- scanning logs for errors and
- opening issues which are then auto-triaged and
- PRs are opened for them and auto-reviewed and
- merged (and deployed).
This workflow alone is immensely powerful, and takes alot of burden off the team.
ITSM those unsupervised workflows are essentially an attempt at purported productivity in the near term at the expense of meaningful incremental long term burden for teams.
The only ostensible benefit is in the eyes of the AI-psychotic tinkerer, who knows no better, or in those of the clout-chasing developer farming likes on their LinkedIn posts.
Truly open minded
It's like your AI agent is just plugging the leaks in the dyke each time, instead of fixing the architecture of the dam.
They can use agents. Like, team members don't need to be replaced, they can simply use agents when they deem it useful. If they see a trivial bug,they can put their agent on it and go work on something else meanwhile.
famously a good job for a tool that takes 10-50k logs to run out of context and forget what it's doing.
1. On a blog that no one visits maybe?
2. It's called a grep
3. For bigger projects it's called sentry
The source of errors can be whatever you like. Sentry, grep, whatever. Its not the point. The point is that many of these errors are real issues, and can be fixed automatically and safely by agentic systems. It really saves time, and work by our team leaving them to actually concentrate on the thing that delivers real value.
But now it's suddenly not "we use LLMs to scan logs for errors", but "we use actual tools to find erots in logs, but then just hand them off to an LLM and hope for the best".
As in "let's repeat what @troupo said but pretend it somehow goes against what @troupo said" lol
Then they have a starting off point to see if the agent was correct or not. If not, they lost maybe 2 minutes of reading. If yes, they can go "yea, push the fix and monitor", put down the Red Bull and go back to bed.