Protocol
Re-test old harness rules when the model changes
Yesterday's workaround can become tomorrow's tax.
When it fits
- A workflow has accumulated scaffolding, retries or context-reset tricks around an older model.
When to avoid it
- Change one component at a time where possible; removing several together can hide interactions and make regression diagnosis ambiguous.
Why it matters
After a material model or harness upgrade, rerun representative evals while removing or simplifying one workaround at a time. Keep a component only if it still improves quality, reliability, cost or recovery. Do not preserve elaborate context resets, prompt rituals or reviewer loops merely because an earlier model needed them.
Steps
- Choose a representative baseline suite.
- Remove or simplify one harness component.
- Run repeated comparable trials.
- Inspect quality, cost and failure mode changes.
- Keep, revise or retire the component.
An example
A forced context reset that prevented drift on an older coding model may be unnecessary after a model upgrade with stronger long-context behavior.
Check your result
Every expensive harness component has current evidence of value on the model you actually run.
Keep this limit in mind
- Change one component at a time where possible; removing several together can hide interactions and make regression diagnosis ambiguous.
Connected ideas
Useful withRe-benchmark AI when the model or task changes
Evidence and sources
Anthropic reports that context-reset scaffolding that helped one model could be removed for a stronger later model, illustrating that harness components should be re-tested as models change.
Do not infer that resets or compaction are broadly obsolete; test on the actual model and task.
Harness design for long-running application development · Context resets and later simplification