# Scaffold Ablation on Model Upgrade

> On each model upgrade, treat every harness component as an encoded assumption about a past model weakness — ablate the ones the new model no longer needs, gated by evals.

- **Category**: Agentic AI
- **Subcategory**: Governance & Observability
- **Canonical URL**: https://designpattern.fyi/patterns/scaffold_ablation_on_model_upgrade/

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## Description
**Intent**: On each model upgrade, treat every harness component as an encoded assumption about a model weakness — ablate the components the new model no longer needs, gated by evals.
**Context**: An agent harness accretes over several model generations: retry wrappers, decomposition scaffolds, format-coercion steps, guardrails, planning constructs. Each was added to compensate for something a past model couldn't do reliably. A stronger model arrives, and the harness is carried over wholesale because it "works." The result: scaffolding that was designed to patch weaknesses is now constraining strengths.
**Solution**: Make each harness component carry the assumption it encodes ("the model cannot keep a long plan straight," "the model will not emit valid JSON"). On model upgrade, walk the components and stress-test each assumption against the new model: temporarily remove the component and run the eval suite. If the eval holds, the assumption has expired and the component comes out; if it regresses, the assumption survives and the component stays. The eval suite is the gate; the anti-pattern is carrying everything over by default.



## Use Cases
- A harness has accreted scaffolding across several model generations.
- A model upgrade is being adopted and the team owns an eval suite to gate changes.
- There is evidence or suspicion that carried-over scaffolding is suppressing the new model's capability.






## Trade-offs


### Advantages

- Harness complexity tracks the current model's real weaknesses instead of accumulating across generations.

- Capability suppression from scaffolding built for weaker models is removed, not inherited.

- Each removal is evidence-backed — the review is auditable, not a matter of taste.




### Considerations & Drawbacks

- Ablating a component whose assumption hasn't fully expired causes regression if the eval missed the edge case.

- The review is only as trustworthy as the eval suite gating it.

- Per-release review is recurring work that a carry-everything-over approach avoids.







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**Reference**: [Original Source](https://www.agentpatternscatalog.org/patterns/scaffold-ablation-on-model-upgrade/)