Dynamic Scaffolding

Problem

If the prompt always carries the full scaffolding library, easy requests waste tokens on examples they never needed and sometimes the irrelevant examples push the model toward a wrong shape of answer. If the prompt always carries nothing, the model under-performs on the hard cases that genuinely benefit from few-shot examples or explicit schemas. A single static prompt forces the team to choose between overshooting cost on easy tasks and undershooting quality on hard ones.

Solution

Maintain a library of scaffolds (few-shot examples, schemas, hints) keyed by task type or feature. At runtime, classify the task and inject the matching scaffolds. Audit which scaffolds fired per request.

When to use

• Some tasks need few-shot examples, schemas, or hints and others do not — static prompts overshoot or undershoot.
• A library of scaffolds keyed by task type or feature can be maintained.
• Task classification at runtime is reliable enough to route the right scaffold.