[max_on_hn]

(Disclaimer: I built and sell a product around that workflow)

It often is, if you pick the right tasks (and more tasks fall into that bucket every few weeks).

You can get a simple but fully-working app out of a single prompt, though quality varies widely unless you’re very specific.

Once you have a codebase, agent output quality comes down to architecture and tests.

If you have a scalable architecture with well-separated concerns, a solid integration test harness with examples, and good documentation (features, stack, procedures, design constraints), then getting the exact change you want is a matter of how well you can articulate what you want.

One more asterisk, the development environment has to support the agent: like a human, agents work well with compiler feedback, and better with testing tools and documentation/internet access (yes my agents have these).

I use CheepCode to work on itself, but I am still building up the test library and preview environments to de-risk merging non-trivial PRs that I haven’t pulled down and run locally. I also use it to work on other apps that I'm building, and since those are far more self-contained / easier to test, I get much better results there.

If you want to put less effort into describing what you want, have a chat with an AI to generate tickets. Then paste those tickets into Linear and let CheepCode agents rip through them. I’ve got tooling in the works that will make that much easier, but I can only be in so many places at once as a bootstrapped founder :-)