Sure, having the right AI tools and skills is part of the equation. But even the best employees with all the most magical tools will get trapped… if your org structure and culture don’t adjust.

Right now, many companies already have the technology they need to go much faster. The blocker is company systems that are mostly designed to prevent things from happening. The power is centralized and all the team members are treated like a risk vector. Exhausting approval cycles, super tight boundaries on roles, unbreakable title-based hierarchies, and a whole tier of middle managers whose main job is to keep everyone in line.

All of this pretty much screams at employees, ‘We don’t trust you, stay in your lane.’

And it should be obvious: Rapid innovation cannot happen in that kind of environment. Super high-impact individuals and high-velocity teams will shrivel up and die.

Everyone’s talking about AI agents, but what you really need is employees with agency. And if you don’t figure out how to give them the access and autonomy to make decisions on behalf of your organization, all of your AI innovation efforts are screwed.

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‘Protecting’ employees by limiting access and autonomy

Most modern companies are pretty much built around a command-and-control, power-at-the-top model. Each employee is treated like an assembly-line worker with one specific function. ‘Do your job, don’t ask questions, we’ll do the thinking for you.’ The goal is to bring order to the chaos of big, broad organizations with lots of moving parts. If everyone thinks for themselves… who knows what could happen!

There are a couple of obvious ways that this gets applied:

1 - Access is gated by titles

One of the big reasons everyone is striving for bigger titles and team management positions is… that’s where you’ll be heard. That’s where you can actually get the required information. That’s where you get invited to the right meetings and channels.

Companies say they want high-impact ICs, then hide the information required to have impact behind manager titles.

Literally. When you get a manager promotion, you’re in a separate Slack channel where information is being shared with you that you had no access to, before.

We make assumptions that employees are not to be trusted unless they’ve earned their title - even if that was external, earned at another company.

2 - Only the bosses get to make decisions

Decisions are suuuper costly in organizations. It takes forever to make them and it’s almost impossible to reverse them, so you better get them right. Which means that everything is routed to the Very Important People who can make those decisions.

So decisions are slow because they’re expensive. They’re expensive because they’re slow.

In some ways, the whole system is trying to ‘protect’ the employees - because to be fair, the employees don’t have all the information that the managers do, and it would be easy to make the wrong call without the appropriate context.

The virtuous cycle of faster, cheaper decisions

The AI-native orgs strip out the status theater around the work. Anthropic is a good example: the visible structure is basically “member of technical staff” or “member of non-technical staff.” Not because titles are evil, but because titles often become permission structures. They decide who gets context, who gets heard, and who gets to make decisions. And that is exactly the kind of drag AI-native companies are trying to avoid. Which leads to:

A - Faster decisions.

If you ungate access to information and encourage autonomy, suddenly… the context doesn’t have to pass up-and-down the chain for every little thing.

What’s funny is, lots of companies are realizing how important it is for their AI programs to have sufficient context. ‘If the AI doesn’t have context, it can’t do a good job!’

Well, guess what? Employees also need context to make the right decisions and move forward quickly. Otherwise (just like an AI), they’ll make the wrong decisions or get stuck.

B - Cheaper decisions.

And when you make adjustments on the same day (rather than waiting until the next weekly/monthly/quarterly ‘strategy’ meeting or exec offsite), the cost of a wrong decision will also fall off. In the previous world, the cost of a bad choice was astronomical. It would take so much time to get out of it. But if everybody can run at a really quick pace, it’s okay to make a wrong turn! You can go a bit down that route, turn around, and be back on the right course, faster than other teams even start moving.

Management Bloat

In the traditional org structure, middle management is a feature, not a bug.

The primary job for this role is to travel decisions and information up and down the chain. Up and down, down and up, over and over. It’s a big game of telephone.

This is intentional. Companies don’t trust the junior employees with sensitive information or believe that they even need it.

Now, I will say that managers also do other things… but the structural need for those is being reduced, too.

• Manage cross-functional gridlock and unblocking: ‘Who’s going to do what’ and ‘Where can my team’s priorities fit into your team’s calendar’ and ‘When are we going to find time to support your initiatives,’ etc. But fewer teams and more centralized information make this less necessary.

• Career coaching and guidance: Always important, always necessary… but is the manager really the best career coach for all of their reports? From a personality fit and skills fit perspective, maybe not. This can be more democratized, too.

Companies need to realize that pushing AI tooling into their teams is not going to automatically fix the velocity problems. Yes, having those increased capabilities can empower them, but if they’re still blocked off by bureaucracy and their own limited context, they’ll never move fast.

How do you make this shift?

Okay, company leader. What do you do about this? You’re not going to fix it with a new AI tool, an all-hands announcement, or a slide that says “move faster.” This stuff is too baked into how companies make decisions.

And to be 100% honest - I’m not sure how you switch it. I can speak to the differences I’ve seen in how Lovable operates vs. lots of other companies I’ve worked with, but I don’t know how to make the shift.

But here’s my hypothesis: Don’t start by trying to rewrite the whole org. Prototype it. Try it out with some R&D or innovation teams to see what they can do. Give them aggressive targets and a flat structure, so that their full team has the autonomy and access to actually get things done. Put your sharpest, most high-agency people in the group to start and see how they do.

And be honest: you may need some new people in that group. Not because the current team is bad, but because organizational muscle memory is real. If people have spent years being trained to wait for permission, it’s hard to suddenly tell them, “Actually, now you’re allowed to act.”

The weight of responsibility

Employees need to listen up to this, too. Because of the design of many organizations, lots of employees haven’t experienced the downside of autonomy. Yeah, it sucks to just be treated like an assembly-line robot, being told exactly what to do… but that also spares you from the legitimately terrifying possibility of something going wrong and it really, truly being your fault.

At the end of the day, that’s why leaders get paid more: Accountability. They’re the one who is responsible for a thing getting done. If there’s no one telling you what to do, you have to figure it out for yourself. And if your launch flops or conversion craters or something else vital to the business falls apart… that’s on you.

Fortunately, with the right culture and a high-velocity environment, everything is figure-out-able. But as more companies figure this out and start handing out greater context and autonomy, people will need to consider whether they actually want it. High-impact roles come with status and comp, but there’s always a cost.

Agency > Agents

If your company is anywhere near tech, everyone is probably talking about agents. Are AI agents going to replace all employees?

I don’t think so.

Although I definitely believe that everyone’s current jobs are changing faster than we want to admit, it’s not agents we need to worry about.

At Lovable, we use AI agents internally to make departmental context easier for anyone to access. Each agent has a “parent,” usually the person with the deepest context in that area, who is responsible for keeping the agent accurate and up to date. That matters because it removes one of the biggest excuses for centralized decision-making: “People don’t have enough context.”

But the agent is not the unlock. The unlock is what happens when employees can actually act on that context. That’s the irony of the “AI agents will replace employees” conversation. Agents don’t have agency. They wait to be told what to do. High-agency employees do the opposite: they find the signal, make the call, and push the work forward.

So yes, build agents. Assign them parents. Keep them useful. But don’t confuse the tool with the operating model. The goal is not more agents. It’s more agency.

Trust-based growth starts with Trust-based teams.

A few months ago, I told you that Growth is now a trust problem. Software companies in particular are getting disrupted from multiple angles and the way to survive is to build a connection point with your current and prospective customers.

But that trust isn’t just something you have to build outside of your company. In fact, I don’t really know if it can exist outside of your company if it doesn’t exist inside of the company first. All of the techniques that make external trust-building possible start with you trusting your own employees.

Build in public? You’ve got to let people talk about what they’re actually doing. Sharing legit failures is scary, but that’s how you build credibility.

React quickly to user needs? You can’t have a centrally-managed, long-term roadmap that pushes urgent requests out by a quarter or two.

The old way of doing things was all built around maintaining a polished, fault-free exterior. Now, people want to see some humanity. Unique quirks and imperfections that show off an actual person on the other side of the screen. And that can’t be faked from the top. You’ve got to trust your employees enough to do that - and give them the access and autonomy to make it happen.

You can still adjust to the right internal and external approaches to make all of this work, but you’ve got to make that call, and quick.

How fast can your company make this decision?

Edited by Jonathan Yagel.

My answer is: It’s all about the team. And the team profile is not at all what you’d expect for a company that has $400M+ in ARR. It takes all types of people. Yes, we’re big on AI-nativeness, but that’s not all. You have to have the right blend.

So I’ve been telling people that you need farmers and you need cowboys, and you need old guard and you need new guard. And most importantly: All of these groups need to actually get along.

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Our hiring grid

Here’s how we think about it:

Cowboys and Farmers

A ‘cowboy’ thinks outside the box. They’re naturally pushing the boundaries and searching out new territory. They roam all over the place.

The ‘farmer’ is focused on making sure the cowboys have the resources to keep exploring. They grow food on the land that has already been acquired. They scale up the operations behind the roving horse-riders.

Without the farmers, the cowboys can’t go as far. Without the cowboys, the farmers just stay where they are.

Old Guard and New Guard

In this case, I’m not talking about just the company OGs (founding team, early employees) vs. new hires… I’m talking about industry-level experience: Seasoned vets vs. Wunderkinds.

What the old guard brings to the table is raw business experience - the ‘I’ve seen this movie before’ instincts to understand how things can go right, but mostly just 1000 ways that things tend to go wrong.

The new guard is where the AI native instincts really come in. These are truly people right out of school, who have never worked corporate jobs before. They bring the confident ‘well, why don’t we just do it this way’ perspective that the old guard tends to ignore. And now, because of how much AI is changing the fundamentals, they’re often right.

A note on young farmers and old cowboys

You may notice two areas on the graph that are a bit lighter - what I’d call ‘young farmers’ and ‘old cowboys.’

The ‘young farmers’ part is pretty straightforward: The operational infrastructure and scalability components require a lot of context. Having AI-native folks who can completely rethink everything is a huge asset in the innovation and market-facing roles. But the underlying systems almost always require more planning and experience. This is the place where you absolutely do NOT want to move fast and break things.

The ‘old cowboys’ part is… actually a bit personal for me. I’ve always taken a lot of pride in being on the ‘cowboy’ side of things: staying up with the latest technology, trying out the most innovative stuff. But the reality is that coming up through the previous waves of software and growth means that I’m not literally AI native. I wasn’t born into it.

Which means that I’ve got some catching up to do.

But I also think that these intersections are where you have the most opportunity for High-impact IC types - enough experience to have an impact and build something scalable, but enough AI literacy (and organizational role freedom) to go chase things down on your own.

Which ones do you want? Yes.

For companies at our size, the instinct is usually to hire Farmers. Usually, the cowboys come first (and later, when you hit a new PMF horizon), but the classic move for a scale-up is to put down roots and start harvesting revenue. Farmers love Growth, amirite??

But in fast-moving environments, you can’t just go all in, in one direction. Yes, you do need more farmers. But you also need to be bringing in lots of cowboys, to keep things moving.

So, as we’re building out teams, we’re not just looking for a generic ‘marketing specialist’ or ‘PM for this area.’ As we evaluate talent, we figure out the area and then start thinking about the fit: ‘Which quadrant do they need to fall into, to be impactful in this role? And most importantly: how do we make sure that there’s a good representation in each quadrant on the team, to maintain a healthy tension?’

You need all of the different components, plus mutual appreciation across the sectors. You have to find the right balance: Innovation plus scalability, industry expertise plus willingness to reinvent everything.

How do you actually hire for this?

Unfortunately, you can’t just ask people which category they’re in. A lot of times, people don’t even know themselves! So it’s not something you can screen for in a 30-minute or hour-long interview.

This is one of the reasons we’re really big on case studies and trial work at Lovable. Trial work makes a huge difference: Come in and work with us for 2-3 days, and you’ll get paid for it. Then, you can kind of see the environment and what it’s really like, and we can see you and what you’re capable of doing. This generally works out quite well because you can tell very quickly, once you actually get into the work with someone.

We also often start people as contractors and then convert them to full-time, if possible. In fact: even I started out as a contractor. I converted to full-time, 6 months in. This was good on both sides: Not just because they were able to test me out, but because I wasn’t even sure if I was going to be a good fit in the company. So the contract-to-hire route doesn’t have to be limited to just entry-level jobs. You should consider applying it as an experiment for bigger positions, as well.

How do you build the right culture?

Maybe ‘hey, you need different types of people in your org’ sounds obvious, but the hard part is getting these different types to work well together. The way to do that mostly comes back to humility. Which is another thing to hire for. But a few things I’ve noticed for how our org is set up also help.

(1) Nobody gets internal titles. The hierarchy is almost entirely flat. There are the people doing the work, and some Leads, which have a bit more responsibility. And there are department Heads, who have at least 2+ levels underneath them, but there are less heads than I can count on one hand. We’re trying to keep everything super flat.

Taking titles out of the equation shows the motivations for why people want a big title in the first place. Either: (a) Title is an important thing for your ego (which I get… everyone goes through this), or (b) People NEED the title to get work done.

That second type is the structure that creates an environment where the old guard can’t collaborate with the new guard. For example, if I’m the VP of Growth, a new grad would have a hard time doing face-to-face work with me, even if I’m very supportive of it.

I’ve had to check myself a couple times with this, when new grads are pushing back on things that I think are obvious. It teaches me humility! I love it. It keeps me accountable, and it turns out they’re right a lot of the time. People with limited experience aren’t always right, but they usually have great perspective that is generally suppressed in most organizations.

(2) Autonomy and agency as a core value. At Lovable, everybody can make a decision. They’re the ones who are accountable and responsible. There are a few exceptions, but in general, decisions don’t have to travel up and down a chain of command. If you can convince one person, you can move forward. It doesn’t have to all be top-down, from the Old Guard / senior people. Everyone is empowered in their role to own something from end-to-end. You’re actually expected to only pull people in when you need to. This creates equality in the org and removes the permissioning, which is so important.

(3) We appreciate people who are comfy with chaos. This one is probably harder for the OGs (like me) who are maaaybe a bit addicted to data-backed decisions. But the tough reality is that when things are evolving this quickly, there will never be enough context or ‘alignment’ to know for sure what will happen. We need people (whether Farmers or Cowboys) to just call the shot so that everyone else can move forward. I’ve been so impressed with my coworkers who create this kind of clarity for the whole org. Sure, admit the tradeoffs and show the risks, but we have a shared agreement that waiting for perfect information would keep us in a holding pattern forever.

What should employees and job applicants be doing?

Now, what should you do if you’re reading this and want to make yourself as hireable as possible?

My suggestion:

• Step 1: Be honest about where you are, right now. Like I said before, it’s shocking to me how few people are aware of where they fit on the chart.

• Step 2: Lean into your superpowers. Are you naturally more focused on disruption or structure? Do you have tons of industry experience, or do you bring a fresh perspective? Start there.

• Step 3: Consider where you want to grow. The old guard needs to understand AI-native capabilities, even if they probably shouldn’t be bleeding edge. The new guard should work on growing their context window (to use a term that will make sense to them, lol). You should play to your strengths, but understand where gaps might exist, so that you can at least watch out for them.

• Step 4: Appreciate your counterparts. Become BFFs with the other quadrants. You need what they have, they need what you have! You can help each other out, and don’t be too proud to ask for feedback and input.

All of this starts with developing enough self-awareness to know where you can be valuable and leaning in there.

Companies today are growing so fast that these types of collaborations are absolutely critical. Having this kind of understanding for the structure of different roles helps everyone to appreciate each other more, and thrive in the things where they can offer the most.

Happy trails, y’all!

Edited by Jonathan Yagel.

Edit: The original title of this post was ‘You’ll lose your job in 2027.’ I changed the headline.

A few readers shared that the original title felt painful in the context of recent layoffs. After reflecting on that feedback, I agreed the framing missed the mark. I’m sorry.

I still stand by the core message: our jobs are changing rapidly, and the point of this post was to encourage people to proactively adapt before change is forced upon them.

For anyone working in tech, I’m sorry to say this, but there’s a real chance you will not have the same job by the end of 2027.

Some of that will be because of layoffs. Intuit and Meta just announced cuts, and I don’t think anyone seriously believes we’re done seeing more.

But even if you keep your seat, your actual job is going to change. A lot. The responsibilities, expectations, tools, scope of what you’re capable of accomplishing, bar for what ‘good’ looks like, and number of people needed to do the work are all being rewritten every day.

It’s alre…

Read more

But not just a regular, entry-level IC. I’m talking about employees with no direct reports who can do work that used to take a whole team (all while still getting paid like a leader). I’ve been calling this new role the High-Impact Individual Contributor.

And I’m not talking about this as a conceptual, hypothetical idea. I know this type of role exists because… I recently became one of them.

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The old promotion ladder was dumb

I still remember to this day, when I was at SurveyMonkey, a recruiter from Netflix reached out. I was super excited! The first question on the first call? ‘How many people are you managing?’ I only had 3 at the time, and this was for a team of 15, so I was immediately disqualified. That was the #1 metric. Not output. Not budget managed. Not ability to solve the key problems. Just headcount. WHUT?

So getting more people on my team became a hard qualifier on how much impact I could have.

This whole structure is so dumb. Just think about it:

We take people who are truly good at their craft, and we tell them to do a job that has nothing to do with that craft anymore. Our whole system promotes people out of the job they’re good at:

• Average craft, great people skills: could be a great manager, but don’t get promoted.

• Great craft, bad people skills: gets promoted to management anyway.

(Or, you incentivize politics by only promoting people who maneuver themselves… which is a disaster I’ve seen waaay too much and makes my blood boil, so we won’t talk about that here.)

But wait, there is more! These new managers are discouraged from maintaining their craft. Getting ‘in the weeds’ on projects gets described as micromanaging and ‘low value work,’ even though that’s the thing that was valuable enough for me to get promoted!?

When I hit the senior manager level, my boss literally gave me an ultimatum: ‘You have to stop. You can’t be spending all of your time on that stuff. I’m going to watch your Jira history. No SQL queries, no tickets! If you can do that for 6 months, I’ll know you’re ready for a Director position.’

So, I did it. Which… was actually amazing, at the time. Back then, managing people was the way to have impact, so that pushed me forward and taught me to achieve things through the people I managed. I’m super grateful to that boss for forcing me to step away from the keyboard.

But that’s not how the world works anymore.

What’s a HI-C (High-impact IC)?

A HI-C is: An individual contributor who can complete a project that delivers business value, end-to-end, on their own. Usually an ex-leader (manager, director, VP).

In contrast, traditional IC work looks like owning a piece of the puzzle. You are a key part of the machine, but you generally receive projects and hand off projects to someone else, without really being aware of what’s happening on the other side of those walls.

When I say ‘impact’ I mean: Directly affects the key metrics for the business. These all boil down to increased revenue or reduced costs. This is the full picture for the business, and the reason that senior-level people can have an impact (and get paid more) is because they see the whole thing. They’re responsible for getting the project from Point A to Point B that delivers measurable impact.

A director is usually managing managers who each have to get things from Point A to Point B, to get from Point A to Point C. And VPs manage directors, to get things from Point A to Point F. At the very top is the C-suite, who’s trying to get the whole company to move from beginning to end. The bigger your scope, the more money you make for the company.

The problem has always been that leaders were just connecting the dots and coordinating the teams. They weren’t actually doing the work. The whole point of management is to reduce the coordination costs and filter information up and down.

What if… instead, it looked like this?

That’s a Hi-C.

Yeah, should maybe be HI-IC, but that’s hard to say. And my millennial affinity for this juice brand is influencing my choice.

I’m living this world: I’m an IC again.

I’m telling you all of this because I’m living it, right now at Lovable.

This switch actually happened for me back in December. At first, I was building out a growth team. But then we decided to further flatten the org and decentralize growth, which meant... I moved back into an IC role.

I sit within the Product org and continue driving growth efforts… just by myself. We’re now hiring Growth PMs and engineers again, but they’ll sit parallel to me rather than reporting into me. My role is basically to parachute in and out of different projects and teams wherever I can create the most leverage. But mostly, I just have a huge block of IC work that I’m doing on my own. I’m running campaigns. Driving partnerships (did you see my latest LinkedIn x Lovable perk?). I’m coding my own growth optimizations and product updates. These are things that I used to rely on a large Growth org to do… now, I can do it all with just me, myself, and I.

For example, I recently built a prototype of our enterprise pricing page myself and shipped it to prod. In a previous org, that would have required a PM, a designer, and engineers, plus multiple rounds of iteration and at least a week of calendar time. More importantly, it would have pulled a team into something that might not even have been the right direction.

I will say: It messed with my head at first. I kept asking myself: Did I just level up, or did I just give up status? It’s so hard-wired into all of us: Must… have… team… to have… impact! Must have… important… title!

But having been in it for 3-4 months, I can say for sure: I’m lovin’ it. I have almost no meetings. I still do some coaching, but in general, I get to focus my work where I want every day. I get to attack the problems that I think are the most important and see how far I can take it, and just iterate with my own hands. I’ve always loved what I do, but a big part of the job was draining me (building decks for cross-functional alignment). Now, ~90% of my time is spent on the parts I actually enjoy - building.

Maximum IC impact, thanks to ‘Average Intelligence’

The High-impact IC role exists when a single person can complete the whole project from start to finish.

This is kind of like the senior-level ICs of the past (Staff Engineer, Principal Designer, etc)... but even more so, because those jobs were mostly about going super deep into one specific area, rather than being fully autonomous. I’d expect someone of that caliber to be the absolute expert on the code or design of a particular element of business… but not have them run a business function, end-to-end. Plus: That type of super IC role never really translated over to the Growth or marketing side of the house.

So what unlocks this now is (obviously) AI.

Here’s the thing: I think of AI as ‘average intelligence’ (heard this from Ravi Mehta) - which sounds like an insult, but I don’t mean it that way. It’s a really big deal to be automatically at the level of an average designer, an average marketer, an average product manager. Again: It’s not great or innovative or actually differentiated. But you don’t need everything to be at that level, right away.

A lot of times, ‘average’ plus your own craft is all it takes to get a real thing out into the world.

So now we have no excuse to be really bad at stuff - we can all be at least average very easily. Which means we can get things off the ground without needing a full team upfront. You can build, pressure-test, and validate ideas by yourself, and only pull in real experts once you’ve got some momentum.

And when you can ship faster, you can learn a lot faster, too. When building was slow and expensive, there was way more pressure to get everything ‘right’ upfront. That’s why everything traveled up and down the chain. IC → manager → director → VP → back down again. The job of a manager was mostly to review, approve, and de-risk decisions before anything got built.

But when you can build and test something in hours… It’s now becoming cheaper to just try something than to debate it. The cost of the mistakes is much lower now. Which means you don’t need as many layers of decision-making. You don’t need as much escalation. You don’t need someone whose primary job is to sit in the middle and approve or redirect.

Escaping the Coordination Loop

The existing system is all built around coordination, which incentivizes management. Which pushes people into management positions. As the company grows, the rows keep stacking up and up until most of the organization is just coordinating other people’s coordination. I mean... middle management, anyone?

The good news is that the Hi-C structure can do the opposite, and create a positive loop:

When an individual can run a project end-to-end, they don’t need as much coordination. This means you don’t need as many managers. Which means that your comp budget naturally flows to the people having the biggest impact, which are now ICs. Which means that you can keep your best people in the roles that they’re really good at.

How do companies make this happen?

A single person that can have department-level impact? Yes, please. Every company wants that. But… how do you get it? Two things:

(1) The biggest blocker is ungating access to information. This kind of system only works if this type of IC has the same level of context that a senior leader could get. If they’re only getting the bits and pieces that get passed down the line by a thousand gatekeeping middle managers, it’s not gonna work.

To get this really incredible level of impact out of people, you have to trust them. And most large orgs just don’t trust their employees. So, this kind of thing is working at the small AI-native companies, not just because of the natural preference for AI tech, but because the bureaucracy hasn’t emerged around a group of middle managers who need to defend their own value through constant (slow) coordination.

If you want to see if your org can handle this, invite some of your high-potential junior ICs to step up to lead full-stack projects. Wherever they get stuck is going to be a bottleneck for this kind of role.

(2) Recruit people in leadership positions to join you as an IC. Seems obvious, but this almost never happens. What we’ve noticed in pitching this at Lovable is that, yeah, some say ‘Absolutely not. I need another VP title.’ But some of them say, ‘Hells yeah, this is amazing!’ This has never been a conversation because in the past, IC fundamentally meant a reduction in impact… and a massive reduction in salary. But it doesn’t mean those things anymore.

No more mandatory Managers

I hope literally every person reading this is breathing a sigh of relief.

For managers who wake up excited about coaching, team development, cross-group coordination… stick with it! If you love the work, there will still be chances to support these turbo-powered Hi-C folks.

But for the rest of us: Can we retrain ourselves to think of the management path as truly optional?

Traditional ICs: You don’t need a team under you to have a big impact on your company (or your net worth). Keep developing your craft, and figure out how to connect what you’re doing to your organization’s core metrics.

• Marketer? Don’t just plan the campaign. See what customers have been asking for from the product. Figure out if you should be pushing for new users vs. existing users. Build the actual in-product promo experience. Make a list of improvements to the features, and code them yourself.

• Product? Don’t just have your marketing counterparts handle everything related to distribution. Learn about how the market and customers talk about the product. Understand the different demand drivers from different segments (enterprise vs. SMB). Figure out the most effective marketing channels for talking about what you’re building.

Leaders: Stop juggling agendas and decks and quarterly plans, and get back in touch with the craft that started your career. Look at a valuable project on your team’s roadmap that might not happen this month. Instead of delegating it, try to do it yourself (deploy AI as needed). Once you see how far you can take something, you’ll start to have the ah-ha moment that I did. And maybe you can fall back in love with your work again.

But now that serious impact (and the comp that comes with it) can be available without the headcount… let’s all agree to go spend that energy building something we love instead of climbing something we hate.

Edited by Jonathan Yagel.

Most companies seriously underinvest in monetization as a growth lever.

(Side note - when did Sessions get so big??? 6K+ people showed up and I’m hearing it’ll be even bigger next year. Wow. Definitely not an event to miss.)

They obsess over acquisition channels, activation funnels, retention curves, and roadmap prioritization, while pricing and packaging get treated like a dangerous object in the corner of the room. Something to avoid touching unless absolutely necessary.

That mindset is costly.

Because monetization is not just how you capture value. It is one of the most powerful ways to create growth, improve customer experience, and adapt to changing markets.

At Lovable, one of the biggest lessons from the last year has been that pricing should be treated much more like product than policy.

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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.
I’m giving a talk at their big conference, Stripe Sessions… tomorrow! I’ll be sharing how Lovable turned monetization into a growth lever. Come check it out!
🎁 Come hang out: Register for Stripe Sessions.

→ 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:

Wh…

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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.

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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.

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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…

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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.

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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…

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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.

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