[skeedle]

Even it's slow, you can run multiple agents. You can have one doing changes, while another writes documentation, while another does security checks, while another looks for optimizations. Persist finding to markdown files to track progress and for cross-agent knowledge sharing if need. And do whatever else while it's all running. This has been my experience.

[sarchertech]

But then you have to keep all those tasks in your head and be ready to jump into any of them.

The check-ins are much more frequent and the instructions much lower level than what you’d give to a team if you were running it.

Do you have an example of a large application you’ve released with this methodology that has real paying users that isn’t in the AI space?

[CuriouslyC]

If you set up your agents correctly, they can run for hours. My record is around 4 hours for a "prod/launch readiness" on a 90k LoC codebase, and that same codebase had a marathon lint and mypy plan that fixed ~700 issues over 6 hours (split around 3/3 due to API limits)

[foobarbecue]

OP says in 2nd paragraph that they are using multiple agents in parallel. In fact, that's what their app does.

[ants_everywhere]

if they are modifying the same code, then you have to merge all of different changes so it's not really parallel.

IME it's faster to not try to edit the same code in parallel because of the cost of merging.