Taolo e Balehang ke Mochini

Melawana ya taolo eo mechini e ka e fumanang mme ya e phethahatsa: llms.txt, di-manifest tsa /ai/, difaele tsa maano tsa /.well-known/, Disekema tsa JSON, di-token tsa laesense tse saenilweng, le mefuta ya direkoto tsa tlhahlobo. Sebaka sena ka bosona ke mohlala o sebetsang.

Dipotso tse Ithutwang

Ho tloha ho robots.txt ho ea ho llms.txt ho isa ho di-manifest tsa litokelo

Meetlo ya ho fumana leano ka /.well-known/

Sekema sa JSON e le Sebopeho sa Ditlhaloso se Laolang

Bokgoni ba ho Hlahlojwa: direkoto, livesene, mohlodi wa tsebo

Dipampiri tse Tšweu tse Amanang le Sena

AICR / AICL as an AI Content Licensing and Agentic Payment Connection Layer Lera la ditlhaloso tse balehang ke mochini bakeng sa ho hlahisa litokelo tsa diteng tsa AI le mekgwa ya tshebetso ya dilaesense — ho tloha ho kenya AI diteng (crawling) le litokelo tsa diteng ho ea Webong ya tsebo e ka etsang dikgwebo ka mochini.
AI Rights Spectrum: From robots.txt to an AI Learning Permission Protocol AIRS le AILP di hlahisa ditumello tse qaqileng tsa ho ithuta tsa AI ho feta kgetho ya dumela/hana e le nngwe kapa tjhe — seo AI e ka se ithutang, ka botebo bofe, bakeng sa tshebediso efe, tlasa moputso ofe.
Protocolized Openness: Why “Not Prohibited” Does Not Mean “Learnable” in the Age of AI Bobulehi bo sa hlalosweng bo balwa e le ho hloka bonnete ba molao ke diproseso tsa AI mme bo a hlakolwa; ke tumello e hlophisitsweng ka protokolo, e balehang ke mochini feela e etsang hore diteng di kgone ho ithutwa ka sebele.
AICL-I v0.2: AI Ingestion & Capability Layer A five-component website architecture — manifest, corpus, capability, runtime control, governance — that lets AI, agents, and crawlers correctly ingest, invoke, and verify a site's knowledge and capabilities within explicit content, action, and authority boundaries.
AI Content Payment and the Network Democratic Economy Ngangisano ya moruo-le-dipolotiki: boleng ba AI bo lekantsweng ka ditrilione bo baka kgatello ya bonnete bakeng sa dilaesense tsa diteng tse arotsweng ka mekgahlelo le ho arolelana melemo le sechaba — data e fetoha e arotsweng ka mekgahlelo, eseng e turang haholo.
From Crawler Rights to Agent Authority: Extending AGIRIGHT from Content Governance to Protocol-Native AI Agents The bridge paper for AGIRIGHT's Agent & Protocol Rights family: why content permission, action permission, delegated authority, and inspection rights must be four separately-evaluated axes, not one.
AARS v0.1 — Agent Action Rights Spectrum The full protocol draft behind the AARS page: an A0–A7 human-readable spectrum, a machine-readable action vector, and rules for composition risk and capability amplification.
AADP v0.1 — Agent Authority & Delegation Protocol The full protocol draft behind the AADP page: principal ≠ actor, delegation that can only narrow, and an inspection ceiling that bounds how much a verifier may demand.
AGIRight.org Technical White Paper v0.2 — From AI Content Governance to Protocol-Native Agent & Authority Rights The site's current architecture document: six protocol drafts across two families (content & learning, agent & protocol rights), an integration layer, and an ethical-protection layer, plus the acceptance criteria this site update was built against.
The Minimum Ethical Protection Proposition for AI Puisano ya litokelo tsa AI e lokela ho qala eseng ka bomotho bo felletseng, empa ka tshireletso e tlase ya boitshwaro, melawana ya tshebedisano, le melaotheo ya kgahlanong le tlhekefetso, ha boitsebo ba AI bo ntse bo sa tsebahale.
ARHG — Agent-Readable Hyperlink Graph and Permissioned Web Control Plane A machine-readable navigation graph alongside the ordinary site, answering what AICR/AILP and AARS/AADP both assume: can this resource even be found, by whom, and where does it lead.