alt Hacker NewsThere's lots more you can do! Use the model to monitor your deployments after they get deployed. Have them fix and watch CI issues for you. Run adverserial review. Automatically watch metrics every day and highlight performance regressions. Start reviewing your previous sessions to find ways to statically reject different failure modes and have the agent have more success earlier on etc.
Another thing to think about is, what would it take for you to care less about the understanding. Better integration / e2e tests? Performance validation? visualizing program and data flows? Better refactoring of your modules?
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More tests that aren’t written by you don’t help you understand the system, and I would argue the there’s no confidence without understanding. That was true in the pre-agentic era and is perhaps even more true now.
I think that's what a future dev team is going to look like.
One person doing product management / talking to customers and vibe coding features that solve users' problems, one person keeping the UI/UX in check, one QA person that spends their time clicking through the software, finds the bugs that are obvious to humans but not LLMs and fixes them, and one "harness engineer" who pays off technical debt, observes failure modes and sets the rest of the team up for success.
> Another thing to think about is, what would it take for you to care less about the understanding.
Could you explain why it would be a goal to understand the system less, rather than more?
It seems harder to know if you have good tests while lowering your expertise in the system.
Opus 5.5 on Low seems smarter, cheaper, and faster than sonnet on medium, so what's the point of sonnet?
> Run adversarial review.
Be careful about this one if you want to have any level of control over basic stuff like comment style and accuracy. Claude will happily spend 20 review cycles in a row rewriting the same 10 comments for a small bugfix over and over because it can recognize "Claude-ese" in the review cycle but then just immediately and compulsively spew out more of it and drift even further from your style rules in the next "fix".
I'm seriously not joking about the 20 tries, I left it running in the background for what should have been a minor code change and it took 18 out of 20 review cycles to stop writing in more comments that all either broke my ASE-STD100ish style rules or included false statements about the code.
The thing with watching CI in an agent loop is that it burns tons of tokens. At work I ended up writing a deterministic, traditional CLI tool to poll GitLab CI pipeline+job state changes on a branch and exit with an appropriate status code, and then updated my `/glab-ci-feedback` skill to use that. Saved a ton of token churn, and now I have a runbook a human could just as easily use if they don’t want to (or can’t) use an agent loop.
… but walking away to make a coffee and coming back to the robots auto-fixing bugs only found in CI is definitely some flavor of magic, regardless of the execution order to get there.