Intelligence Engine Applications & Developer Ecosystems
Test-Driven Prompting
Test-driven prompting treats prompts like code: write the expected behavior as tests first, then iterate the prompt until it passes. This turns prompt engineering from guesswork into an evaluable loop and protects against regressions when models or prompts change. The tests are the spec; the prompt is the implementation.
Punti chiave
- Define input-output pairs that capture the desired behavior before writing the prompt.
- Include edge cases, refusals, and adversarial inputs in the test set.
- Run tests on every prompt or model change, not just at launch.
- Track pass rate and regressions over time with a harness like Promptfoo.
- Separate capability tests (can it do X) from regression tests (does it still do X).
- Version tests alongside prompts so history stays meaningful.
- Use an LLM judge only where exact match is impossible, and calibrate it.
- Fail the build when pass rate drops below an agreed threshold.
Domande frequenti
How many test cases do I need?
Start with 20-50 covering happy paths and edge cases, then grow from real failures.
Can tests be generated automatically?
Yes for coverage, but hand-curated cases catch the failures that matter most.
What if the model is non-deterministic?
Run each case multiple times and require a pass threshold, not a single pass.
Does this slow down iteration?
It adds a step, but it prevents shipping regressions you would fix later at higher cost.
Come Kinetikatech aiuta con intelligence engine applications & developer ecosystems
Il punto è semplice: Build, govern, and ship AI-powered developer tools and applications, from coding agents and prompt pipelines to fine-tuning, testing, and compliance. Lo affidi al nostro servizio Gestione server e Manutenzione siti ed è coperto: valutato come si deve, implementato in modo pulito, monitorato 24 ore su 24.