DP

DepthPilot AI

System-Level Learning

Assessment

Routing policy audit: teach the system when it should not answer

This audit forces you to write explicit policy for task classes, model-path choices, unsupported-answer behavior, and fallback order. DepthPilot cares less about the claim that one model is stronger and more about whether you can explain which requests should use which path, when the system should abstain, and how those decisions can be reviewed.

Final artifact

A model-routing matrix, an unsupported-answer policy, and a fallback ladder.

Real acceptance criteria

Not that the system usually answers, but that it takes the right path when it should clarify, retrieve, abstain, or escalate.

Where our value shows

This page turns routing, abstention, and downgrade behavior into executable policy instead of vague anti-hallucination advice.

Routing matrix

Classify tasks by value, risk, and evidence need instead of by provider preference.

Give each class a latency and cost budget so not every request goes through the strongest path.

Define which tasks should never auto-answer.

Make routing rules reviewable by a second operator.

Unsupported-answer policy

Treat clarify, retrieve, abstain, and escalate as legitimate outcomes instead of failures.

Define the response to missing evidence, stale evidence, missing authority, and high-risk action requests.

Write the user-facing language so unsupported answers are explicit instead of hidden behind vague prose.

Treat refusal as a quality mechanism, not as product embarrassment.

Fallback ladder

Define whether the primary route should fall back to retrieval, clarification, downgrade, or abstention.

Separate downgrade from abstain: downgrade still delivers a bounded result, abstain means the system should stop answering.

Make the hard stop and human owner explicit.

Turn fallback into an explicit ladder instead of an improvisation.

Proof you must keep before launch

One routing matrix that makes task class, risk, evidence need, and budget explicit.

One unsupported-answer policy that covers clarify, retrieve, abstain, and escalate paths.

One fallback ladder that shows how the workflow degrades in order instead of jumping randomly.

One short recap explaining whether the workflow is currently most threatened by over-answering, overspending, or chaotic fallback behavior.

Search Cluster

Connect routing and abstention policy back to discoverable reliability paths

High-intent users often enter through model-routing, limitations, or eval-checklist searches before they commit to real unsupported-answer policy design.

Reference appendix

These links anchor the method. The actual lesson is the routing matrix, unsupported-answer policy, fallback ladder, and deliverable templates above.

Routing Policy Audit for Model Choice, Abstention, and Fallback Ladders | DepthPilot AI