Watch on YouTube: https://youtu.be/5gaqsgiF52c
I recorded this episode because I think every software engineer is feeling something right now that nobody wants to say out loud. We’re scared. AI writes code faster than us, junior roles are getting cut, and every week, some founder on Twitter brags about replacing their engineering team.
But I have to admit something, I was scared way before AI showed up. Four years ago, I was sitting in sprint planning, estimating tasks with random numbers, building features I’d never hear about again. I had no clue if anything I built actually mattered.
I felt replaceable. AI just made it everyone’s problem.
The Frustration Was Always There
The engineers who feel threatened by AI right now are the ones who were already stuck in a broken system. If your whole job is translating someone else’s decisions into code, AI is absolutely coming for that. That’s literally what AI is best at: taking instructions and producing output.
But if you understand what you’re building and why, what success looks like, whether it actually worked, AI can’t touch that. AI has no idea who your customer is. It has no judgment. It can’t tell if the feature you shipped moved the needle or was a complete waste of everyone’s time.
The engineers who aren’t anxious right now all have one thing in common. They understand the customer, make product decisions, and own outcomes. They’re product engineers.
The Smart People Have Been Saying This for Years
Sometimes people act like product engineering appeared out of thin air. It didn’t.
Back in 2019, Gergely Orosz wrote a piece called “The Product Minded Engineer.” When I read it, it was the first time I actually felt understood. Someone was describing exactly what I was trying to become. Engineers who don’t just ask “how do I build this?” but “why are we building this? What happens if we do it differently? Who actually uses this?”
He listed nine traits. Things like understanding business economics, building relationships with PMs and designers, and tracking the impact of your work after you ship. Every single one of those traits is something AI can’t replicate.
Then there’s Marty Cagan’s Empowered, where he made a bold case. Most product teams are feature teams. They get told what to build, and they just build it. Empowered teams get assigned a problem to solve and figure out the rest. A feature team is exactly the kind of team AI is going to replace.
Teresa Torres brought the concept of the product trio: a PM, a designer, and an engineer working together on continuous discovery. For the first time, someone was saying engineers belong in discovery, not just delivery.
AI is proving all of them right.
The System Is Broken, Not You
Product engineers exist because the way most companies build products is fundamentally broken. AI just made it painfully obvious.
Think about your typical product team. A PM figures out what to build, a designer makes it look nice, and an engineer writes the code. Every time you pass information from one person to the next, stuff gets lost. The engineer building the feature knows the least about the actual customer problem. The PM doesn’t understand how hard it is to build. It becomes a game of telephone.
The people who could have flagged the problems early, the engineers, weren’t in the room when the product decisions were made. A product engineer keeps all the context in one place. The customer problem, the business goal, and the technical constraints. Instead of scattering it across three departments that barely talk to each other.
What This Looks Like in Practice
I’ve talked to several companies doing this, and they all do it a bit differently.
At PostHog, engineers make the final call. They decide what to build, when, and how. PMs do research, competitive analysis, and customer feedback, but engineers own the decisions. Raquel Smith, one of their product and engineering leaders, told me the key is being crystal clear about who owns the decision. Once everyone knows who decides, there’s no confusion, no power struggles, no endless meetings trying to reach consensus.
At Zen Educate, Martin Pengelly-Phillips, the VP of Engineering, told me something I keep thinking about. Product engineers, there aren’t caretakers, they’re problem shapers. They still have PMs and designers, but engineers are in the mix from day one. They push back. They ask “are we even sure this is a problem?” That kind of engineer becomes more dangerous with AI, not less.
And then there’s Andsend. Kevin Östlin, the CEO, told me they mapped their bottlenecks and found they were losing 40 days per week in handoffs. Forty days. They dropped the backlog completely. Kevin told me he was still sneaking looks at his perfectly organised Jira project at night, crying a little that they had to let it go.
Now every standup is basically a sprint planning for the day. They never talk about features; they talk about hypotheses to test. They ship multiple times a day per engineer. Kevin said something I loved:
“What has been really interesting is how people that were traditionally very heavy engineers, they knew math, they wanted to do complex algorithms. Those people might as well be the ones becoming your best UI designers or UX researchers. It’s almost beautiful to see people finding their strength through actually getting freedom.”
That’s people coming alive because they finally get to use their full brain instead of just the part that writes for loops.
AI Didn’t Create This. It Just Blew the Doors Open
PostHog has been hiring product engineers since 2020. Linear and Ghost were doing this before ChatGPT even existed. The ideas have always been there.
What AI did is blow up the gap between product and engineering roles. Before AI, working as a product engineer was harder. Prototyping was expensive, synthesising customer insights was slow, and learning new skills outside your comfort zone took forever. Now you can prototype a user flow in hours instead of days and pull customer insights way faster.
AI didn’t just make product engineers faster. It made the old way of working obviously broken. If you’re still on a feature team where a PM writes the spec, a designer mocks it up, and you just code it, AI just made each of those handoffs feel pointless.
And here’s what’s wild. My friend, product leader Else van der Berg, pointed out that AI-native companies are showing a completely new pattern. Tiny teams, huge results.
Cursor: 800 million in revenue with 12 people
Mid-Journey: 200 million with 40
Bolt: Zero to 40 million in five months with about 20 people
Growing headcount used to be a flex. Now it’s kind of embarrassing. People at these companies don’t have AI anxiety because every person owns something real. Zero room for passengers.
What You Can Actually Do
If you’re an engineer who’s anxious about AI taking your job, that feeling is awful but useful. It’s telling you that your current way of working isn’t working. And honestly, it never really worked. You were already undervalued, already disconnected from the impact of your work. AI just made it impossible to ignore.
Start small. Next time you get a ticket, ask why. Push back on the problem. Suggest something different. Try to talk to a user before writing a line of code. You don’t need permission to care about the product. You never did.
Every time you do this, you’re building the one thing AI can’t replace: judgment. The ability to look at a problem and know what matters and what doesn’t.
If your company doesn’t want engineers who think this way, and it doesn’t plan to change, I’d be worried. Life is too short to be anxious at a job that’s making you replaceable.
If you’re a leader and your engineers are anxious about AI, that’s on you. Give them ownership, a real problem, and trust. As CTO coach Stefan Schmidt put it, what matters right now is real leadership. Setting a direction and trusting people to get there, not telling them what to build.
The best thing you can do for your team’s AI anxiety is give them something meaningful to own.
The Walls Are Coming Down
The engineers who understand the customer, who make product decisions, who own outcomes, they’re not worried about AI. They’re excited. AI makes them more powerful.
The dream builders have had all along, owning the whole thing from problem to solution to impact, is becoming real. Product and engineering are converging. The walls between roles are finally coming down because, in my opinion, they never really made sense in the first place.
The only question is whether you’re going to be part of that or sit there waiting for the next ticket while AI writes the code faster than you ever could.
