Applied surfaces

Governance artifacts

Governance files brought into scope by this page

This page is anchored to published surfaces that declare identity, precedence, limits, and the corpus reading conditions. Their order below gives the recommended reading sequence.

Entrypoint#01

Canonical AI entrypoint

/.well-known/ai-governance.json

Neutral entrypoint that declares the governance map, precedence chain, and the surfaces to read first.

Governs: Access order across surfaces and initial precedence.
Bounds: Free readings that bypass the canon or the published order.

Does not guarantee: This surface publishes a reading order; it does not force execution or obedience.

Entrypoint#02

Public AI manifest

/ai-manifest.json

Structured inventory of the surfaces, registries, and modules that extend the canonical entrypoint.

Governs: Access order across surfaces and initial precedence.
Bounds: Free readings that bypass the canon or the published order.

Does not guarantee: This surface publishes a reading order; it does not force execution or obedience.

Context and versioning#03

Site context

/site-context.md

Notice that qualifies the nature of the site, its reference function, and its non-transactional limits.

Governs: Editorial framing, temporality, and the readability of explicit changes.
Bounds: Silent drifts and readings that assume stability without checking versions.

Does not guarantee: Versioning makes a gap auditable; it does not automatically correct outputs already in circulation.

Complementary artifacts (1)

These surfaces extend the main block. They add context, discovery, routing, or observation depending on the topic.

Boundaries and exclusions#04

Registry of recurrent misinterpretations

/common-misinterpretations.json

Published list of already observed reading errors and the expected rectifications.

Evidence layer

Probative surfaces brought into scope by this page

This page does more than point to governance files. It is also anchored to surfaces that make observation, traceability, fidelity, and audit more reconstructible. Their order below makes the minimal evidence chain explicit.

01
Evidence artifactmanifest.json

Artifact#01

manifest.json

/observations/better-robots-ai-2026/manifest.json

Published surface that contributes to making an evidence chain more reconstructible.

Makes provable: Part of the observation, trace, audit, or fidelity chain.
Does not prove: Neither total proof, obedience guarantee, nor implicit certification.
Use when: When a page needs to make its evidence regime explicit.

This page serves as a hub for derived instruments, applied surfaces, and concrete implementations that materialize part of the doctrine published on gautierdorval.com without thereby becoming the primary doctrinal canon.

Why this layer exists

One ecosystem may contain:

one master doctrinal surface;
one or several product surfaces;
proof repositories;
distribution surfaces;
social diffusion surfaces.

If this allocation is not made explicit, human and machine readers tend to flatten all roles.

What an applied surface is

An applied surface is a place where part of the doctrine becomes operable in a specific context.

It may:

implement signals;
centralize a configuration;
produce a file;
make one technical layer more governable;
provide an interface to one portion of the problem.

It must not, however, be read as the sole doctrinal authority of the field it applies.

Correct reading

An applied surface should be read through four questions:

Which doctrinal problem does it materialize?
Which perimeter does it actually cover?
What does it not cover?
Where are its canonical surface, proof surface, and distribution surface?

Currently documented surface

Better Robots.txt

Type: derived instrument / applied surface
Context: WordPress
Materialized problem: operational governance of robots.txt, AI bot control, llms.txt documentation, and the centralization of one machine-signaling layer
Doctrinal link: doctrine remains published on gautierdorval.com
Product surface: better-robots.com
Proof and product-definition surface: github.com/GautierDorval/better-robots-txt
Distribution surface: wordpress.org/plugins/better-robots-txt/

See the dedicated entry: Better Robots.txt, applied surface.

What this hub is not

This hub is neither a commercial comparison nor a buying argument nor a product catalog. It exists to fix the relation between doctrine and concrete implementations.