Treat the announcement as a planning trigger
Prepare a clear statement of your content-use preferences before implementing a future shared control. On 30 October, Google announced plans to support an industry-wide AI-training signal in robots.txt, aiming for 2027. It is not a new setting that this article can truthfully tell you to switch on today.
The operating matrix below is my recommendation for preparing that decision. It supplies no speculative policy-token syntax and does not claim that other providers already interpret the proposal identically.
Understand the relationship Google describes
Google says company-specific controls will continue alongside the proposed shared signal. Its announcement describes how a shared training opt-out would interact with Google-Extended when that provider-specific preference is absent. It also identifies a consequence of explicitly allowing Google-Extended for grounding in Gemini Apps.
That is enough to justify a careful review of intended outcomes. It is not enough to treat training, Search inclusion, agent browsing and Gemini grounding as interchangeable uses. Keep each use named in your working record and follow the documentation for the specific product and control.
Write the business choices before the rules
For each public content category, record what reuse the business intends to permit and why. A general service description, commissioned illustration and licensed research extract may involve different constraints. Where the business lacks the rights to authorise reuse, do not let a broad technical default stand in for that decision.
Then record provider-specific exceptions and their owner. A fictional studio might want broad discovery of its service pages while reserving a decision on training use of original artwork. That scenario illustrates the questions to resolve; it does not prescribe an effective technical configuration for every provider.
Avoid deploying a proposal as if it were a standard
Retain the current, understood configuration while researching an intended change. Identify the release notice and implementation reference that would make the future review actionable. Do not copy an invented token from a generated answer into production robots.txt.
When implementation documentation is available, compare the exact precedence rules against the matrix. Check whether an explicit provider rule overrides a broad preference, which use cases it covers and how the server actually delivers it. Review the resulting configuration with the responsible site owner rather than relying on a file that merely parses.
Keep policy review and technical verification connected
The current crawler-policy article covers the broader decision to separate uses. This follow-up adds a dated preparation step for the announced shared mechanism. Give the review an owner and a trigger tied to confirmed implementation details.
JQ's consulting work can turn an unclear preference into a documented decision and a later verification task. The useful deliverable today is an intelligible set of choices. Any deployment should follow the actual rollout and preserve a recovery copy of the previous rules.
Link Map
Sources and editorial review
Assigned to the 27 October–2 November 2026 editorial series. This edition was prepared and source-checked on 2 November 2026; assigned dates do not imply prior public deployment. Proposed workflows and illustrative examples are JQ AI SYSTEMS editorial analysis, not completed client experiments.
- Google: Supporting a shared AI training control (30 October 2026; primary announcement; planned for 2027).