What Is the Difference Between a Training Crawler and an Answer Crawler?

Are all the AI bots hitting your site doing the same thing?

No, and treating them as one category is the reason most AI crawler decisions are made badly. The major vendors run several distinct robots with different jobs, and the difference between a bot that trains a model and a bot that fetches your page to answer somebody's question is the difference between giving your content away and getting cited.

I see site owners block all of them in one line, or allow all of them without a thought, and both choices are usually made without knowing that the choices are separable. They are separable, and the vendors document exactly how.

So here is what each type actually does, in the vendors' own words, and what I would do about it.

What does a training crawler actually do?

It collects content that may be used to build the model itself. OpenAI says GPTBot, with the user agent token GPTBot, is used to crawl content that may be used in training its generative AI foundation models. Anthropic says ClaudeBot collects web content that could potentially contribute to their training.

The important property of a training crawl is that it is not connected to any individual question or any individual reader. Your page goes into a process, and whatever influence it has on future answers is diffuse and untraceable. There is no citation, no link, and no visit at the other end of it.

OpenAI is explicit about what refusing means. It says disallowing GPTBot indicates a site's content should not be used in training generative AI foundation models. That is a clean, stated consequence, which is more than most platform decisions give you.

What does an answer crawler do instead?

It indexes your content so it can be surfaced when somebody searches. OpenAI describes OAI-SearchBot, token OAI-SearchBot, as used to surface websites in search results in ChatGPT's search features. Anthropic describes Claude-SearchBot as navigating the web to improve search result quality, analysing content to enhance the relevance and accuracy of search responses.

This is the bot that has something to offer you. If your content is not available to it, you are not a candidate for the results it produces, and the visibility work that most businesses now care about depends on exactly this category of access. Blocking it is a decision to be absent.

OpenAI goes as far as recommending you allow it. That recommendation is self-interested, obviously, but it is also aligned with yours if you want to appear in those results. The honest framing is that training and answering are different trades, and only one of them offers you something back.

What about the bot that fetches a page because a user asked?

That is a third category and it behaves differently again. OpenAI describes ChatGPT-User, token ChatGPT-User, as used for certain user actions in ChatGPT and Custom GPTs. Anthropic describes Claude-User as supporting Claude users, saying that when individuals ask questions of Claude, it may access websites using a Claude-User agent.

These fetches are the closest thing to a real visitor in the whole taxonomy. Somebody has asked a question, the assistant is going to your page specifically, and what it finds there shapes an answer being read right now by a person who was already interested. This is the moment your page content matters most.

OpenAI also runs OAI-AdsBot, token OAI-AdsBot, which it describes as used to validate the safety of web pages submitted as ads on ChatGPT, visiting only submitted ad pages. It is worth knowing it exists so you do not mistake it for something else in your logs.

Do robots.txt rules apply to all of them equally?

No, and this is the single most important thing in this article. OpenAI says that because ChatGPT-User actions are initiated by a user, robots.txt rules may not apply. Anthropic takes a different position, saying that disabling Claude-User on your site prevents its system from retrieving your content in response to a user query.

Read those two sentences next to each other. Two major vendors, the same category of user-initiated fetch, and opposite answers about whether your robots.txt governs it. Anyone telling you there is a single correct AI crawler policy has not read both pages.

Anthropic is clear that its bots respect do-not-crawl signals by honouring industry standard directives in robots.txt, and it also supports the non-standard Crawl-delay extension, giving the example of Crawl-delay set to one for ClaudeBot. So the levers exist, they just do not all behave identically across vendors.

How quickly does a robots.txt change take effect?

Not instantly. OpenAI notes that it can take around 24 hours from a site's robots.txt update for its systems to adjust. That is a short delay in absolute terms and a meaningful one if you are changing your policy in response to something urgent.

The practical implication is that robots.txt is a policy instrument rather than an emergency control. If you need something to stop being accessible immediately, robots.txt is not the tool, and you should be thinking about access control at the server instead.

It also means testing is slower than you expect. Change the file, wait, then check your logs, rather than changing the file and concluding within the hour that it did not work. Both vendors publish IP ranges for their bots as JSON files, which gives you a way to confirm what you are actually seeing rather than trusting a user agent string that anyone can set.

Should you block training and allow answering?

For most businesses, yes, and it is a defensible default rather than an obvious one. Allowing the search and user-initiated bots keeps you eligible to be found and cited. Blocking the training crawler withholds the use that returns nothing to you. The two decisions genuinely are independent.

The argument against it is that training influences what models know about your category and your brand in the long run, and being absent from that is its own kind of invisibility. I find that argument weaker than it sounds, because the effect is unmeasurable and you cannot tell whether it worked, but it is not a stupid position.

What I would not do is make the decision by copying somebody's robots.txt from a blog post. The vendors change their bots, the tokens change, and a file written two years ago is now governing robots that did not exist when it was written. If you are weighing this up, the case for and against blocking AI search is worth reading properly before you edit anything.

What does my own robots.txt do, and why?

It allows all of them explicitly. My file has a section commented as AI answer engines and training crawlers, explicitly welcomed, listing GPTBot, OAI-SearchBot, ChatGPT-User, PerplexityBot, ClaudeBot, anthropic-ai, Google-Extended and Applebot-Extended, each with its own Allow directive rather than a single blanket rule at the top.

That is a deliberate choice for my situation rather than a recommendation for yours. My business is visibility work, the whole point of the archive is that people find it, and a published article is already public. The training trade that other businesses reasonably object to costs me very little.

A company whose content is its product should reach a different conclusion, and I would defend them doing so. The point is that the file should reflect a decision somebody actually made, with the training and answering lines considered separately, rather than a default nobody has looked at since the site launched.

How does this fit with llms.txt and everything else?

robots.txt is the access layer and it is the one the vendors document and honour. Everything else in this space, including llms.txt and how to set it up, sits on top of that and is about helping a system that is already allowed in to understand what it found.

Keep the two jobs separate in your head. Access control decides whether a bot may fetch the page at all, and it is enforced. Guidance files describe your content for whoever chooses to read them, and adoption varies. Confusing the two produces a lot of wasted effort on files that nothing is obliged to obey.

Neither file tells you whether any of this is working. That requires looking at your own server logs and at how you actually appear in AI answers, which is a separate measurement problem and the subject of measuring AI visibility for your brand.

What should you do next?

Open your robots.txt and check which of these tokens appear in it. GPTBot, OAI-SearchBot, OAI-AdsBot, ChatGPT-User, ClaudeBot, Claude-User and Claude-SearchBot. If your file predates some of them, it is not expressing a policy about them at all, it is simply silent, and silence resolves differently for each vendor.

Then decide the two questions separately and write the answers down. Do you want your content used in training, and do you want to be eligible to appear in AI search results and user-initiated fetches. Those are different questions with different consequences, and one line in a file cannot answer both well.

Finally, read the vendor pages themselves rather than a summary, including this one, because the differences between them are exactly the sort of detail that summaries flatten. If you want help turning that into a file that matches what your business actually wants, reach out.