# Protocol

# Protocol

AIEP — the **Architected Instruction & Evidence Protocol** — is a simple idea made operational.

It exists because instructions and claims shape the real world, but the evidence that should support them is often scattered, unverifiable, or lost. The web made publishing easy. AIEP makes publishing **knowledge** easier by linking what is said to what supports it.

AIEP does not require a new internet. It uses the one we already have.

## The core rule

An instruction should be linked to evidence.

In AIEP, an **instruction** is any statement that people or machines may rely on: a decision, a directive, a conclusion, a requirement, a certification claim, a compliance statement, or an operational event.

**Evidence** is the artefact or set of artefacts that justify the instruction. Evidence can be a document, dataset, log, certificate, image, measurement, or any object that can be referenced and validated.

AIEP turns this into publishable infrastructure by making three things normal:

1. **Publish machine-readable surfaces** so AI can discover what is available.  
2. **Publish artefacts with provenance and hashes** so integrity can be checked.  
3. **Preserve dissent and outliers** so discovery stays alive and recall is possible when new evidence appears.

## Mirror: how AIEP is published on the web

AIEP Mirror is the publishing pattern that makes AIEP usable at scale.

A Mirror-compatible site publishes machine endpoints under:

`/.well-known/aiep/`

Those endpoints allow automated systems to discover the publisher’s artefacts, schemas, and policies. This Hub is itself an exemplar Mirror node.

## Knowledge states: consensus, outliers, and recall

AIEP reflects how knowledge actually evolves.

Consensus is what the evidence most strongly supports today. Outliers are ideas that do not currently fit, but may fit later. Radical outliers are archived ideas held at low confidence until evidence arrives.

AIEP treats dissent as a feature: it preserves competing views while requiring that claims be linked to supporting artefacts. This allows “dead theories” to be recalled when new evidence makes them relevant again.

## Why this matters for AI

More people are using AI as a replacement for search. But models cannot safely rely on unstructured, unverifiable web content.

AIEP enables **evidence-backed knowledge retrieval**: machines can retrieve artefacts from sources that publish them, validate structure with schemas, and check integrity using hashes.

**The future of information retrieval is not search — it is evidence-backed knowledge retrieval.**