We're missing tests, evals or monitoring
"It feels better" is not a reliable test strategy. If you use AI functionality seriously, you need to be able to see what changes do and when things go wrong in production. We help set up that feedback loop.
Does this sound familiar?
Without a good feedback loop, an AI product becomes harder and harder to develop responsibly.
Testing is mostly manual
After every change someone tries a few known examples.
Prompt changes are hard to compare
You can't objectively tell whether version B is really better than version A.
Production errors are discovered by users
The system itself hardly flags deviating behaviour.
Model updates feel risky
A new provider or model version can change behaviour without clear warning.
Where do you want to be?
You want to change things with confidence because you quickly see what a new prompt, model version or code change actually does.
Regressions become visible
Important existing situations are automatically checked again.
AI quality becomes measurable
You compare changes against relevant examples and criteria.
Production gives feedback
Errors, latency and unusual behaviour no longer disappear quietly into logs.
Why does this happen?
Traditional software tests remain important, but AI adds behaviour for which there isn't always one exactly correct answer.
See how we approach thisAI output is probabilistic
Exact string comparisons are not enough for many AI tasks.
Good examples aren't recorded
Knowledge of what is right and wrong mainly lives in heads and scattered chats.
Observability stops at technical errors
An HTTP 200 says nothing about the quality of the answer.
Rescue Sprint
If the scope is clear, we set up a practical feedback loop in a Rescue Sprint with the right combination of tests, evals, traces and monitoring. If broader research is needed first, we start with an audit.
View this offer€5,950 excl. VAT
Per Sprint · one clear rescue goal
- Result
- The agreed technical blocker solved, tested and handed over
- Duration
- One week
- Next step
- You take it over, or another Sprint for a new goal
Why 9to5 for this?
A measurement layer is only useful to us if it helps engineers see faster whether a change is safe and actually better.
View casesRegular tests where possible
Deterministic software simply stays deterministically testable.
Evals where needed
AI behaviour gets examples and criteria that fit the real use case.
Production data closes the loop
Monitoring shows which real-world situations need attention.
What else fits your situation?
Vibe Code Rescue Audit · €2,950 excl. VAT
We examine what you have, what can stay as it is, where the real risks are and how you can move forward responsibly again.
View offerOur agent is not reliable enough
The agent can do impressive things, but does not behave predictably enough to trust a serious process or product to it.
View use caseEvery new AI code change breaks something else
New features ship quickly, but regressions, unexpected errors and repair work take more and more time.
View use case