AI is on track to understand the human mind better than we do. That makes it the largest threat the mind has faced, and at the same time the first instrument that can measure, upgrade, and defend it at depth.
MindTech works the interface where the human mind meets the artificial one. We build the instruments to measure a mind, the tools to upgrade it, and the defences to protect it. Because the whole of it runs on AI, we start one layer down. We test and harden the AI first, so the intelligence trusted with a mind cannot easily be turned against it.
We work both, because defending the first while ignoring the second does not hold. Most teams in this space work one side. A wellness app is easy to build. Standing behind the AI that does the work is the harder part, and it is where we begin.
Before an AI touches a mind, it earns the right. Each agent is tested under pressure and hardened so it holds up under manipulation and coercion, and stays stable after a model change.
A short guided conversation. Voice where possible, since text loses most of the diagnostic signal.
The belief map, ordered by depth, anchored to validated psychology. It updates from use, with no re-mapping session.
Pick a replacement program from a consented, anonymised library and run it daily until the map shows the change.
Play against known tactics. The same map that guides the upgrade points to where a person is most easily moved.
Why it is built this way. AI companions tend to fail in one of three ways. The person hands over their thinking and gets weaker. The model flatters instead of correcting. Or a system that has learned a person is used to steer them. So the test we hold ourselves to is whether a mind is stronger with the system than without it, and the map is how we check. Mind data stays with the person, and inference runs locally wherever the platform allows it.
Joshua Tanner, medical doctor and AI systems engineer. Trained at Stanford in medicine and AI, where he was Co-Executive Director of HealthAI and founded the graduate course Deep Learning in Medicine. Eight years in AI, with fifteen or more healthcare AI projects across ten countries, and agent-verification work now in production with a global advertising group and a UK government department.
The beta is narrow and reviewed by hand. Tell me what you are working on and I will send you the part that is yours.