the literal meaningWhat "vibe coding" actually means, word for word.
Vibe coding is a way of making software where you don't write code — you describe an outcome to a large language model ("add a login screen", "make this faster", "why is this red") and it generates the code for you. The defining trait isn't the AI; it's the surrender. You stop reading the output. You run it, see if it feels right, and prompt again if it doesn't. Karpathy named it in February 2025, Merriam-Webster logged it as slang weeks later, and Collins made it Word of the Year for 2025. The dictionary version is simple: code by vibes, trust the machine, forget the source exists.
- Coined by Andrej Karpathy (OpenAI co-founder) in February 2025.
- The key word is forget — you accept the code without reading the diff.
- It's not "AI helps me code". It's "AI codes, I judge the result".
where it gets confusedVibe coding is not the same as using an AI assistant.
This is the distinction most articles blur. When you use Copilot or Cursor and you still read, tweak and approve every suggestion, that's AI-assisted programming — you're in the loop, you're the reviewer. Vibe coding is the moment you let go of that loop: you let the model take command and you deliberately don't check the code it produces. That single difference — oversight or no oversight — is the whole story. It's also exactly why vibe coding feels magical on a weekend project and turns dangerous the moment other people depend on the software.
- AI assistant = you read and approve every line. You're the safety net.
- Vibe coding = nobody reads the line. The safety net is gone.
- Same models, opposite amount of human oversight on the output.
the company problemWhy the meaning matters: vibe coding breaks at company scale.
At hobby scale, "forget the code exists" is liberating — worst case, a toy app crashes. At company scale, that same sentence is the risk. The code nobody read still ships to real users, holds real data, and has to be maintained by someone next quarter. The numbers are already loud: security teams at large enterprises saw findings jump roughly 10x in six months as AI-generated code spread, and analysts expect most companies to hit moderate-to-high technical debt in 2026, with fast AI adoption named as a main cause. The recurring failures are mundane and brutal: hard-coded secrets, missing authentication, SQL injection, code in patterns nobody on the team recognizes when it breaks at 2am.
- Hard-coded credentials and missing auth in MVPs that "look done".
- Maintenance debt: unfamiliar code no engineer can safely change later.
- "Why is this red?" with nobody who can answer — because nobody wrote it.
the fix isn't going backThe answer is a method, not more code review.
The wrong reaction is "so read all the code" — that just deletes the speed and puts the human bottleneck back. The right reaction is to keep the speed and add structure around it. We call it the Digital Native Method: a Product Owner describes the intention on the live product; a Tech Lead encodes the rules once (architecture, conventions, security, your company's standards); and AI agents deliver inside a structure that verifies everything before production. Deterministic gates — lint, types, tests, security — run on every change. Green or it doesn't ship. You keep "forget the code exists" — but now a structure remembers, every single time, instead of a tired human sometimes.
- Product Owner describes the result on the live product, in plain words.
- Tech Lead encodes the standards once; every agent boots inside them.
- Lint / types / tests / security gates pass before anything reaches prod.
the software for itAgentation is the software that makes the method real.
A method on a slide changes nothing. Agentation is the tool that enforces it: you point at your running product and describe what should change, the Tech Lead and agents implement it, the gates verify it, and it lands through your own GitHub — on your existing AI plan, so we never see your code. That's the line between vibe coding and shipping: not whether an AI wrote it, but whether a structure checked it before your users did.
- Annotate the live product; agents return verified, reviewed results.
- Everything ships through your GitHub — your repo, your history, your control.
- The structure reviews every change, so "I never read it" stops being a risk.
cocoricoBuilt in France — sovereign on the tooling that orchestrates the models.
Agentation is a French company, built by a French team. You may not be sovereign over the models themselves — Claude, GPT — but you can absolutely be sovereign over the tools that orchestrate them, and that's a huge part of the value: with raw models alone you don't get much done; the orchestration is where the work actually happens. So we make the layer you can own: hosting in the EU (Hetzner, Germany), data in the EU (Supabase), your code in your own GitHub, GDPR by design. Sovereign on the orchestration, even when the model is American.
- French company, French team — European by construction.
- EU hosting (Hetzner) and EU data (Supabase); your code stays in your GitHub.
- Sovereignty on the orchestration layer — the part that actually does the work.
FAQWhat is the simplest definition of vibe coding?
Building software by describing what you want to an AI in plain language and accepting the code it generates without reading it. You guide, test and re-prompt based on the result — you don't review the source. The term was coined by Andrej Karpathy in February 2025.
Is vibe coding the same as using GitHub Copilot or Cursor?
No. If you read and approve each suggestion, you're using an AI assistant and you're still the reviewer. Vibe coding is when you let go of that review entirely and trust the AI's output without checking it. The difference is the amount of human oversight on the code, not the tool.
Why does vibe coding break in companies?
Because the trait that makes it fast at hobby scale — not reading the code — becomes a liability when real users and real data depend on it. Unreviewed AI code ships hard-coded secrets, missing authentication, injection flaws and unfamiliar patterns nobody can maintain later. Enterprises have seen security findings spike roughly 10x as AI-generated code spread.
If reading all the code isn't the answer, what is?
Structure instead of inspection. The Digital Native Method keeps the speed — you still describe outcomes, agents still write the code — but a Tech Lead encodes the rules once and deterministic gates (lint, types, tests, security) verify every change before production. Agentation is the software that enforces that, shipping through your own GitHub.
Is Agentation a French / European tool?
Yes. Agentation is a French company. While the AI models are American, the orchestration layer is ours and can be sovereign: EU hosting (Hetzner, Germany), EU data (Supabase), your code in your own GitHub, GDPR by design. You own the tooling that orchestrates the models — which is where most of the real work happens.