Why AI Coding Agents Still Get APIs Wrong Even When They Have Documentation

Saurabh Yadav — Sun, 13 Sep 2026 07:59:02 +0000

AI coding agents have gotten very good at writing code.

But APIs are still a surprisingly easy place for them to make mistakes.

The problem isn't always that the model doesn't know the API.

Sometimes the documentation is:

for a different version
spread across multiple pages
buried inside a traditional documentation site
missing from the model's context
inconsistent with examples found elsewhere
full of deprecated endpoints

That's what led me to build DocOrbit.

DocOrbit is an open-source documentation intelligence layer for coding agents.

Instead of treating documentation as a giant block of text, the goal is to turn it into structured, version-aware evidence.

The pipeline looks roughly like:

Documentation discovery -> Documentation graph -> Project dependency detection -> Version resolution -> Task-specific retrieval -> API intelligence -> Implementation context -> Code/API verification

One part I'm particularly interested in is verification.

If an agent generates code using the wrong endpoint, wrong HTTP method, missing required parameters, or a deprecated API, DocOrbit can compare the implementation against the documented contract and report the result.

The project is still evolving, but the goal is simple:

Don't just give coding agents documentation. Give them the right documentation, and check whether their implementation agrees with it.

GitHub: https://github.com/HakashiKatake/docorbit

I'd love feedback from people building coding agents, MCP servers, developer tools, or documentation infrastructure.

DEV Community: Saurabh Yadav

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Why AI Coding Agents Still Get APIs Wrong Even When They Have Documentation

Why AI Coding Agents Still Get APIs Wrong Even When They Have Documentation