I asked engineering leaders at five companies how AI code reaches production. Four allow it with human review. The gate is process, not the model.

Andrej Karpathy coined the term after vibe coding, and the meaning shifted. Here is how a coinage turned into a discipline with rules and review gates.

Software 1.0 was assembly, 2.0 was high-level languages, 3.0 is natural language prompts. That reframing changed how I plan a project before I type.

Vibe coding buys speed, one prompt per feature. Agentic engineering buys control, several agents checking each other. Choose by what breaks if it is wrong.

It is the practice of designing agent systems that plan, execute, and verify their code. That structure is what separates it from one prompt and a prayer.

Component, layout, states, then the exact spacing. That order is what turns a generic card into something I would ship without redrawing it.

I hand over 300-500 characters of the right code, not the whole repo. Past a point, more context makes the answer worse, not better.

One prompt per feature fails. Chained prompts, each one building on the last output, got me a full feature in one session instead of four tries.

The AI hardcodes the key because nothing in the prompt says not to. I keep secrets in .env, load them in one config module, and set the boundary first.

Working code is the easy half. Deployment steps and monitoring are what I check before an AI-built app takes real traffic.