The rise of the AI-native employee

Managers without vertical expertise, this is your extinction call

I’ve been at Lovable for five weeks and yeah… I’m not in Kansas anymore. This company operates on a completely different level - and as someone who’s spent my entire career in traditional tech, I’m seeing a very different pattern here that’s worth sharing.

Lovable is blowing past crazy revenue milestones: $1M ARR in just 8 days post-launch, $17M in 3 months, $60M in 6 months, and $80M ARR in just 7 months. With ~35 people. That’s not a typo. That’s the new normal - if you’re AI-native. And I don’t just mean the product is AI-native. I mean the people are.

What even is an AI-native employee?

Before Lovable, when someone said “AI-native,” I assumed they meant the product. Built with AI at it’s core. Agent workflows. GPT something-something. But after getting in the trenches here, I’ve realized: the product being AI-powered is only half the story. The real shift is how people work.

An AI-native employee isn’t someone who “uses AI.” It’s someone who defaults to AI.

Typical tech company: a case study in bottlenecks

Let’s rewind to the traditional tech org.

You have an idea. Great. Now you need either money or people to solve it. It goes something like this:

Step 1: Craft a beautiful doc… that nobody will read.

Step 2: Sit through 26 meetings, syncs, check-ins, standups, and “quick connects”… that accomplish absolutely nothing.

Step 3: Submit a request to design… that goes into the bottom of the backlog.

Step 4: Beg for budget to maybe, just maybe hire a contractor who might be available sometime this quarter… just to enter endless conversations with Finance about ROI.

Step 5: Ping web dev to squeeze it into this sprint… so they can laugh at you.

Step 6: Wait… while pretending the Gantt chart isn’t six weeks out of date.

[Bonus]: Discover - surprise! - there is tech debt. Add 8 months to your delivery.

Step 7: Finally ship something so scoped-down, so watered-down… that it barely resembles your original vision.

Sound familiar? Yeah. That’s the cost of dependency drag. Specialization is great until it becomes a coordination tax. Enter: ops teams and managers to manage the mess.

And just like that, your velocity dies.

AI-native org: default to done

Now let’s talk about how AI-native employees do it (as seen at Lovable)

Here, when someone wants to build something (anything) - from internal tools, to marketing pages, to writing production code - they turn to AI and... build it. That’s it.

No headcount asks. No project briefs. No handoffs. Just action.

At Lovable, we’re mostly building with… Lovable. Our Shipped site is built on Lovable. I’m wrapping hackathon sponsorship intake form in Lovable as we speak. Internal tools like credit giveaways and influencer management? Also Lovable (soon to be shared in our community projects so ya’ll can remix them too). On top of that, engineering is using AI extensively to ship code fast (we don’t even really have Product Managers, so our engineers act as them).

Can everything be done this way? Absolutely not. But even when we do go cross-functional (aka my design and dev teams jump in), things still move at crazy speed - because everyone’s using AI to cut the fluff, skip the handoffs, and just… get things done faster.

Will it change as we grow? Maybe. But right now, this feels very different from any other startup of similar size I’ve ever encountered.

Spotting the ai-native in the wild

Most (not all) of the AI-native employees I’ve seen are young (at least compared to me, LOL) - fresh out of school, sometimes not even graduated yet. And honestly? That’s their superpower. They haven’t been indoctrinated with our corporate bullshit. They’re not weighed down by legacy processes, approval chains, or the deep-rooted belief that "things just take time." They see a problem and start building.

So what changes?

1. Ownership is real: You build it? You own it. No “well leadership changed the scope” excuses. It’s your idea, your execution, your result.

2. Autonomy is unlocked: There’s no need to wrangle five other teams. You can just go. And that freedom is addictive.

3. Trust becomes the backbone: You can’t move this fast without implicit and explicit trust. If you need a weekly check-in to approve button colors, this ain’t your speed.

4. Velocity becomes your moat: When the whole company moves like this, it stops being a team dynamic - it becomes cultural gravity. And customers feel it.

Proof and point on velocity: in the five weeks since I joined, we’ve shipped a referral program, launched free collaboration, and in just a few days, annual plans and credit rollovers will be live. And that’s only a highlight reel - there are countless improvements and optimizations that happened in between. This is just growth, I’m not even talking about our core team. Again, remember - 35 people total!

The hidden superpower: cheap failures

When you can move this fast, the cost of failure plummets. That means:

• More bold bets.

• Less analysis paralysis.

• And a wild, unfair advantage in learning loops.

“Move fast and break things” is back - but this time with 10x output and 1/10 the mess.

But what about the jobs?

Cue the naysayers:

“But the process is good, it helps us stay aligned!”

Sure - if by “aligned” you mean equally stuck. Attaching yourself to process is just trying to validate your own existence and hard earned experience. Don’t do it (but I appreciate it’s painful). Adapt to the new norm. Let velocity lead, and introduce process only when (and if) it’s actually needed.

“Won’t this kill jobs?!”

Most jobs are just fine. Ya’ll just need to maintain your vertical expertise and learn to work with AI. But me be crystal clear, I think some jobs will disappear:

• Operations roles that only exist to herd cross-functional chaos? Gone.

• Managers with no vertical skill, acting as coordination layers? Extinct. And thank goodness.

We’re not replacing people. We’re replacing bloat. The rise of AI-native employee means the fall of organizational calories that don’t create value.

AI-native employees can’t survive in legacy systems

AI transformation inside existing tech companies is going to be brutal. You can’t just spin up a centralized “AI task force” and expect the rest of the org to suddenly think and operate differently. It doesn’t work.

This mindset shift isn’t something you can document or mandate - it has to be seen and experienced. I know, because I had to see it myself.

And even if a few brave AI-native employees emerge, the existing bureaucracy will smother them with a thousand tiny cuts: “Did you get that approved?” “Who signed off on this?” “Let’s run it through the process.”

Congrats, you just killed the spark before it had a chance to catch fire.

The future, in one hot take

Here’s my bet:
→ Company sizes will shrink.
→ Org charts will flatten.
→ The middle management layers without vertical expertise will vaporize.
→ The AI-native employee will become the new 10x team.

Welcome to the future #AINativeEmployeeEra