Building a Personal AI Factory

"Fix inputs" => The assumption is there exists some perfect input that will give you exactly what you want.

It probably works well for small inputs and tasks well-represented in the training data (like writing code for well-represented domains).

But how does this work for old code, large codebases, and emergencies?

- Do you still "learn" the system like you used to before?

- How do you think of refactoring if you don't get a feel for the experience of working through the code base?

Overall: I like it. I think this adds speed for code that doesn't need to be reinvented. But new domains, new tools, new ways to model things, the parts that are fun to a developer, are still our monsters to slay.

> But how does this work for old code, large codebases, and emergencies?

Have you actually tried Claude Code? It works pretty well on my old code, medium size SaaS codebase. I’ve had it build entire features end to end in (backend, front end, data migrations, tests) in one or two prompts.