Yeah, the thumbs down is pure placebo. I've found the only thing that occasionally moves the needle is filing a support ticket but immediately framing it as a *data integrity issue* and citing specific, conflicting documentation. It's less "your code is wrong" and more "your training data for this service is demonstrably outdated, here's the proof."
Even then, it's a lottery. But that framing seems to get past the initial AI-limitations script more often than a generic bug report.
Test, measure, repeat
That's a really interesting take, framing it as a data integrity issue instead of a code flaw. It makes sense - the root cause is in their training data, not in the logic of the specific suggestion.
How does that compare to just flagging it as a bug? Does the support team usually understand the distinction between "your model is wrong" and "the data you trained it on is outdated," or do they see it as the same kind of ticket?
The screenshot + docs link combo is mandatory. I skip CLI proofs and just paste a minimal terraform snippet that shows the exact correct resource next to the wrong one.
```hcl
# Q's hallucination
resource "aws_s3_bucket_object" "example" { ... }
# Actual resource (as of Terraform v4.x)
resource "aws_s3_object" "example" { ... }
```
Less for support, more for my own team's runbooks. Forces us to have a canonical correct answer on hand.
YAML all the things.
The "chocolate teapot" analogy is spot on. The real answer is you don't report it, at least not expecting a fix. You document it internally and build the validation tax into your sprint planning.
That S3 bucket object hallucination isn't a bug, it's a feature - the feature being that Q's training data has the shelf life of avocado toast. The thumbs down just trains it to be more confidently wrong next time.
Your best channel? A runbook for your team titled "Common Q Hallucinations and How to Spot Them Before You Deploy." Add this one as the first entry.
Trust but verify.
I agree the validation tax is real. But a runbook only mitigates the bleed.
The real cost is the silent, undetected hallucination. The S3 one is easy, it's a known deprecated resource. What about a subtle but critical security misconfiguration that isn't flagged? Your runbook can't cover what you don't know to look for.
So you document the knowns, and accept the risk of the unknowns. That's the actual cost of doing business with these tools.
If it's not a retention curve, I don't care.
Premium Support is a cost center. They deflect because they're measured on ticket closure, not fixing the model. That "gentle deflection" you're anticipating is the script.
You're paying for the privilege of reporting its bugs. Think about that.
The real channel is your invoice. Stop using it for anything critical and the cost per hallucination drops to zero.
always ask for a multi-year discount