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Setting up monorepos for AI: submodules versus subtrees
I've been building my app for 8 months now, and i ended up having 5 repositories
nextjs app
databases
customer facing API
node-sdk that wraps the api
react-sdk, for both reusing shared component and customer facing components
So i thought, it's gonna be great if i create a mono repo with submodules. But it was terrible. I realized that turborepo does not like external packages, and as i tried to reuse my own customer facing libs, the DX became terrible. It was very time consuming to ship a feature. Even when i wanted to use Codex or Cursor 3, it was not able to show git diff properly, also i was not able to use Cursor's cloud agents properly to ship complex features.
The 3 hardest technical problems I hit building an AI agent that calls real APIs
Not a launch post. Just things I wish someone had written down before I spent a month figuring them out.
1. LLMs send partial payloads on write operations
You ask the agent to update a record. It sends only the fields you mentioned in the prompt. The PUT request goes through, returns 200, and you've silently wiped every field you didn't specify.
The fix: before every write call, fetch the current resource state via the companion GET endpoint and deep-merge the LLM's payload on top. The LLM only needs to specify what's changing the executor fills in the rest.
