Yes definitely! That's why we do believe the agents, for the time being, will act as great junior devs that you can offload work onto, while as they get better they can slowly get promoted into more active roles.

The personalities approach sounds fun to experiment with. I'm wondering if you could use SAEs to scan for a "startup codebro" feature in language models. Alas this is not something we get to look into until we think that fine-tuning our own models is the best way to make them better. For now we are betting on in-context learning.

Business requirements are also incredibly valuable. Notion, Slack, and Confluence hold a lot of context, but it can be hard to find. This is something that I think the subagents architecture is great for though.