growth engine for everything that followed.

If you want a step-by-step worksheet to score your audiences, download the First Audience Framework PDF here.

Security compliance was only required by the biggest enterprise companies so startups didn’t budget for SOC 2. Spending 10 months and $100,000 made it too easy to avoid.

“We’ll do it at some point, but not now.”

Vanta built a shortcut that templatized the SOC 2 process so startups could be compliant in 1/10th of the time for 1/10th of the cost. But that still wasn’t enough to motivate them.

“We’ll do it at some point, but not now.”

That’s a common story in emerging categories: We create a truly innovative way to do something faster, cheaper or with less disruption, but that isn’t enough to meaningfully budge demand that’s stuck in “not yet.”

Instead of focusing on product features, Vanta unlocked demand by animating the moment when the absence of their product would cause painful, quantifiable loss:

Imagine your sales team closes a huge enterprise deal. Then procurement sends the security questionnaire that requires a SOC 2 Type II report. You don’t have one. The deal dies, your competitor wins, your market share stumbles.

• “Achieve compliance faster” ❌

• “Stop losing deals you’ve already won” ✅

The first is about future benefit. The second makes the loss tangible today.

When building in a category where prospects don’t feel urgency, we can’t manufacture it with features and benefits.

Let’s dissect the Tangible Loss Framework for lessons we can apply in our own businesses.

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Becoming a “Must-Have” with Tangible Loss Framework

From the Four Waters Framework viewpoint: Vanta was at a stage called “Uncharted Waters” where the market didn’t recognize SOC 2 compliance for startups as urgent or worth solving. Their primary competitor wasn’t another company, it was a lack of urgency to solve a problem that hadn’t started to bother them yet.

The Tangible Loss Framework that we can derive from Vanta has four steps.

1. Identify the Loss Event

What do prospects lose if they don’t have you? Notice the verb choice of “lose” vs “fail to gain.” It’s intentional.

• “You’ll gain customer trust with SOC 2.” ❌

• “You’ll be compliant with industry standards.” ❌

• “You’ll lose enterprise deals without SOC 2.” ✅

Research on loss aversion explains that people feel losses 2x as intensely as equivalent gains. Losing something, especially something you’ve fought to earn, is a potent motivator.

I’ve had a similar experience with Recurrent, where commercial EV sellers saw battery information as nice to have but not essential. Electric cars made up only 10% of their sales so touting the benefits or potential upside was not enough to unstick inaction.

Identifying the loss event created urgency:

“You’re undervaluing every EV you sell by $2,000 to $5,000 because you don’t understand the battery. That means you’re leaving $3.5 million on the table each year.”

Suddenly the 10% problem became a seven-figure hole in their bottom line.

Lesson: The loss event must be tangible. “You might lose deals someday” doesn’t drive action.

Common misstep: You can’t invent a hypothetical loss. It has to be something they’ve already felt the pain of at least once.

Test it: Map your customer’s worst days in the last year. What went wrong and how could you have helped to avoid them?

2. Quantify the Stakes

Vague statements don’t create urgency. Make the loss concrete and measurable. If they can’t quantify the loss you’re preventing, you can’t build a business case.

1. What deals are being lost or delayed? (Revenue)

2. What does each week/month/year of waiting cost? (Delay)

3. What market share would be lost to competitors moving faster? (Competition)

4. How much time and money is wasted on manual processes? (Efficiency)

Vanta didn’t just say compliance was important. Vanta showed that a traditional SOC 2 process would cost $100,000+ and take 6-12 months. During that time, how many enterprise deals would stall or die? If a company closes $5M in enterprise ARR per year and 10% of prospects ask for SOC 2, that’s $500,000 in pipeline risk.

It’s specific and measurable. Those are the business cases that get a CFO’s attention.

Lesson: Everything needs a concrete number because “faster sales cycles” is too vague to be urgent.

Common misstep: Industry averages are only better than nothing. It’s easier than ever to estimate actual business value from publicly available data.

Test it: Build a simple calculator for your target personas to quantify the stakes.

• Revenue: Deal sizes and number of deals affected

• Cost: Penalties or inefficiency or labor

• Timeline: How often these loss events occur

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3. Align with the Calendar

Manufactured urgency fails with business customers. That’s not what we’re doing here. Prospects see through it. True urgency comes from their business’s calendar so it’s your job to align with it.

In several of the executive interviews that I listened to while studying Vanta, CEO Christina Cacioppo said that they researched a vertical until they could predict 75% of a prospect’s answers.

That helped Vanta align its marketing and sales motions with prospect’s businesses.

Lesson: Don’t try to create artificial deadlines. Find the real ones already in your prospect’s business cycle.

Test it: Map your customer’s businesses to a calendar to understand when loss events are most likely to occur or feel most urgent.

• Fiscal year ends

• Budgeting periods

• Regulatory deadlines

• Development cycles

• Customer renewals

• Industry conference seasons

Step 4: Offer Crash Detection

My truck applied its own brakes when I didn’t see a cyclist weaving through parked cars the other day. The rush of relief was overwhelming because I instantly saw two very different outcomes.

Crash detection is what we’re trying to offer.

Vanta’s core promise was speed. Traditional SOC 2 took 6-12 months. Vanta delivered it in weeks. That meant the difference between losing a deal in the pipeline and closing it.

Lesson: Position yourself as the solution to an active problem, not a tool for future optimization.

Test it: Audit your website and key marketing materials. Do they present a product or crash detection?

When This Doesn’t Work

Loss aversion isn’t universal. The Tangible Loss Framework breaks when:

1. The loss is hypothetical

2. The timing is distant

3. The loss is industry-wide

4. You don’t have credibility

If prospects don’t believe the loss is real or don’t believe you can prevent it, the entire framework collapses. Your marketing goes from helpful to manipulative.

Lesson: Don’t weaponize fear you can’t credibly back up. It erodes trust faster than it creates urgency.

Test it:

• Are prospects already experiencing this loss?

• Can you prove your solution prevents it?

• Is the timeline urgent enough to overcome inertia?

Vanta hit $100M ARR by making compliance urgent. They weren’t manipulating people into believing it mattered. The urgency was always there, Vanta just made it visible.

Your opportunity is the same: Find where your category already has hidden urgency.

Make the loss visible. Quantify the stakes. Show the timing. Offer crash detection.

That’s not manipulation. That’s clarity.