Final artifact
A model-routing matrix, an unsupported-answer policy, and a fallback ladder.
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.
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.
DepthPilot Summary
This lesson teaches the system when it should not answer
Many systems mistake answering for intelligence, but a reliable system must know when to clarify, retrieve, downgrade, abstain, or escalate. DepthPilot focuses on designing the routing matrix, unsupported-answer policy, and fallback ladder together. After this lesson, the user should be able to separate 'the model was weak' into routing mistakes, evidence gaps, or missing abstention policy.
Route by task class first
- Not every request deserves the strongest model or the most expensive path.
- Task classes should be driven by risk, evidence need, and budget instead of intuition.
- Without routing by class, abstention and fallback become random.
Legitimize abstention next
- Clarify, retrieve, abstain, and escalate should all be allowed outcomes.
- Refusal is not embarrassment. It is a quality mechanism when evidence is weak.
- If unsupported-answer policy is vague, the system will drift toward over-answering.
Write the fallback ladder explicitly
- The order of fallback must be designed in advance instead of improvised under pressure.
- Downgrade and abstain are different behaviors and should not be blurred together.
- The final artifact should prove the system stays orderly under uncertainty, not only when everything works.
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.
Reusable routing templates
Download the model-routing matrix
Bind task class, risk, evidence need, and budget to a concrete model or path.
Download the unsupported-answer policy
Write explicit policy for clarify, retrieve, abstain, and escalate behaviors.
Download the fallback ladder
Make downgrade, abstain, and escalation order explicit.
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.
LLM Model Routing Guide
An LLM model routing guide for systems that should not send every request down the same answer path
Many users search for model routing by asking which model is strongest. DepthPilot focuses on a harder question: which requests deserve the strong path, which should take the cheaper path, and which should not answer directly at all.
Open pathLLM Limitations
LLM limitations are not just about hallucinations. They are about knowing when the model should not answer directly.
Users searching for LLM limitations often only want a list of weaknesses. DepthPilot pushes further: you should learn how to route tasks into direct answer, clarification, retrieval, tool use, or refusal so fluent output stops stealing your judgment.
Open pathAI Eval Checklist
An AI eval checklist for deciding whether the system actually improved
Users searching for an AI eval checklist usually do not lack opinions. They lack an executable review frame. This page condenses the minimum eval logic into a checklist-style entry point.
Open pathReference appendix
These links anchor the method. The actual lesson is the routing matrix, unsupported-answer policy, fallback ladder, and deliverable templates above.