Behind the Curtain: Why the Most Successful AI Apps are Actually Code-First.
We didn’t start with a big strategy. We just wanted to move faster.
We had APIs, Swagger specs, and a lot of repetitive work; validation, mock data, test payloads. So thought, “Why not let the LLM handle it?” and started a POC on it. It sounded right. And honestly, in the beginning, it worked. We gave it the spec, asked LLM to generate payloads, validate inputs, even simulate flows. The output looked clean. Demos went smoothly. Everyone was impressed.
Then we tried to use it in a real workflow. That’s where things started getting messy. The system didn’t crash. Which would have been easier. Instead, things failed in small ways. One request would pass, another one would fail. Same structure, same API, but slightly different values. Logs didn’t show anything obvious. No clear error pattern. Just inconsistency.
One example stayed with me. We were generating mock data for a dispute...
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