What should be versioned together in an AI application?

Treats model, prompt, schema, tools, routing, retrieval, policy, and evaluators as one observable behavior release.

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TL;DR

I assign a release identity that links the model or deployment, prompt templates, output schema, tool definitions, routing rules, retrieval configuration, safety policy, and application code. A trace records the relevant versions for every response. This makes evaluation, incident diagnosis, and rollback refer to an actual behavior bundle rather than a vague model name.

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Practice focus

Configuration identity, reproducibility, rollout, compatibility, and rollback.

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Core answer first, then checkpoints toward a stronger answer.

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Core answer
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Overview
AI behavior changes through configuration and external assets even when application code does not.
I assign a release identity that links the model or deployment, prompt templates, output schema, tool definitions, routing rules, retrieval configuration, safety policy, and application code. A trace records the relevant versions for every response. This makes evaluation, incident diagnosis, and rollback refer to an actual behavior bundle rather than a vague model name.
Checkpoint
Stronger answer
Optional upgrade with examples, trade-offs, and sharper phrasing.
Not every asset must share one deployment mechanism, but compatibility is tested before combinations become eligible. A schema change may require a prompt and parser change, while a retrieval migration may need matching embeddings and thresholds. Configuration comes from reviewed, immutable versions instead of mutable dashboard values with no audit trail.

Review signals

Use these to catch weak phrasing, shallow reasoning, and risky claims.

Common mistakesCandidateCommon mistakesMistakes that weaken the answer or signal shallow understanding.Open details

Details

Recording only the marketing name of the model.
Editing production prompts without an audit trail.
Changing schemas independently of parsers and tools.

What should be versioned together in an AI application?

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