Hi everyone - Most of you are Growth or product people, which means that one of your closest collaborators is probably: Product Marketing. As I’m seeing roles start to merge and overlap, this is an area you should definitely be aware of. What are AI-native PMMs doing and how can you collaborate best with them? What skills do they have that you should maybe learn? I asked our incredible Core PMM from Lovable, Gemma Casey-Swift, to write this guest post to fill you in. Enjoy! - Elena

How product marketing works these days is unrecognizable from even a few months ago.

Some of it’s the available AI tools, some of it’s the speed of feature releases, some of it’s the shifting job roles. But if you’re trying to launch products in late-April 2026 (it may be different next week!), please reconsider what you think you know about PMM.

One of the biggest changes? Product Marketers used to be a bottleneck. Building a lot of elaborate processes (yes, I said the p-word, I’m sorry) that seemed like they were slowing things down.

Now? Well, now the PMM team is a crucial part of helping your org go fast. Here are a few key ways that product marketing at Lovable has built foundations that the rest of our team needs.

(If you’re a Growth or Product person… hey, friends! Send this to your PMM to make sure they’re tracking. But also maybe read it yourself? Spoiler alert: The more you can do your own product marketing, the faster your career and company will grow.)

Let’s do this!

Elena’s Picks

Hey, I’m trying out a new format for my sponsors! I’ll be specifically recommending products and services I personally use and love.

→ Stripe: Ideal for payment processing and all-things monetization.
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→ Customer.io: Ideal for highly-targeted email campaigns based on user behavior.
We use them at Lovable and I’m a huge fan. It’s so flexible and intuitive to use that, before we had our first email marketer, anyone on our team could launch an email campaign! And it was actually cohesive. Now that we do have an email marketer, they’re doing amazing things with it. A product that can serve varying degrees of experience like that is so hard - but Customer.io has nailed it.
👀 Check it out: Learn more.

→ Lovable: What can I say? Yes, I work here. But… I work here because I was obsessed with the product, first. It’s the best way to build an app or site, even if you have no technical experience. Try it out!
🎁 Offer: Get a year of Lovable for free! (For paid subscribers to Growth Scoop)

1 - Enable your team to launch stuff, themselves (vs. expecting everything to go through you)

This is probably the biggest switch. The reality is that we are launching updates wayyy too fast for a traditional PMM-driven launch cadence. In old school companies, you’d have a big Tier 1 launch at your user conference… once a year? Maybe twice if you’re aggressive.

Now, we launch updates that could be tier 1 almost every other week. So, how do we keep up this pace? Definitely not by making everything come through PMM every time. If we did that, we’d always be the bottleneck.

So, instead, we built out the infrastructure to help our team launch stuff on their own.

We tiered launches into a few main buckets:

• Big launches (still Tier 1): These are still big releases (or round-ups of multiple releases) with big moments and active coordination across the teams. Marketing still runs these.

• Tier 2: Still run by product marketing alongside a PM but generally more fluid with a more flexible bill of materials. We often amplify these further post-announcement if the launch is getting good traction.

• Everything else: If it’s not specifically designated for a tier 1 or tier 2 launch, the people building it launch it themselves. Our job as the product marketers is to give everyone the resources they need to do this.

This is the key to going fast. The whole point is to create a culture where people are encouraged to launch their own stuff without PMM being precious. You lose a little messaging control, but you gain momentum. And honestly, some of the content our eng and product team shares goes more viral than any perfectly curated post ever could.

So, what kind of infrastructure are we actually building?

2 - Define your ICP based on actual data (vs. based on brainstorming or wishful thinking)

Providing a clear, consistent Ideal Customer Profile (ICP) is one of the most valuable things a PMM team can provide to their organization. Unfortunately, most of these are all over the place and based on some hand-wavy hypotheticals.

Now, no one has time for an ICP that doesn’t drive value.

How do you get that? The good news is that this profile actually already exists. It’s just buried in your CRM, usage data, support tickets, and that spreadsheet someone in sales has been carefully maintaining.

Here’s how we pull the data with help from our awesome insights team:

• Product data: We dug into usage, retention, ARR, and conversion across the full user base.

• Builder surveys: Captured roles, needs, decision-making, and “definition of done.” Paired responses tracking expectations vs. outcomes across a build cycle.

• Deep-dive interviews: Tapped further into what people were building, why, their emotional state, workflows, needs, struggles, and dreams.

• Internal AI agents (built on Lovable, live in Slack): Built by our insights team and connected to our full library of user calls, surveys, and interviews. We ask questions in natural language and get back themes, quotes, and patterns on demand.

The biggest shift for me was realizing our ICP is genuinely “everyone,” and you can’t ignore that.

My old instinct was to narrow: pick one persona, one segment, one use case, and aim everything at them. But when the product is category-defining and/or general-purpose, demand can show up from solo-builders to huge enterprises all at once. Even if this makes product marketing and prioritization hard, you can’t ignore clear signals.

This is also why ICP reviews can’t be an annual ritual anymore. PMMs traditionally set an ICP in January, build a deck, and let it calcify. That cadence won’t work today. We review which segments are growing, converting, expanding, and churning weekly. Most quarters there’s a small adjustment. Some quarters there’s a real one, and catching it early changes what marketing, product, and sales should be doing right now.

Naming the ICP is one thing, the actual job is making the rest of the company move with it. PMM is constantly refreshing core messaging, channel mixes, targeting and talk tracks.

We package ICP insights into clear updates and make the rounds on Slack channels, all-hands, team meetings, 1:1s with leads, etc.

3 - Constantly interview customers (not just to start, or when you’re forced to)

Most product marketing teams either rely on other teams to gather direct customer feedback… or they just don’t get it at all. But if you’re going to build fast and launch fast, you need to be talking to your customers a LOT. Do not let sales or CS block you (this was the bane of my life for years).

When I joined, me and our Growth PMM immediately linked arms and packed our calendars with back-to-back interviews. We went to every team and asked them a million questions about our users.

On each customer call, we asked the same five questions every time:

1. “What were you trying to do when you found us?”

2. “What did you try before Lovable?”

3. “Walk me through the moment you decided to sign up.”

4. “What almost stopped you from using it?”

5. “How do you describe Lovable to other people?”

We recorded everything (with permission) and looked at trends and patterns.

This kind of information is the lifeblood for any product-based business. Having real-time feedback on what’s working and what’s not helps everyone go faster. So, what were the pain points that users mentioned?

• “Hiring developers is expensive and slow”

• “I tried no-code tools but hit limits immediately”

• “I’m not technical but I have ideas”

And it wasn’t just the themes. A big part was making note of the exact language they used:

• “It gives me superpowers” (not “it writes my code”)

• “I had a working prototype by lunch” (outcome-focused, time-specific)

• “Finally something that just works” (cognitive ease)

And the moments they got excited about:

• Watching their ideas come to life before their eyes for the first time

• When they shared what they built and someone said “You built this?!”

• When they realized they didn’t need to hire anyone

• When something they thought would take weeks took 20 minutes

And the questions that kept coming up:

• “Is this actually production-ready?”

• “How do I work with my brand?”

• “Can I export the code?”

Back in the day, these insights would probably just sit in a doc. Now, they’re powering tools that every team at Lovable can use, including:

• An interactive messaging house (built in Lovable, naturally). We took the core messaging and turned it into a living document inside a Lovable app. Not a deck. Not a Notion page that goes stale in a week. An interactive messaging house anyone in the company can navigate, search, and pull from by audience, by archetype, or by use case.

• An AI research assistant. Remember the agent I mentioned earlier? Our data scientists built it so anyone at Lovable can just ask things like “How do solo-founders describe the product?” or “What’s the #1 frustration for small teams shipping to production?” and get insights from every interview, survey, and call we have on file.

This means every team can get more accurate, higher-quality context when trying to communicate with current or potential customers. For me, when I was writing landing page copy a few days later, I literally pulled exact phrases:

• Landing page headline: “Ship your ideas in days, not months” (exact phrase from user interview)

• Social proof: “I’m not technical but I have ideas—Lovable is perfect for people like me” (real quote)

• Campaign copy: Added “Your co-founder doesn’t just build, it runs the business with you” (based on how people were describing the product)

4 - Create a simplified messaging framework (vs. making everyone invent messaging from scratch OR read an exhaustive 25-page treatise)

Does your company have a central source for messaging? When I joined, I asked about this… and it turns out one existed from a few months prior but no one remembered what it said.

You’ve probably seen it before: The PMM team beats everyone over the head with messaging documents that are constantly updated and also dozens of pages long, full of details that seem oddly specific and still somehow hard to understand.

But it never hurts to start over, especially if you’re new. I asked everyone on the team: “Show me how you describe what we do.” And that led me to:

• Pitch decks (multiple versions)

• A bunch of different Google docs

• Landing page copy (homepage, pricing, feature pages)

• Email templates

• Links to tons of social content and videos

• Customer-facing help docs

• Interview recordings

• A bunch of deep Slack threads

And we started looking at the patterns:

• People didn’t see Lovable as a coding tool - it was becoming a “full co-founder”

• Everyone mentioned speed (“fast,” “10x,” “minutes not months”)

• Split on whether to lead with AI or outcomes

• Technical teams said “full-stack apps,” non-technical teams said “just describe what you want”

Which also forced us to consider some unresolved conflicts:

• How technical are our audience really?

• What do they really want?

• Is the magic the AI or the speed?

• Are we selling software or selling outcomes?

After some hard conversations, I was able to build a single messaging hierarchy with our core positioning, messaging variants for technical and non-technical users, use cases, and proof points. And again, the thing that helps everyone go fast with this kind of thing is… actually getting access to it. So I presented it to key stakeholders, got feedback, adjusted, and circulated.

Within two weeks, people stopped asking “How should we describe what we do?” The marketing team updated copy across all of our channels. The product team echoes the same messaging in roadmap planning sessions. The founders reference it in company updates. Everyone’s able to move quickly, because they’re not having to build messaging from scratch every time.

BONUS: PUT IT WHERE THEY CAN ASK IT

One of the biggest time sucks for any organization is trying to find the right information. It’s all probably out there… it’s just scattered across Slack threads and Google Docs no one can find, or the PPT decks with “FINAL - Final Actual v2.8” in their titles. If you don’t know whether something is current or accurate, you can’t trust it. And none of the work PMM does matters if it’s buried.

The old version of fixing this was “put it where people can find it”. By that I mean creating and distributing single source of truth documents with links to relevant resources so the same question doesn’t get asked twenty times. That’s still table stakes, and it’s still one of the highest-leverage things a lot of PMMs aren’t doing.

But the bar is moving fast. The next version is “Put it where they can ask it.” Instead of hunting for the right doc, anyone in the org should be able to ask a question to an agent or LLM chatbot, in natural language: “What’s the messaging for the payments launch?” “Who’s our ICP for enterprise pilots?” “What are the top 10 most used features right now?” The goal is to be able to ask these questions and get an answer on demand, wherever they work.

We’re already running a network of specialized agents on Lovable, which are basically small company brains built to help people with specific areas of their work when they need it. Next up: a launch agent connected to our calendar, messaging briefs, and asset libraries, so anyone can ask about upcoming launches, find the information they need, and talk about it.

Conclusion: Product Marketing at ludicrous speed

So, who has time for product marketing? Turns out everyone does when product marketing starts thinking more like an infrastructure, not as a gatekeeper.

Providing a clear ICP grounded in real data, easy access to that live data, self-serve launches, and information that is findable, askable, and usable by anyone in the org. Done right, PMM stops being the team you wait on and starts being the team that makes everyone else faster.

If you’re a PMM reading this, throw out the parts of the playbook that were really about controlling work rather than enabling it. Build the foundations, then get out of the way.

If you’re a Growth or Product person reading this, your closest collaborator just became one of the highest-leverage people in your org, so don’t outsource product marketing thinking, borrow it. Sit in on customer calls, pull from the messaging doc, ask the research bot. The more you can do your own product marketing, the faster you (and your company) move.

PMM isn’t the bottleneck anymore. In an AI-native company, it’s one of the engines. so go find yours, or build the one your team’s been waiting for.

Want more from Gemma? Check out her awesome new substack:

Edited by Jonathan Yagel.

It’s the thing that makes the whole company go around - marketing and sales build their entire personality around it, founders try to change it every week, and engineers nod while secretly thinking ‘this feels made up.’

Define your customer → build for them → grow. Easy. In theory.

But there’s an assumption baked into all of this: Your user is human. I think that assumption is breaking.

As agents begin to interact with products on our behalf - often via protocols like Model Context Protocol (MCP) - your ‘user’ may never actually touch your product.

Which changes pretty much everything.

In the past, even API-first products had a clear answer. Your ICP was still a human, usually a developer. Someone chose your product, integrated it, and used it. But now, LLMs will definitely be involved in every step of that process, and may even replace it. This is the question I think every company should be asking:

What happens when your main ICP is an MCP?

Elena’s Picks

Hey, I’m trying out a new format! I’ll be specifically featuring products and services I personally recommend to this community. Plus, sometimes a few that I’m exploring.

→ Stripe: The GOAT for payment processing. They also crush it with billing, invoicing, and pretty much the whole monetization stack. They’re an essential part of our growth work at Lovable, and I use them to manage payments for all of my solopreneurship stuff, too. If you’re considering alternatives… don’t. Just use Stripe.
🎁 Offer: Playbook for scaling AI product pricing. How are we supposed to price AI products, exactly? Stripe put together the 5-step framework you need.

→ Lovable: What can I say? Yes, I work here. But… I work here because I was obsessed with the product, first. It’s the best way to build an app or site, even if you have no technical experience. Try it out!
🎁 Offer: Get a year of Lovable for free! (For paid subscribers to Growth Scoop)

→ Factors.ai: Here’s one I’m exploring: The problem they’re going after? Running ABM campaigns manually and across a bunch of different platforms. Factors.ai has an agent that pulls together visitor identification, intent data, ABM activation, and multi-touch attribution. How much better could all this be if it’s all in one platform?
🎁 Offer: LinkedIn Benchmarks report. The Factors.ai team analyzed 100+ b2b companies and they’re giving away the insights for free.

Good products have always been about understanding the quirks of how humans actually operate and interact with things.

We built onboarding flows to reduce friction, polished UI to feel intuitive, added empty states and tooltips and delightful microcopy so users feel guided and successful. Entire growth teams exist to improve the conversion between steps in a flow that assumes a human is clicking through it.

But what happens when none of that is seen?

Agents don’t care about onboarding. They don’t care about your navigation. They don’t care about user psychology. They don’t care that you spent six weeks debating whether the CTA should say ‘Get Started’ or ‘Try Now.’

They care about whether your product returns the right output, quickly, reliably, and in a format they can use.

If it does, you stay in consideration. If it doesn’t, you will get replaced. Not churned. Replaced.

You have to open up

If agents are going to sit between users and software, then your product needs to be accessible to them. Which is where the MCPs come in.

If your product isn’t exposed through MCP (or something equivalent), agents can’t use it. And if agents can’t use it, you’re not part of the workflow anymore.

This means that every B2B company will be pressured to open up. And might be forced to, even if they don’t want to. Which means some uncomfortable tradeoffs.

Opening up your product means sharing functionality, data, and workflows in a structured, machine-consumable way. You are effectively saying: ‘Here is what we do. Here is how to use it. Go ahead.’

Which is great for accessibility. And terrible for any moat that depended on friction, UI complexity, or user habituation.

A lot of companies are going to discover that what they thought was defensibility… wasn’t

If your product required training, onboarding, or repeated human interaction to be valuable, that created a kind of stickiness. Some companies have gotten confused and thought the stickiness was based on their product being superior. But it wasn’t. It was just too painful to switch.

Agents remove that pain.

They don’t need to ‘learn’ your product. They don’t care how it feels. They just evaluate whether your output is better than the alternative.

Which leads to a pretty brutal question: If an agent can reproduce your core functionality without ever touching your product, what exactly are you defending?

In that world, your UI is not a moat. Your ease of use is not a moat. Your brand is not a moat. Even your workflow might not be a moat.

Your moat becomes whatever cannot be easily replicated at the output layer.

For some companies, that’s proprietary data. For others, it’s unique aggregation, network effects, or deep integration into systems of record.

For many, it’s… unclear.

This affects distribution, too

This shift in ICP affects your core product flows, but please also consider what Growth looks like when agents are a core part of the buying process, too. A lot of what we call ‘Growth’ today is really distribution and conversion optimization for human users. Ads, traffic, funnels, activation rates, onboarding completion.

With this in mind, you start designing differently. With agents and MCPs as part of the mix, distribution is almost reversed - you’re not taking it out to them, you’re making it easier for them to come get it from you. Are you part of the set of tools an agent can call? Are your endpoints discoverable, documented, and trusted?

You stop asking: ‘How do we get users into our product?’

And start asking: ‘How does our product fit into their workflow?’

You start prioritizing:

• clean, well-documented interfaces

• predictable, structured outputs

• reliability

Do you even need a traditional landing page anymore? Clean, thorough documentation may do the trick.

Does ranking on Search matter? Now we’re not just talking about ‘People ask ChatGPT instead of Google’ - we’re talking about people not asking at all, because an agent is going out to find the answers for them. And that agent is wayyy more thorough. They’re not going to stop at the first few options. There’s no ‘below the fold’ for them. They’re on a relentless mission to evaluate every option and then choose based purely on performance.

And as agents are able to not only evaluate but actually purchase software, things get even crazier. Since Stripe launched Machine Payments Protocol (MPP) a couple weeks ago, all of a sudden, the possibility of agents handling the entire purchase flow seems more real than ever.

Once you start thinking through this, you’ll realize that some of the things you used to invest in may not matter as much in this new layer.

This doesn’t mean human experience goes away

So, invisible, mechanical replacements for every product?? Nah. But I do think this will split the market.

A good analogy is what happened with ghost kitchens during Covid. Restaurants that went all-in on delivery optimized everything for that model. Speed, packaging, menu design, pricing. They didn’t need ambiance or location or even a particularly strong brand outside of the delivery apps. They survived and thrived during that time while restaurants focused on the in-person dining experience got destroyed.

I think we will see something very similar with software.

Some products will double down on being genuinely enjoyable to use. These are your “minimum lovable product” companies. They win because people choose them, advocate for them, and build affinity with them.

Others will become almost entirely invisible. They exist as infrastructure. As a codified set of rules that is hard to reproduce. They are never opened directly, never explored, never ‘used’ in the traditional sense. They are just… there, powering outcomes. And you know what, I think most of the B2B will fall here. Gasp.

Why?

Because most people don’t actually enjoy using business software. Most of B2B product experiences… suck. They use it because they have to. If an agent can take over those interactions and deliver the same or better outcomes, most users will happily step out of the loop.

B2C will likely lag, because there are parts of consumer behavior that are tied to taste, identity, and exploration. But even there, pieces of the experience will get abstracted over time.

What now?

Every company has some decisions to make. In order to evaluate your product and the value you can provide, agents and MCPs need to have the full picture - your structure, systems, processes. Most companies don’t want to share these elements… but if you don’t, you may be replaced by an alternative that does. And even more than that: If all of that process doesn’t actually lead to a better output, we’re not just talking about a threat to your efficient distribution. We’re talking about a threat to your company’s existence.

So start thinking about this. The shift hasn’t fully played out yet, but the direction is pretty clear. If people don’t want to use your software or product, they’re going to ask their agents to do it for them. And if another upstart company can provide the same value to those non-human ‘users’ at a fraction of the cost? The LLMs may not be great at math, but that’s an equation I’m pretty sure they can solve.

So yes, you probably still need a clear human ICP. But if you’re not also thinking about how an agent evaluates, selects, and uses your product… you’re optimizing for a user that may not be in the loop much longer.

Edited by Jonathan Yagel.

We went from on-prem to cloud. Then came digital transformation, where every company suddenly needed to become a software company (whether they had any business doing so or not). Entire stacks got rebuilt - .NET stopped feeling inevitable, Python spread everywhere, and everyone got weirdly excited about Next.js. Mobile came in hot (B2B, naturally, is still deciding whether a phone is a real device). Recurring revenue became our SaaS religion. Remote work exploded, then partially un-exploded. Product-led growth rewired how companies scaled.

Each wave felt big. AI feels 10x bigger. And 10x faster.

That speed is the part I can’t quite process. There are days where it genuinely feels like I need a full-time job just to keep up with what’s happening. And even then, I’m not convinced I am. Am I just getting better at being slightly less behind?? Haha.

And that’s really the feeling underneath all of this: behind.

Not ‘I should probably test that new tool’ behind. More like ‘am I already operating on an outdated mental model?’ behind.

There’s also a weird social dynamic to this whole thing. Everyone has a system, a stack, a workflow that supposedly changed their life, saved them from the burnout, and probably whitened their teeth. It creates this illusion that everyone else already knows what’s going on.

So you hesitate to ask basic questions, because it feels like you’re the only dumb one who doesn’t get it.

Which is almost certainly not true. But it feels true. And the result is a lot of fake confidence theater, a lot of noise, and very little shared truth about what’s actually working.

Then there’s the part that’s harder to admit: a lot of what I spent the last decade learning is losing leverage.

Growth, marketing, product management, sales - these used to feel like crafts. You built intuition over years. You learned what great looked like. You got good at pattern recognition. You earned judgment and respect by grinding through it all.

AI is flattening a lot of that.

It’s a weird experience to spend ten years becoming excellent at something only to watch a 22-year-old produce a suspiciously solid version of it in 14 minutes. Not the best version. But enough to make you sit there like, wow, okay then. And you don’t really get to process that shift. There’s no mourning period. You just move on to the next thing, because everything is changing too fast. (and don’t even get me started on how non-tech people are supposed to keep up with any of this - ‘mass adoption’ feels almost comical.)

Which forces a much more uncomfortable question: if your identity was tied to being good at X, what happens when X gets automated?

Now, senior people still have some advantages, but some of the old signals of seniority are getting weaker fast. The hierarchy flattens. The ladder gets weird. Experience still matters, but not in the clean, linear way we got used to.

Honestly, I think that a lot of that is good. A lot of old hierarchies deserved to die. RIP politics and middle-management. Still, it’s disorienting as we are going through it.

And of course, the reward for becoming more efficient is exactly what it has always been: more work. If AI makes you 10x faster, nobody says, ‘Amazing. Please enjoy your afternoon!’ They ask why you’re not doing 10x more. Productivity gains get absorbed immediately by the system, which is very on-brand for tech.

And underneath all of this is the part we really don’t want to talk about: the economics.

If output goes up while the cost of producing that output goes down, what happens to compensation? What happens to leverage? What happens to the premium attached to knowledge work when more of that work becomes abundant? What happens to company structures when fewer people can produce dramatically more?

My guess is the value shifts.

Away from execution. Away from being the person who can grind through the work manually. Toward taste, judgment, prioritization, and orchestration. Toward deciding what’s worth building, not just how to build it.

Which sounds elegant until you realize those are harder skills to build patterns on and really really hard to teach/learn.

The last question I keep coming back to is whether we are the last generation that built our careers around software as a medium.

We leaned all the way in. We learned the tools, the systems, the playbooks. We rode cloud. We drove digital transformation. We built careers on knowing how to operate software better than other people. We are also, unfortunately, the sandwich generation that has to explain software to our parents and now AI to our kids.

But if software starts getting built, configured, and operated by AI, what happens to the people whose edge was being good at creating software?

I don’t know. And I’m not convinced anyone else does either, despite the amount of confidence cosplay happening online.

And maybe I’m overblowing it. Or maybe this is just what it feels like to live through a real industry shift while still being expected to perform like nothing has changed.

The only thing I feel confident about is that the advantage is shifting.

It’s shifting toward the people who can see clearly, choose well, and adapt faster than the ground is moving beneath them.

No pressure everyone. Everything will be okay. (RIGHT?)

Usage.
Conversion.
Retention.
Revenue.

A much less comfortable question: do users actually give a shit?

Because a lot of “healthy” products are really just products people tolerate:
their boss told them to use it, they have not found a better alternative yet, or switching feels too annoying.

None of that means they love it.

And the second a real alternative shows up, they’re gone. There goes your retention.

If you want durable growth, the distinction between “I have to use it” and “I love using it” matters a lot.

Read more

Here are a few that we’ve recently tested… which all yielded a meaningful lift!

Plus, 2 laws of retention improvement that everyone keeps forgetting.

Read more

The kind where you squeeze customers a little harder every quarter, slowly wreck trust, burn the brand, and then six months later everyone’s in a meeting asking, “Why is retention and growth suddenly bad?”

And here’s the hard truth: in this age of technological trAInsformation, that kind of revenue chasing is straight up fatal.

I’ll go even further: If revenue is your North Star, your company is destined to die.

Read more

And sure, we can debate what ‘viable’ is supposed to mean, but let’s be real - MVP devolved into “minimal functioning product” because ‘viable’ got watered down to ‘it performs bare minimum.’

And that’s because dev work was expensive. Like very expensive. But we live in the new reality now where dev costs are collapsing. Everyone’s a builder now. Software functionality is becoming a… commodity. So an MVP just means you built another tool people tolerate until they re-create it themselves or a better one comes along.

An MLP is different: earliest version that’s genuinely lovable. The kind of product where people feel it. It’s fast, obvious, opinionated, and gives you that ‘wait, this is actually… nice’ moment.

But most people still don’t get why this matters so much right now.

When I bring up MLP, I always get pushback. ‘You’re describi…

Read more

I agree with the core premise of his article. Disruption is coming, and it’s going to be massive. But I think most people are framing the conversation the wrong way. Everyone is stuck debating whether AI will take their job. The answer is almost certainly yes (I know, I know - it’s terrifying). That part isn’t interesting anymore.

The more important question is this: What if this is also the biggest opportunity of your career?

Right now, there’s a short window where individuals can get absurdly far ahead by becoming AI-native. Not “AI-aware.” Not “occasionally uses Claude.” AI-native. And that window is measured in months, not years.

Who should actually be scared?

It’s a terrible time to be a company or an exec. But it’s a great time to be an individual contributor.

If you’re a founder/ceo or exec running a bloated, slow-moving org that spent decades layering process, coordination, and middle management to handle complexity AI is about to flatten, you should be sweating. Companies that need 26 meetings, four approval chains, and a Gantt chart from 2019 to ship a button color change aren’t careful. They’re exposed.

At this point, many companies are only alive because of distribution, network effect, or data lock-in. The product itself is no longer the moat.

But if you’re an individual stuck in a role you don’t love, underpaid, boxed in, spending your days in meetings that accomplish nothing, writing docs nobody reads, and waiting for your ideas to get prioritized on someone else’s roadmap, the bad news for them might actually be the best news for you.

The demand for AI-native employees is exploding. Not in some abstract, future way. Right now. Companies are starting to care less about fancy titles, perfectly laddered careers, and padded resumes, and more about who can actually get things done in this new environment. People with good taste, real business sense, and, most importantly, high drive. In the next year or two, I’m convinced being AI-native plus those qualities will matter more than years of experience, brand-name logos, or titles that only made sense in a slower world.

Let me make this concrete

At Lovable, we have a Slack channel called #feedback where anyone can post things that feel broken or annoying in the product. Normally, devs would jump in and fix them.

But lately, I started noticing something different.

Instead of devs writing the fixes, I kept seeing messages like, “Hey Cursor, fix this” or “Claude Code, can you handle this?” And then… the fix would just happen. A PR would appear. A quick human review later, it was live.

So next time I was ready to post in the channel (CTA button had the wrong color), I had a wild thought: could I fix this myself?

I don’t have an engineering background. I didn’t even have a GitHub account. But I remembered a teammate (Benjamin) I’d seen do this, so I asked him to show me how it worked. He helped me set up GitHub, Claude Code, and Cursor.

I took a screenshot of the button, told Cursor what was wrong, and asked it to fix it.

It immediately found the issue, fixed it, and opened a PR. The engineer reviewed it and merged it.

I had just “written” code to production. In minutes. Something that would normally take tickets, meetings, and weeks of waiting… I just did it. Not because I became an engineer, but because the gap between intent and execution collapsed.

Honestly, it felt like the biggest unlock for me since discovering Lovable. Equal parts excitement, an undeserved sense of superiority, and just enough danger to be intoxicating.

For individuals, this is leverage. And it’s happening right now.

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Get your head out of the sand

A lot of people’s response to AI right now is critique. Pointing out where it fails. Where it’s wrong. Why it’s overhyped. Screening for em-dashes. Every new model drop turns into a race to prove what it can’t do.

I get it. If something threatens your role, tearing it down feels like self-defense.

But that fear only makes sense if the current setup is worth protecting. And watching this play out, it feels like people are desperately defending a system that was already failing them. Meetings instead of making. Process instead of progress. “Work about work” that creates no value.

AI is not just automating tasks. It’s removing permission. You no longer need to wait for headcount, budget, or alignment to create something real. That’s why companies are nervous. A motivated individual with curiosity and initiative can now do what used to require a team.

This is why there’s a window right now.

Early adopters are compounding advantage. They’re learning faster, shipping faster, and building confidence faster. Once AI-native workflows become the default, that edge disappears. Right now, curiosity beats credentials. But that won’t last when AI skill becomes commoditized.

I’ve spent years writing about this stuff. About how full-time employment stability is a myth - were you 100% safe from layoffs, even before AI? About how tying your identity to your job title is a trap. How the leadership ladder has a dark side that pulls people away from work they actually love and into meetings, politics, and people management they hate. How I quit full-time roles to build career optionality - how owning your skills, your reputation, and your ability to create value independently is the real security. And how I literally want to eliminate my own job, because so much of Growth has been stagnating and I think AI could free us up to do better, more creative work.

Things you should do this week

First, lock in and try to vibe-code a rough version of your own company’s product. Block a few hours (using Lovable, obvi, LOL). No perfection. Just see how far you get.

Don’t start with edge cases or scale. Start with the core thing your product actually does. Most companies have two or three workflows that matter and a long tail of noise wrapped around them. Focus on those. See if your users can create their own personal tools solving for that workflow.

If AI gets you uncomfortably far in a single day, that’s a signal for you of what’s to come.

Second, make AI your default for everything. AI should be your starting point for everything: writing, thinking, designing, coding, planning.

The culture around this is backwards. We spend so much time shaming people for not deleting them em dashes... Oh how wrong we are here. The real question now is why someone didn’t use AI in the first place.

Manually doing work that AI can do better, faster, and cheaper isn’t craftsmanship. It’s wasted time. And in a world where leverage compounds weekly, wasting time is the most expensive mistake you can make.

Third, if AI couldn’t do something yesterday, try it again next week. AI improves in weeks, not years. Once AI began writing its own code to improve itself, the pace of capability growth went exponential. “We tried that and it didn’t work” is the fastest way to fall behind.

Fourth, start a side project. Not because you’re quitting tomorrow, but because building is the fastest way to internalize what’s changing. The tools are cheap or free. The barrier to entry is gone. Maybe you can even make money from it.

Fifth, ask the AI-native person around you for help. They’re waiting to show you. This stuff is contagious once you see it. Don’t do this:

Stop reading. Start shipping.

No one wants to lose their job. That fear is real. People depend on your income. I’m not dismissing that. But ask yourself honestly: do you love your job so much that you want it frozen exactly as it is? Do you want your kids to have it?

You need a job. But do you need this one, in this form, forever?

What if this moment isn’t about falling behind, but about finally getting unstuck?

The biggest risk right now isn’t AI taking your job. It’s watching other people pull ahead while you wait to feel ready.

So stop scrolling. Open Claude, ChatGPT, Cursor, or Lovable. Try something. It doesn’t have to be perfect. It doesn’t have to be big.

Just start.

Edited by Jonathan Yagel.

And so the “subscription economy” has exploded in the last decade - and it’s the backbone of the SaaS. And let’s be real, much of the Growth and Marketing discipline has been built around learning how to create and optimize a model around Annual Recurring Revenue (ARR)... aka, those sweet, sweet subscriptions.

But (and I know some of you don’t want to hear it)... not every business should monetize through subscriptions. In fact, most of the time it doesn’t even make sense. And your customers may hate you for it.

That’s something a lot of AI companies are realizing right now. We did at Lovable.

Read more

Read more

Read more

But what happens when ICs become far more autonomous, leaner teams mean coordination and supervision matter less, and every company is shipping faster than ever? When the cost of a wrong decision drops and people on the team just… go. Because that is the vision behind AI-native employees and something that AI-native companies are striving and organizing for.

The role of leaders changes. We still need decision makers. We still need context setters. But what we won’t need is pure leadership or management as a full-time job.

That role is dying. I stand behind that prediction.

The future looks more like this: senior leaders and execs who stay…

Read more

How are you supposed to grow in this new landscape? It ain’t easy. But there’s a new playbook that I’m seeing emerge, and it’s all built around one simple concept: Trust.

Here’s how it changes how you should be thinking about your growth model.

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Trust-based Acquisition

The classic distribution systems are falling apart. You may have been hearing this for a while - Andrew Chen pointed out that every marketing channel sucks right now, almost a year ago. But it’s getting worse. You’re probably starting to see all of your channels get to be more expensive or less efficient, or both. Unfortunately, I don’t see them getting better any time soon.

What’s Not Working Anymore

SEO and organic search. The obvious thing is that AI slop has reduced the barrier-to-entry for creating the content that SEO depends on. Now anyone can churn out dozens of articles with just a few prompts. But it’s deeper than that: SEO is all based on the assumption that people will primarily find information and access the Internet’s vast knowledge through Google searches that send them to web pages. That’s just not true anymore. People are going to ChatGPT, Claude, and Perplexity to get answers. And even when they do Google, the AI-generated answers intercept traffic before people ever click a link. And soon? People will use LLMs to navigate to products they already talked to AI about, the same way they use Google as a navigation bar now.

Want examples? Check out this post: AI is killing some companies, yet others are thriving - let’s look at the data

Paid search (SEM). This is the same thing as SEO, but the economics are more obvious: With the total number of searches not growing, the cost of placing your ads on those searches skyrockets as competition increases. Everyone’s bidding on the same keywords, and it’s getting harder and harder to maintain a positive ROAS. Plus, you’re not just competing with other companies but with AI tools that solve the same problem for $20/month. Good luck with that.

Corporate social. Social platforms are increasingly hostile toward corporate accounts and external links, optimizing for on-platform engagement. You might be able to get attention, but try to convert that into external traffic? No more juice for you. The algo giveth, the algo taketh away. Plus, the creative treadmill required to maintain polished ‘brand-aligned’ assets is expensive and exhausting. All for posts that still feel like interruption marketing. Which they are.

What’s Working Now

Employee-led social. When founders and employees share their thinking, their failures, their roadmap publicly, it demonstrates transparency and accountability. This isn’t about posting motivational LinkedIn content (please, make the carousel posts stop). It’s about sharing real expertise, examples, and demonstrating the humanity of your company. People buy from people they trust. Faces create that trust in ways corporate accounts never can.

Influencer and creator partnerships. When someone with an existing audience bets their reputation on recommending your product, it transfers trust. The key is finding partners whose audience genuinely matches your ICP and who will actually use and believe in what you’ve built. Not the ones who’ll promote anything for a check.

Community-driven growth. Your users become your distribution channel, but only if you build the infrastructure for it. Your product has to create stories worth sharing. But also give them a place to show their work, staff it so questions actually get answered, and let users teach each other - the best content explaining your product never comes from marketing. And when it works, community creates trust that marketing budgets can’t buy: users believe in your product because other people they respect believe in it. Features are easy to copy. Trust isn’t.

Want to boost your community with user referrals? Be sure to check out this post’s sponsor, Cello.

Product-led brand. Brand used to come from marketing campaigns and logo recognition. Now it comes from product experience. Brand is a product job, now. Every interaction, every feature, every detail either builds or reduces trust. The product itself has to demonstrate that you care about the user’s problem and will keep solving it better than anyone else.

You may have noticed that a lot of these channels feed into the same thing… building word of mouth. This isn’t a channel you can control really, but it’s the ultimate trust signal. If someone hears about your product from someone they know, that’s priceless. But it’s also super difficult to manufacture. It has to be woven into everything you are doing, how you are building, in your cultural values. And it’s not something you can do with a clever viral marketing campaign - that might get people to talk about your ads or your content, but if you want people discussing your product, you need to WOW them. And that comes from product, which is also your retention engine.

Trust-based Retention

Just like it’s killing traditional distribution channels on the one hand, the arrival of AI is ruining retention for traditional SaaS businesses. This is a little bit different from AI-native companies who are stuck on the PMF treadmill, but it’s the same idea - it’s all about your value prop.

At the end of the day, every company has to answer this critical question: ‘Why you? Why should users use (or keep using) your product? The answer always comes down to one of three options: You are…

1. Cheaper

2. More efficient (faster at solving the problem than alternatives)

3. More effective (able to produce a better outcome)

The problem for SaaS companies is that most of them were built around #1 or #2. In fact, out of all the growth workshops I’ve done with software companies, 9 out of 10 times, they say that ‘why’ is: ‘time to value vs. the manual approach.’

And now, that’s a major problem: AI is faster than any traditional tech hard-coded software product. It’s more efficient than your workflow tool. It answers questions better than your knowledge base. It generates content faster than your marketing platform. If your primary value proposition is efficiency or cost savings, you’re competing with something that will beat you on both dimensions AND costs your customers $20 per month.

Plus, even if your value prop does fall into the ‘More effective’ category, you’re at risk if that functionality is not utilized enough:

Add in the fact that AI can also be more effective because it’s better at understanding final intent…. and this means all of the traditional value props are weakened. So, utility-based value places you on shaky ground. When all the capabilities get commoditized, users will stick with the products they trust.

More specifically, this kind of trust is confidence that this product and team will continue to deliver better outcomes over time. This depends on their belief that you genuinely care about their problem and will keep iterating to solve it better than anyone else.

Now, how do you build this kind of trust?

• Transparent roadmap sharing. Not the sanitized public roadmap that commits to nothing. I mean real visibility into what you’re building and why. When customers see you’re thinking three steps ahead on their actual problems, it builds confidence that you’ll continue to be valuable even as AI capabilities expand. (And they will expand. Fast.)

• Responsive iteration based on feedback. Speed matters, but it has to be in the right direction. Are you really listening to what customers need and building it? Or are you on a pre-made product roadmap that ignores their reality? The companies that tighten this feedback loop and ship legit improvements quickly are the ones that earn ongoing trust.

• Amazing user experience / ‘WOW’ moments. I’m not talking about looking pretty. I mean showing through the product experience that you care about how people actually work. The delightful details, the thoughtful interactions, the features that anticipate needs - these ‘love marks’ in the product create an emotional connection that goes beyond the product’s utility.

• Thoughtful lifecycle comms. Every email, update, and push notification is either building trust or reducing it. Are you creating value with your updates, or just bombarding people?

• Monetization aligned with outcomes. Getting paid only when your customer succeeds is more than a pricing strategy. It’s a retention moat. It creates real trust, reduces churn, and removes the pressure on customers to justify their spend. It also avoids “sleeping bears” - customers who pay but don’t use the product, and wake up just in time to churn.

This is why brand is a product job now, not just a marketing job. The product itself must demonstrate trustworthiness. You can’t market your way into trust-based retention. Marketing can tell the story, but the product has to be the story. If those things don’t align, customers see right through it.

Trust is the Main Lever Behind Growth

Acquire through trust. Retain through trust. These aren’t separate strategies - they’re the same system playing out at different moments in the user journey.

Honestly, there aren’t that many products I actually trust. For me its Lovable, Miro, Whisperflow, Spotify, Granola, Oura, Stripe, Tesla, Netflix, Arc, Superhuman, Substack, ChatGPT among a few others. They’ve never let me down. I found each one through referrals. They continuously evolve and solve my problems. I enjoy using them. I’m rooting for them to succeed. Which ones do you trust? And why?

And what does this mean operationally?

Build this into your org structure & values. Product, marketing, and customer success can’t operate in silos. Trust-building requires everyone running in the same direction. Your founders and executives need to be visible in public channels and keep it real. Your product team needs to be talking directly to customers and shipping based on what they’re hearing. Fast. Your customer success team needs the access to influence product direction. If you still have org charts where these teams only talk in quarterly planning meetings, you’re already behind.

Optimize for velocity. Trust-based growth requires speed - both in how fast you ship and how fast you respond. Tighten the feedback loop between customer input and shipped features. Minimize cross-functional dependencies so teams can move without waiting for approval chains. Ship daily if you can. Micro-releases trigger something traditional marketing can’t: they make the product feel alive. Users signed up for version X… but they keep getting version X+!? This makes them feel like they got a free upgrade, and it builds trust and loyalty without you having to ask for it.

Learn to build in public. You’ve got to share your work as you go - a steady rhythm of progress, ideas, wins (and fails!), over time. The product becomes the story. The shipping cadence becomes the engagement strategy. And remember: this can’t be run by your corporate account. People don’t want the company POV. They want to hear from builders - your CEO, your engineers, your designers, the people who actually made the thing. That’s what makes it feel real instead of manufactured. It’s scary because you’re giving up control and polish. But when you’re moving fast, you don’t have time for Apple-style keynote presentations anyway. And honestly? Less polished is more effective. A super glossy ad is cool, but it elevates the brand… away from the people watching it. You want connection, not hype.

The companies that figure out trust-based growth will have a significant and lasting advantage. Trust is harder to build than features. It’s harder to replicate than efficiency. It compounds over time in ways that performance marketing never could.

AI will keep commoditizing product capabilities, which is why trust is becoming the moat that actually matters. The question isn’t whether to adopt this approach. The question is how quickly you can make the shift before your traditional channels and value propositions collapse completely.

And trust me: they’re collapsing faster than you think.

Edited by Jonathan Yagel.

Everyone keeps asking for the secret sauce behind the growth. Sorry to disappoint - there’s no magic new channel. We just do a few things differently, and we’re relentless about them.

I was back on Lenny’s Podcast for the fourth time (but who’s counting?), and we talked about what growth at Lovable actually looks like in practice. Here are a few of the major growth topics that I wanted to unpack a bit.

1. Optimize for empathy & emotion

2. Build in public

3. Shipping velocity is everything

4. Invest in your community

5. Social>search

6. Give a lot of shit away

Like I told Lenny: Not every company can or should be like Lovable! A very unique set of circumstances came together to make this outlier growth trajectory possible: be at the right place, at the right time, with a right group of people, and in the fast moving waters of a category that is rapidly expanding. But still, Lovable has 100’s of competitors and we are doing quite well - so here are some of the key growth lessons that worked for us.

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1 - Optimize for empathy & emotion

When the cost of building comes down, building for utility is no longer enough. The value of creating empathy and emotion goes up.

Product and Growth teams used to be able to focus on the pure product utility and what the features did. With the rise of AI-enabled building, those features are becoming commoditized - anyone can rebuild your app’s capabilities. But the experience of the product and how it connects with people is what lasts.

This can’t just be an afterthought, and it’s one of Lovable’s unfair advantages: it’s literally right there in the name! Everything we build has to be ‘lovable.’ Those moments of delight are what keep bringing people back.

Read more: Brand… a Product job now?

2 - Shipping velocity is everything

Shipping velocity is everything, because products & markets are evolving so fast.

‘Velocity of Shipping’ is our #1 dev team value. And for a product like Lovable, it has to be, because Product-Market Fit is now a constantly moving target. This is because both the underlying technology (which shapes the product) and the customer expectations (which shape the market) are both changing on a monthly basis. PMF used to be something you could achieve and then gradually scale… now, features can become outdated almost as soon as they’ve shipped.

Read more: The Product-Market Fit Treadmill: Why every AI company is sprinting just to stay in place

3 - Build in public

Building in Public is the natural distribution mechanism for fast-shipping companies.

When you’re shipping this fast, traditional marketing timelines don’t make sense. You can’t finalize the product and then finalize an elaborate campaign to promote it, months later. The overall volume of updates would likely overwhelm marketing teams, anyway.

‘Build In Public’ (BIP) turns this weakness into a strength: Use the momentum of constant shipping to your advantage.

Plus, this approach has another huge advantage - it builds trust. In a super competitive field, loyalty is key. BIP creates a connection between the team behind the product and the users, which builds a sense of buy-in.

Read more: Building In Public is scary. Do it anyway.

4 - Invest in your community

When software starts to feel less like a tool and more like a place.

But community doesn’t just magically appear. You have to design for it.

At Lovable, it’s been non-negotiable because we’re early in a category. People are still figuring out what’s possible, and they need a place to compare notes, brainstorm ideas, and unblock each other.

What actually matters:

• Give users a place to show their work. We run on Discord - nothing fancy. It works because the value is the people, not the platform.

• Staff it. Community doesn’t self-heal. If questions go unanswered, it dies. Stewardship is the job.

• Reward the helpers. Call them out, give early access, share their builds. This is how “ambassadors” happen without over-engineering it.

• Show up as a team. Engineers, PMs, designers. If users feel like they’re yelling into the void, you’ve already lost.

• Let users teach. The best content is never your marketing team. It’s users explaining how they actually use the product.

Community is a force multiplier. It boosts word of mouth, social distribution, retention. It turns solo users into a network.

And in a crowded market, that matters. Features are easy to copy. Community isn’t. When people stick around because they feel invested, the switching costs are emotional, not technical.

5 - Social>search

Distribution shift is happening right in front of us.

Marketing channels are getting reshuffled in real time, and not nearly enough teams are talking and freaking out about it.

Five years ago, “organic strategy” was easy. SEO. Google. Ship content, wait.

That playbook is breaking.

Organic today is social. Full stop.

What is your CEO/leadership posting?
What is your team posting?
What are creators/influencers saying on your behalf?
What are your users sharing without being asked (WOM, baby)?

That’s the channel now. Even in B2B. Especially in B2B.

Here’s the uncomfortable part: most companies aren’t built for this.
They’re optimized for brand accounts, legal approvals, and campaigns.
Not for employees showing up daily, building in public, and shipping opinions. And that’s … a problem. I don’t know how to fix it though.

Eyeballs didn’t disappear. They moved. And if your growth strategy still starts with “let’s rank on Google,” you’re optimizing for where attention used to be, not where it actually lives today.

P.S. Traditional paid performance marketing isn’t a meaningful lever for us at Lovable. Performance works when there’s existing demand. We’re building a new category, so the job isn’t capturing demand - it’s creating it.

6 - Give a lot of shit away

Certain AI products are basically born for aggressive PLG.

If you’re pulling back on freemium because of margins, you’re playing the wrong game. You should be giving your AI away.

Why this works:

• It’s a brand-new category - people don’t get it until they use it

• The first “blow my socks off” moment lives inside the product, not in your ads

• Word of mouth is the growth engine

• Competition is brutal and moving fast

• The old marketing playbook is quietly dying

So yes, LLMs are expensive. And yes, we’re handing out Lovable credits like candy to our free users, hackathons, events, and teams who want to experiment.

That’s not an OpEx problem. That’s a marketing investment.

Classic PLG math still applies: ship real value, drive usage, let the loops compound. In AI, the fastest way to grow is to let people experience the magic before you try to monetize it.

Read more: Why AI doesn’t mean the end of Freemium

Speaking of giving stuff away - all paid Growth Scoop subscribers now get one year of Lovable for free. Enjoy!

It’s all coming together

Here’s the thing: These aren’t six separate tactics you can cherry-pick. They all come together as a flywheel.

Ship fast… which forces you to Build in Public… which pumps up your Community… which improves your ability to build with Empathy… which makes people want to tell others… across social channels… which creates effective opportunities for you to Give Shit Away… which creates more usage and more requests that you need to ship fast.

It all compounds. It’s an entire system that’s built to make the most of this unique moment and this unique company. Right place, right time, right team, right fast-moving waters!

That’s why this approach won’t work for every business. And it requires operators to unlearn their habits and patterns (I had to unlearn… a lot. I find less than 40% of what I know applies nowadays).

A lot has to come together to make this work. But when it does? That’s when you get $200M ARR and a $6.6B valuation in a year. And we’re literally just getting started.

Be sure to check out the full conversation with Lenny, here:

Edited by .

But no, no. freemium isn’t dead. In AI, freemium has actually become the most rational irrational strategy we’ve got.

Read more

It happens because company leaders take marketing inspiration from all the wrong places.

They want to be Hollywood, trying to turn product releases into blockbuster-level brand moments. But they forget how inconsistent and risky this approach is - you only get one shot!

Read more

PMF used to be something companies would hit, maintain, and scale. You’d reach PMF, ride it for a few years, then invest in the next horizon when competitors or markets shifted.

That era is dead.

Read more

Read more

The pace is intense for two reasons: LLM capabilities are evolving faster than we can finish a roadmap cycle, and customer expectations are shifting right along with them. So it feels like we’re on a PMF treadmill. What used to be “horizon 2” innovation that companies had years to get to, we’re hitting every quarter.

There’s no playbook for that. No patterns to copy. And we’re doing it while the ground underneath us is also shifting: we are in the middle of the AI-driven technological platform shift all while distribution shifts are happening as well, and everything I thought I knew is being re-evaluated in real time.

Need to let go

I’ve spent my career in growth roles where 70-80% of what I already knew mapped to the new job. I’d show up, apply my frameworks, tune the funnel, build the loops, scale. All pretty straightforward.

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Lovable has been the opposite. Maybe 30-40% of my experience transfers. The rest I’ve had to unlearn. I’m having to let go of past patterns. Which is super uncomfortable. One of my superpowers is pattern recognition and building scalable frameworks from the trends I see. But the old structures are breaking apart. The market is just moving way too fast to rely on frameworks built for stable environments. So, now I have to treat all my hard-earned knowledge as disposable. Kind of sucks, right?

There’s an entirely new world of growth that’s emerging, and here’s what I’ve been seeing:

1. Growth works on new… ‘features’!?
   In previous roles, 90% of my job was experimentation and optimization. Here, most of the job is inventing entirely new loops, launching new initiatives, and creating new product surfaces (even, gasp, new features). We’re still defining how people use AI, not just scaling an existing behavior. The work feels closer to product innovation than funnel tuning.

2. Traditional marketing isn’t the lever
   Paid marketing, SEO, campaigns, nurture programs. They’re fine. They help. But they are not what moves an AI company right now. The real distribution is word of mouth, creator economy, and community. This all looks more like consumer growth patterns than traditional B2B. If your product isn’t getting talked about, there is no amount of optimization that can backfill that gap.

3. Growth surfaces are collapsing
   Most products are converging into a text box with an agent behind it. There are fewer knobs to turn on the surface. Growth work now sits deep in the agent quality, the model selection, the reasoning behavior, the personality. If the agent isn’t good, no onboarding flow will save you. So growth is embedded inside core product, not layered on top.

4. Need to be on the constant lookout for new growth channels.

   We are in the middle of the distribution shift and more than ever need to be constantly watching for new distribution windows opening. Will it be ChatGPT’s app marketplace? Will there be something with Sora? Who knows. But the point is that we are in the middle of the distribution collapse and changes are coming.

5. The AI skillset is crucial

   I sometimes reflect how different my days are now compared to say... 2 years ago. I’m constantly building something in Lovable, discussing my ideas with ChatGPT (from writing/clarity to brainstorming growth loops), trying out new AI features (hating most, loving others).

6. Growth is confusing during the PMF treadmill
   In past companies, finding product-market fit (PMF) meant you could move on to scaling and growth becomes the priority. Here, PMF is temporary, which means the growth/scaling stage is also… temporary and confusing. Every AI company is on this treadmill, whether they admit it or not. But we still have X,000,000 of paid users and millions in revenue to grow… What exactly are you scaling if product is changing so rapidly? I approach it by over-indexing on innovation and not optimization, but who knows if that’s the right path. My plan is to focus on more traditional growth optimization work when our PMF stabilizes.

7. Roles are blending
   We still have job titles, but the walls between them are thin. Designers do marketing. Marketers shape product direction. Engineers do product work. Everyone runs small feedback loops across their own work. The generalist mindset is necessary. People who only operate inside their lane move too slow for this environment.

8. Organizational structure can’t keep up
   The development velocity is too high for a clean process. You have to be comfortable in the messy middle. Plans are short. Ownership lines shift. You have to self-author your role day to day. This is not for people who want predictability. The current environment rewards people who can create clarity instead of waiting for it.

Those are the lessons, but what does this mean on a day-to-day level? Here are some specific shifts I’ve made to change how I work:

• Plan in 2-3 week directional bets, not quarters.

• Optimize for learning speed, not comfort.

• Default to shipping over polishing.

• Spend more time editing ideas than managing process.

• Assume my current mental model will expire soon.

The work is intense, fast, and constantly shifting. It’s the most fun I’ve had in years.

Whether you’re in AI or not, the growth game is changing. Now, the skills that matter most will be: Letting go quickly, re-learning faster, working across boundaries, and always building things people love enough to talk about.

If you’ve been in this field for a while, these probably don’t sound completely new. They’re a continuation of what we’ve all been doing. But they’re more essential than ever and it’s all speeding up. That’s the amazing/terrifying thing about growth right now: Everything is up for grabs.

What you make of this opportunity is up to you.

Edited by Jonathan Yagel, assistant to the regional meme-ger.

A lot of product teams hate hearing that because it means they can’t hide behind feature roadmaps and velocity charts. They have to care about how the product makes people feel.

Yes, feelings. The stuff product managers tend to roll their eyes at. The stuff that historically got delegated to “brand” and “design” while product stayed focused on utility and speed.

That world is gone.

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