Separate policy decisions

A website can have different preferences about search discovery, model training, and user-requested access. Write those preferences separately before editing technical controls. A broad instruction to block all AI may unintentionally conflict with a goal of appearing in AI search. Conversely, a visibility initiative does not require treating every automated visitor as trustworthy. Identify the intended audience for public pages and the restrictions needed for private material. Keep authentication as the protection for private content; a crawler preference is not a substitute for access control on confidential pages or customer data.

Map names to documented roles

OpenAI documents separate roles for OAI-SearchBot, GPTBot, and ChatGPT-User. Search and training preferences can be configured independently. Google also distinguishes its Search crawler controls from Google-Extended. Consult the current official documentation before copying a configuration from a blog or old screenshot. Record which policy each rule implements. The useful artifact is a small table of user agent, intended purpose, current rule, and policy owner. This lets future engineers understand why an exception exists instead of deleting it during a cleanup or assuming all bots perform the same task.

Check the full delivery path

A permissive robots.txt file does not prove a request can retrieve content. Review CDN rules, bot challenges, application authorization, redirects, and server responses. Test public pages through approved inspection methods and examine logs where available. Verify bot identity using the provider's published method rather than trusting a user-agent string alone. Keep the change narrow: public documentation may need different treatment from login endpoints. Do not disable security controls across an entire domain merely to resolve one blocked content route, and preserve evidence of the specific failure before editing rules.

Work through a controlled example

Hypothetical example: a software company wants public tutorials available in search while declining training use through the relevant provider controls. It records those choices, updates the appropriate crawler-specific directives, and checks the tutorial response and CDN configuration. It does not expose its account pages. The company then watches for subsequent fetches and checks public accessibility. A successful fetch confirms access, not selection in an answer. It therefore reports the technical change as resolved while continuing separate observation of search results and citations over time.

Maintain the decision

Keep a dated configuration record, official documentation links, and a named owner. Review rules after domain migrations, firewall changes, and major hosting updates. Do not change multiple unrelated controls at once if doing so would make troubleshooting difficult. Record before-and-after response status and whether the main content was available. This approach gives security and marketing teams a shared evidence trail. The end state is deliberate access matching the publisher's policy, not a promise that allowing one crawler will produce rankings, citations, or traffic on a guaranteed schedule. Test representative routes after each policy update, including pages served through different application or caching layers.

PUT IT TO WORK

Understand search, training, and user-triggered fetches before changing crawler access rules.

Sources & further reading

Official documentation informs this guide. Examples are illustrative, and product interfaces or limits can change.

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