Vibe coding is already obsolete — and that's great news for product managers
In 2026, Andrej Karpathy — the person who popularized the term “vibe coding” — got on stage and called it obsolete. What he proposed in its place he named agentic engineering, and he described it as a list of activities: writing design specs, supervising plans, inspecting diffs, writing tests, building evaluation loops, managing permissions, preserving quality.
Read that list again with the engineer-specific words removed. Deciding what should be built. Checking whether the result matches the intent. Defining what “good enough” means and refusing to ship below it. That isn’t a new discipline. As Jeff Gothelf put it, the judgment version is the job — it was always the job. AI just removed the places we used to hide it.
That is the single most important shift for anyone building products right now, and it points in a direction most people find counterintuitive.
The skill that survives isn’t coding
For a decade, “learn to code” was the universal advice for anyone with a product idea. In 2026 the advice quietly inverted. When AI agents can turn a clearly-stated problem into working software, documentation stops being the job — intent, clarity, and judgment become the job. The industry has a name for the people who matter now, and it’s not “prompt engineer.” Product School’s read on the year was blunt: AI product managers are the PMs that matter in 2026.
The mechanics back this up. Across the field, the consensus on what an AI-native PM actually does has converged on three verbs:
- Describe what you want clearly enough that a capable agent can act on it.
- Decompose the problem into pieces small enough to verify.
- Judge whether the output matches the intent — and decide what happens at the 15% where it doesn’t.
None of those three are coding. All three are product management.
Why not knowing how to code can be an advantage
Here’s the part that sounds wrong and isn’t. People who can code carry a running estimate of how hard this is to build in the back of their minds. That estimate is useful when you’re the one building — and a liability when you’re deciding what should exist. The idea gets pruned before it’s spoken, shaped by implementation cost instead of user value.
If you can’t code, you don’t have that reflex. You’re left holding the only questions that matter at the start: what does the user actually need, and is this experience right? Then your job is to say it clearly. And “saying the idea clearly” is the oldest core skill a product manager has.
That’s not an argument for staying ignorant. It’s an argument that the bottleneck moved. The scarce resource is no longer typing speed in a text editor; it’s the clarity of the thing you’re asking for.
”Speak it, AI builds it” is a method, not a vibe
The catch is that vibe coding earned its obituary for a reason. When you prompt loosely, every run drifts: designers have noticed that AI prototypes fill the space wireframes used to occupy, but each run of the same prompt produces something subtly different — semantic drift that widens fast. Loose intent in, inconsistent product out.
So the answer isn’t to prompt harder. It’s to work with discipline. That discipline is what we call DO AI PM, and it comes down to a few commitments:
- High fidelity first. Skip the wireframe. Build the real, runnable thing — real content, real states (loading, empty, error, success), real interactions — and verify it by actually running it. A working prototype outperforms a described one every time, including in the room where the decision gets made.
- Five phases, small steps. Discover → Define → Design → Develop → Validate. In Define, make the AI ask you questions before it writes the spec. In Develop, change one thing at a time.
- A safety net. No real secrets or production data in a prototype. The human presses the irreversible buttons — publish, delete, pay. Don’t touch production. When you’re unsure, ask.
That last list is the difference between “I got lucky with a prompt” and “I can do this again on Monday.”
The proof is the work
A method that only explains itself is worth nothing. So everything here is downstream of real products, all built this way with Claude Code: SoloMD (a Markdown editor), Unterm (a terminal AI agents can drive), unfetch (a download manager for humans and AI), StoryAlter (an AI writing companion), and Unflick (a media player for humans and AI). This very website — eight languages, this blog, the decks — was spoken into existence the same way. Not a line of it was hand-written.
The method explains the work; the work proves the method.
Karpathy was right that vibe coding is over. What replaces it isn’t a harder kind of engineering — it’s the discipline of deciding well and describing clearly. That has a name, and it’s a good time to have the job.
If you want to feel what “speak it, AI builds it” is actually like, start from the method center.
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