· agentic ai

Agentic AI outgrew robots.txt. Grade your policy against what replaces it.

Agentic AI does not just crawl. It compares, books, buys and acts, across millions of sites, under a rulebook written in 1994 for a simpler machine. robots.txt can tell an agent to stay out. It cannot tell it 'you may read prices, you may transact under this limit, you may not train on reviews, and here is who to call'. The agentic economy needs that sentence in machine-readable form, and the standard for it is being drafted right now.

AgentGate is Ingenious AI's entry in that draft: the agent-access policy standard at /.well-known/agent-policy.json. This check grades your current posture against the elements any serious standard will require, whichever draft wins.

Honest scope, read this first: this page grades policy completeness, not legal sufficiency. No agent-access standard is final: the Agent Web Protocol's agent.json is at draft v0.2, and AgentGate is a competing proposal with a policy-depth angle. A published policy guides honest agents and documents your terms; enforcement against agents that ignore it is a separate layer.

Agentic AI: why the standard is being written now

Standards arrive when the traffic does. Bots passed humans in web requests in June 2026, at 57.5% of HTML traffic on Cloudflare's network, and agents are the growth inside that majority. Google's AP2 is standardizing how agents pay. The card networks standardized intent the same October week. The remaining blank is the site's own side of the conversation: what the site itself declares.

That blank is why two policy drafts exist already, agent.json from the Agent Web Protocol and AgentGate's agent-policy.json, and why more will come. The sites that publish early are not just adopting a standard; they are rehearsing the terms they will want when agents are the majority of their customers too.

57.5%bot share of HTML traffic in June 2026 (Cloudflare Radar)
1994the vintage of robots.txt, the current universal policy file
6elements a serious agent policy needs: agents, actions, limits, terms, contact, version
v0.2the draft stage of the rival agent.json: early enough to shape, late enough to matter

Why grade a policy against a standard that is not final?

Because the elements are not in dispute, only the file format is. Every serious draft names agents, actions, limits and terms; they differ in syntax, not in substance. A site that has decided its answers can adopt any winning format in an afternoon. A site that has not decided will adopt the winner's defaults, which are somebody else's answers.

Grade your agent policy against the standard's elements

Score your site element by element. Everything runs in your browser; nothing is sent anywhere.

Reach standard-grade: the working order

  1. Inventory your agents: from server logs, name the agents that actually visit. Policy for imaginary agents protects against nothing.
  2. Decide the six elements: named agents, permitted actions, refused actions, limits, data-use terms, contact and version date. Business decisions, made once.
  3. Publish in machine form: agent-policy.json at /.well-known/, generated from your decisions. AgentGate's generator produces it from a short questionnaire.
  4. Align the old files: robots.txt and llms.txt should tell the same story as the policy. Contradictions are found by agents and by lawyers, in that order.
  5. Review quarterly: agents, defaults and drafts all move. A dated review keeps your policy a living document instead of a 2026 fossil.

AgentGate, by Ingenious AI, is the machine-readable agent-access policy standard: declare which AI agents may use your site, what they may do and on what terms, at /.well-known/agent-policy.json, with a generator that drafts the file from your decisions. See how AgentGate works.

FROM INGENIOUS AI
AgentGate is how a site states its terms to the agentic economy: once, in writing, in the file agents read first.
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Quiz: how well do you know the policy standard?

1. What settled first in the agent stack: payments or site policy?

2. How many elements does a serious agent policy need?

3. What is actually in dispute between the policy drafts?

4. Where does the policy file live?

5. Why publish before the standard is final?

Frequently asked questions

What is agentic AI?

Agentic AI is AI that acts on goals through tools and other software: researching, comparing, booking and buying with limited human supervision. Its search demand reflects the shift: 'agentic AI' drew about 101,000 US searches a month in 2026 (Ahrefs). As these systems transact across the web, the rules sites publish for them become commercial infrastructure.

What is the agent-access policy standard?

The agent-access policy standard is the emerging convention for sites to declare, in machine-readable form, which AI agents may do what on a site: named agents, permitted and refused actions, limits, data-use terms and a contact. AgentGate's agent-policy.json and the Agent Web Protocol's agent.json (draft v0.2) are the current contenders for the format.

What is AgentGate?

AgentGate is Ingenious AI's agent-access policy standard and generator. It publishes your policy at /.well-known/agent-policy.json, built around policy depth: named agents, explicit actions, limits and terms, with a contact and version date. The aim is a file that survives the standards race because its substance is complete, whichever syntax wins.

How is an agent policy different from robots.txt?

robots.txt answers one crawler question from 1994: may you fetch this path. An agent policy answers the agentic questions: which agents, permitted to do what, under what limits and data-use terms, and who to contact. Keep both, and keep them consistent: agents read both, and so will anyone adjudicating a dispute.

Does publishing a policy replace blocking?

No. Declaration and enforcement are halves of one posture. The policy governs honest agents and documents your terms; blocking (for example with AgentBlock) handles agents that ignore declared terms. Sites that publish and enforce can welcome good agents, condition the rest, and prove their terms when it matters.

Sources: Cloudflare Radar automated-traffic milestone (June 3, 2026) · Agent Web Protocol, agent.json draft v0.2 · Google AP2 and card-network intent systems (October 2026) · Ahrefs keyword data (agentic ai, 101,000/mo US) · Ingenious AI unicorn audit of AgentGate (October 23, 2026).