This might work only if you have “infinite” compute and infinite tokens.

As someone that used the $20 plan, this pure agentic approach is impossible to do because I’d hit the limit fast and I would end up with less outcome.

What I found that work incredibly well was to provide a human written code as reference, and ask it to extend it. So I scaffold the entire thing, architect it, write few samples code (controllers, services, models, components, database schema, how auth works, etc) so the LLM can have a headstart on their attention (pun intended)

I usually wrote a stub with a lot of details on how to implement it. Something like a higher abstraction pseudo code. Then ask the LLM to implement it.

When it fails, it is often better to undo the whole changes, adjust the stub so it catches what fails before, and try again.

Or, commit the changes, and use a new fresh context and only address what went wrong.

-

Whenever I tried this agentic from scratch approach, I always end up disappointed; both on the outcome and on the limit that I hit before an hour even passed.