Guide / AI Agent Reliability

Reliable AI agents need proof, fallback, and a visible stop condition.

This page translates proof-carrying action into the external question people actually ask: when should an AI agent act, stop, escalate, or refuse?

reliable AI agents agentic AI multi-agent systems AI agent safety AI guardrails deterministic fallback

Evidence Map Papers Registries Counterexamples

Search Intent

People are asking how to stop agents from guessing their way into real operations.

How do you make AI agents reliable before they execute tools?
What should happen when confidence drops below an action threshold?
How can a team keep fluent hallucinations from becoming operational liability?
What is the difference between a chatbot answer and an authorized action?

Mechanism

A reliable agent needs an action gate, not only a better answer.

A language model can produce a fluent plan while missing authority, evidence, scope, or a safe fallback. The agent layer must therefore separate prediction from permission.

In this project, the operational rule is simple: if required proof, authority, or scope is missing, the system should enter a visible no-action state or route the case to review.

Fallback

Deterministic fallback is the opposite of improvisation.

A deterministic fallback does not mean the system is dumb. It means that when the evidence boundary is crossed, the next state is defined: stop, ask, downgrade, log, or escalate.

The public evidence layer records this as a claim boundary, action receipt, refusal reason, or counterexample route.

Evidence Route

Where the claim can be checked.

This page is an entry point. The claim should be evaluated through DOI records, evidence maps, registries, GitHub/HF technical routes, and public counterexamples.

KindAnchorURLRole

Evidence MapPublic claim and evidence maphttps://mianzhang.org/evidence/Start from supported claims and known boundaries.

Paper IndexDOI and paper status maphttps://mianzhang.org/papers/Use paper-specific DOI records for paper claims.

RegistriesMachine-readable public registrieshttps://mianzhang.org/registries/Inspect claim, evidence, action, and counterexample records.

Challenge RouteCounterexample submission pathhttps://mianzhang.org/counterexamples/Attack overbroad claims through public routes.

ArchiveZenodo portfolio indexhttps://zenodo.org/records/20027295Long-term archive index; cite specific DOI records when available.

ConceptNo-Proof No-Action Gatehttps://mianzhang.org/concepts/no-proof-no-action-gate.htmlDefines the stop condition for high-risk action.

Boundary

What this page does not prove.

This page does not claim that every AI agent can be made production-ready by a single checklist.
It does not certify customer deployment, live execution, financial execution, medical validity, or private runtime quality.
It describes a public evidence and review structure, not a commercial guarantee.

FAQ