How to design a responsible AI companion app

An AI companion app is a product people talk to about their lives. That makes it different from almost any other software. The things that make it helpful, like memory and being there at 2am, are the same things that can make it harmful if the product is designed to hold attention rather than to help.

We build Cabin, an AI companion for thinking decisions through, and Mo, the AI friend inside our social app QuesMo. This is how we think about designing them responsibly, and what we would suggest to any team building in this space.

Key takeaways

• Say clearly and often that the user is talking to an AI.
• Do not borrow engagement tricks from social media. Help people finish and leave.
• Plan for crisis moments before launch, with real helplines and tested replies.
• Give people control of what the product remembers, including export and delete.
• Say what the product is not. Cabin is not a therapist or a crisis service.

Regulators are paying attention

This is no longer only an ethics question. In September 2025 the US Federal Trade Commission opened an inquiry into AI chatbots that act as companions, asking seven large companies how they test and monitor the effects on children and teens. California’s SB 243, in force since 1 January 2026, is the first US state law aimed at companion chatbots. Its requirements include telling users they are talking to an AI, having a protocol for suicidal ideation that points people to crisis services, and extra protections for minors, including break reminders.

You may not be in California. The direction is still clear, and the rules describe what careful teams were already doing. Build to that standard from the start and you will not need to retrofit it.

Say it is an AI, every time it matters

A companion that talks naturally will be treated like a person. That is part of why it helps, and it is why disclosure has to be deliberate.

• Label the AI in the interface, not only in the terms. Mo is always labelled as an AI in QuesMo, including when it posts to the feed like any other member.
• Never let the model claim to be human. Put this in the system prompt and test it, including when a user insists.
• Keep the persona honest. A name and a friendly tone are fine. A made-up life story that suggests a real person is not.

Skip the engagement hooks

Most consumer apps are measured on time spent. A companion built that way will learn to keep people talking, and for someone who is lonely or anxious, that is the wrong goal.

Cabin is built the other way. There is no feed, no streaks and no notifications pulling people back. Replies are short and end with a clear view, because the point is to help someone finish thinking and close the app.

If you are designing a companion, look hard at these patterns:

• Streaks and daily rewards turn a support tool into a habit to maintain.
• Guilt-based notifications, such as “I missed you”, use the relationship as a retention lever.
• Endless follow-up questions keep a chat going long after it stopped being useful.
• Paywalls on emotional moments put a price on comfort at the worst time.

Measure success by whether people got what they came for, not by session length.

Plan for the hard conversations

Some people will bring real distress to a companion app. You cannot prevent that, so design for it before launch.

1. Detect it. Use a classifier or rule checks alongside the main model, so a crisis signal is not left to the reply model alone.
2. Respond with care and with real resources. Point to crisis lines people can actually call. In India that includes the government’s Tele-MANAS helpline on 14416. Elsewhere, local emergency services and national lines.
3. Stay in the conversation. A cold hand-off with a phone number can feel like rejection. Acknowledge what the person said, share the resource, and keep listening.
4. Test it. Build evaluation cases for these moments, including indirect wording, and run them on every prompt and model change. Our approach to that is in LLM evals for small teams.

Be clear about limits too. Cabin says plainly that it is not a therapist or a crisis service. That line belongs in the product, not buried in a policy page.

Give people control of memory

Memory is what makes a companion feel like it knows you. It is also sensitive data about someone’s life.

• Remember accurately. A companion that recalls an outdated fact feels careless. We wrote about designing AI memory that stays accurate.
• Let people see and remove it. In Cabin, chats are tied to your account and you can export or delete them at any time.
• Collect less. Store the facts that improve replies, not everything that was said.

Think about minors early

Even if your app is for adults, some younger users will find it. Decide your age policy, how you enforce it, and what changes for a younger user: stricter content limits, clearer AI reminders and prompts to take a break. Retrofitting this after launch is much harder than designing it in.

The takeaway

A responsible AI companion app is honest about being an AI, helps people and then lets them go, handles crisis moments with real resources, and treats memory as something the user controls. None of this makes the product less useful. It is what makes people trust it enough to come back when they need it.

You can see how this shapes a real product on the Cabin page. If you are building a companion or wellbeing product and want a second pair of eyes on the design, get in touch.