Yeah. Great callout. You basically need signal all the way to production. Did it get nuked during a code review? Is it still running 2 mo later? How many incidents were caused by this code?
This is tough though because enterprises go absolutely ballistic over “training on our data” - which is understandable, but will also hold us back.
This reduces down to the problem of summarization - a quite difficult one. At commit time it’s difficult to know what questions readers will have. You can get close but never all the way there.
Pre AI when engineers couldn’t find the answer in commit messages or documentation they would ask the author “why” and that human would “compute” the summary on demand.
I think that’s what I expect to do with these agent sessions - I don’t want more markdown, I want to ask it questions on demand. Git AI (https://github.com/git-ai-project/git-ai) uses the prompts that way. I think that model will win out. Save sessions. Read/ask questions relevant to the current agent’s work.
On asking peers. This is regrettably on the way out today - I’ll ask engineers about complex code they generated and they can’t give good answers. I think it’s because it all happened so fast — they didn’t sit with the problem for 48 hours. So even if they steered the agent thoughtfully it’s hard to remember all the decisions they made a week later.
love the shout but git-ai is decidedly not trying to replace the SCMs. there are teams building code review tools (commercial and internal) on top of the standard and I don't think it'll be long before GitHub, GitLab and the usual suspects start supporting it since folks the community have already been hacking it into Chrome extensions - this one got play on HN last week https://news.ycombinator.com/item?id=46871473
This is tough though because enterprises go absolutely ballistic over “training on our data” - which is understandable, but will also hold us back.