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Lesson 02 of 05 · published

Compaction Is Useful and Lossy

~24 min · compaction, loss, verification

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Compaction is not resurrection

Modern APIs can compact long interactions, sometimes carrying opaque internal state forward. That is useful. It is still not a license to stop writing explicit state. The compacted item may help the model continue, but the human cannot audit opaque reasoning directly.

Two compaction failure modes

Provider compaction (automatic, opaque): may help internally but you can't see what was kept. Manual summary (readable, lossy): omits details unless you list them explicitly. Both need verification. After compaction, ask what may have been lost and compare against durable files.

Trust, but inspect

The first turn after compaction should be a sanity check, not a sprint into destructive work. If the model has lost a critical rule or assumption, you want to find that out before — not during — the next risky action.

Compaction is a compression tool, not a truth oracle. Always verify before acting.

Code

After-compaction audit·yaml
post_compaction_check:
  - restate current goal
  - list live constraints
  - list touched files
  - list authority boundaries (do-not list)
  - name next safe action
  - say what might be missing
  - wait before destructive work
Audit prompt for the model·text
Drift audit (post-compaction):
Using only current context, list:
  1. Live rules I must obey.
  2. Things I must NOT do.
  3. Sources I have verified this turn.
  4. The next safe action.
  5. Anything I think might be missing.
Do not infer from priors. Say 'missing' if missing.

External links

Exercise

Draft a post-compaction audit prompt for your workflow. It should ask the model to admit missing context instead of reconstructing from priors.

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