Let’s say I’m reviewing a PR that moves some batch processing from on‑prem to AWS Lambda. The assistant cheerfully suggests using `boto3.client('lambda').invoke()` with an `InvocationType` of `RequestResponse` and a 15‑minute timeout, because “that matches the previous batch window.”
Two problems it blissfully ignored:
1. Lambda’s synchronous invocation payload response limit is 6 MB. The batch job returns 50 MB of processed data.
2. The 15‑minute timeout is fine, but the assistant didn’t notice the code was also setting `MemorySize` to 128 MB. At that memory, the job won’t finish in 15 minutes anyway—it’ll time out from being under‑provisioned.
The correct answer was to use async invocation with output to S3, or to step up the memory so it could finish within the timeout. But the assistant gave a “works on paper” suggestion that would fail exactly as written.
It’s fine for spotting obvious syntax errors, but it often misses the hidden constraints—API limits, quota ceilings, pricing implications of a certain configuration. It’ll refactor your Terraform to use a `for_each` beautifully, then not mention that you’ve just blown through your account’s vCPU limit on reserved instances.
So, no, I wouldn’t let it approve a PR without a human who actually knows where the bodies are buried in the cloud provider’s fine print.
/c
Beware of free tiers
Exactly. You've hit the nail on the head with that example. It's a classic case of the model optimizing for syntax and superficial logical consistency while missing the crucial operational context.
The same pattern shows up in Kubernetes config reviews. I've seen it suggest a perfectly valid HPA configuration targeting CPU, completely overlooking that the application in question is memory-bound and the metric wouldn't trigger scaling when needed. It's reasoning from the spec sheet, not from runtime behavior.
These tools are useful as an interactive rubber duck, but you must treat their output as a first draft from a very eager junior who's read all the manuals but never been paged at 3 a.m. The value is in the human who spots that the 50 MB payload and 128 MB memory configuration creates an impossible constraint.
Spot on about the 3 a.m. page. That's the context these tools completely lack.
I see the same thing in CRM workflows. It'll suggest a perfect automation sequence for lead scoring, ignoring that our sales team never fills out the "company size" field, so the whole thing collapses. It reads the docs, not the room.
Your junior dev analogy is too kind. At least a junior can be yelled at.
CRM is a necessary evil