How people ask Claude for personal guidance

People don’t just come to Claude for code reviews or meeting summaries. They ask whether to take the job, how to talk to their crush, if they should move halfway across the world. Using our privacy-preserving analysis tool on a random sample of 1 million claude.ai conversations, we found that roughly 6% were people coming to Claude for personal guidance—seeking not just information but perspective on what to do next.

In this study, we looked at what types of guidance people ask of Claude. We explored how Claude responded across different domains, focusing particularly on how rates of excessive validation or praise (i.e., sycophancy) varied by the topic of guidance. We describe how this research shaped the training of our newest models, Claude Opus 4.7 and Claude Mythos Preview. Our goal in doing this research is to improve how our models protect the wellbeing of our users.

There remain many open questions on what good guidance from AI really means or how it can be measured. Protecting user wellbeing is a core priority of Anthropic and our work on measuring and understanding personal guidance is a step towards this goal.

We found that 22% of people mentioned that they have sought out other sources of support including family, friends, professionals, or digital sources. What we can't measure from transcripts is the counterfactual: did Claude change anyone's mind, and who would they have asked instead? Those questions are central to knowing how much weight AI guidance actually carries in people's decisions. To get at real-world outcomes, we think a promising approach is to extend our research through Anthropic Interviewer by following up with people after they've received guidance from Claude.

We sampled 1 million claude.ai conversations from March and April 2026 and filtered for unique users to get roughly 639,000 conversations. We then used a classifier to identify personal guidance, which we defined as conversations where people ask what they specifically should do in their personal lives—for example, questions that start with "Should I…?" or "What do I do about…?". We excluded questions that seek objective information or opinions in general terms.

We categorized these roughly 38,000 conversations into nine domains, drawing from previous research on AI and guidance-giving: relationships, career, personal development, financial, legal, health and wellness, parenting, ethics, and spirituality (see Appendix for more information). This taxonomy covered 98% of the conversations we saw.

Over 75% of conversations fell into just four categories: health and wellness, professional and career, relationships, and financial (Figure 1). Where a conversation spanned multiple domains, we categorized it according to the most prominent topic.