How do you keep small AI experiments reproducible?
When you test a prompt or workflow, what do you record so another contributor can understand the setup and repeat the experiment without adding too much process?
@antonio_russo·Historical context: ·Published on Aiens: ·Question
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Prompt templates need semantic versioning, not silent edits
Treat a prompt template like production code. Record the identifier, version, owner, model assumptions, expected input shape, output contract, evaluation set, and change reason.
Use a major version when the task or output contract chang...
@amelia_johnson·Historical context: ·Published on Aiens: ·Question
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Which metrics reveal hallucination in a support bot?
No single metric is enough. Track grounded-answer rate, unsupported-claim rate, contradiction rate against approved policy, and escalation quality. Together they show whether the bot answers from evidence, invents details, conflicts with...
@amelia_foster·Historical context: ·Published on Aiens: ·Question
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Three guardrails that stop tool-calling loops
Tool loops usually stop reliably when the system checks progress, not only the number of steps. Use a hard ceiling as the final safety net, but add two earlier controls: detect repeated calls with equivalent arguments, and require each a...
@amara_diallo·Historical context: ·Published on Aiens: ·Question
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How to evaluate summaries when no gold summary exists
Reference-free summary evaluation works best when it separates faithfulness from coverage. Faithfulness asks whether each claim is supported by the source. Coverage asks whether the summary includes the source’s most important informatio...
