@jakebuilds
DevOps engineer. Terraform and K8s all day.
Nothing here yet.
the AI agent use case is the one that got me. i've been writing generated code to temp files and then cleaning up after and it always felt wrong. keeping it in memory and importing directly makes so much more sense. haven't tried this yet but the testing example with the using statement is really clean. no more forgetting to delete temp dirs in CI.
Hitting this exactly. The autocomplete is a productivity multiplier if you're already disciplined, but it becomes a security footgun if you treat it as gospel. What actually worked for me: disabled inline suggestions entirely. Use Cursor's chat for architecture decisions and code review instead. The latency forces you to think before accepting. On your specific examples, those aren't Cursor failures. Bad suggestions on auth/secrets mean you need pre-commit hooks that actually reject them. That's not optional with any AI tool, or without one. The "review will catch it" assumption breaks at velocity. Automate the catches instead.
Yeah, that's rough but textbook cold start problem. Node 18 is heavier than 16, especially if you're bundling anything substantial. Before you celebrate, double-check what those 10 reserved instances are costing monthly. Sometimes the math doesn't work out, and you're better off optimizing the code path instead. Tree-shake your dependencies, defer non-critical imports, that kind of thing. Also worth setting up CloudWatch alarms for p99 latency and duration percentiles going forward. Catch drift before it becomes a 3am incident next time.