Product teams ask Claude to reason about users, but single answers conceal variance. Minds runs your Claude prompts against structured synthetic segments to reveal how opinions split.
When you ask Claude how a specific user segment will react to a product decision, you receive a clear, articulate response. The reasoning is well structured. The tone is confident. However, that single answer represents a synthetic average that hides disagreement within the group.
If four out of ten potential users would reject your change for conflicting reasons, a standard Claude thread merges them into a single compromise persona. Because Claude writes with high fluency, unverified assumptions become harder to notice rather than easier. When slight adjustments to your prompt phrasing produce completely different conclusions, it is difficult to know which version to trust. Minds takes the questions you are already asking Claude and evaluates them across a structured synthetic segment to expose the spread of opinion.
Claude is designed to generate coherent, helpful answers to the prompt provided. When you ask it to evaluate an artifact from the perspective of an audience, it constructs an archetype. That archetype blends conflicting motivations into one smooth narrative.
Real customer segments do not share a single opinion. Budget holders focus on annual costs and compliance, while daily operators focus on interface speed and workflow disruption. When Claude resolves these tensions in one answer, it chooses an arbitrary path through the problem. You lose visibility into edge cases and friction points. If you rewrite your question with slightly different emphasis, Claude adopts a different perspective and presents it with equal confidence. You end up comparing polished outputs without knowing what drove the difference.
Minds connects directly to your Claude workflow. Instead of asking one model instance to simulate an entire group, Minds runs your prompt across multiple distinct profiles within a defined cohort.
Each profile evaluates your question independently based on its own role, technical constraints, and operating priorities. The output is not a consensus essay. It is a distribution of reactions. You see where reactions cluster, where confusion arises, and which constraints trigger strong pushback. If part of the simulated cohort rejects a proposal due to integration overhead, that objection appears as an isolated cluster rather than disappearing into a balanced summary.
A structured audience gives you a distribution instead of an average. It is still simulation, and consequential decisions still need real people.
Synthetic runs help you stress-test your thinking, find unstated assumptions, and prepare sharper questions for customer discovery. They do not provide conversion metrics or statistical proof. Synthetic profiles do not manage real budgets, experience real business risk, or navigate company politics. Use Minds to locate blind spots in your Claude questions, not to replace research with real users.
When a simulation finishes, examine the disagreement rather than searching for an overall score. Identify the profiles that rejected the premise of your question entirely. An assumption in your prompt often becomes visible only when several simulated users point out that the scenario does not match their operating environment.
Compare these individual responses with the initial reply you received in Claude. You will often find that the single answer Claude generated earlier made an implicit choice on a trade-off that divides real users in practice.
We are planning to deprecate our manual CSV export function and require all reporting exports to go through a scheduled webhook or an API connection. You are a data operations lead at a mid-market logistics company with fifteen non-technical team members who consume these reports weekly. How does this change affect your weekly operations, what manual workarounds would you need to establish, and under what conditions would this lead you to evaluate alternative software?
Frequently asked questions
Why run prompts through Minds if Claude already answers them?
Claude gives one unified answer per prompt. That answer blends diverse user opinions into an average. Minds runs the prompt across individual simulated profiles so you can see where people disagree.
Does this integration require writing new prompts from scratch?
No. You import the exact questions you are already asking Claude into Minds using the connector.
Can Minds tell me if my feature will succeed in market?
No. Minds only shows the distribution of responses within the simulated audience you configured. It does not measure population behaviour or predict market conversion.
How does Minds connect to my existing Claude setup?
Claude has a live one-click connector. You connect it in Settings and import your prompts directly into a study.
Why do different runs of the same prompt show different viewpoints?
Minds distributes the prompt to distinct synthetic profiles with varying constraints, priorities, and workflows, rather than asking a single model instance to produce a compromise summary.
