Untilt

From agile to neuroleadership

For years I taught agile-method workshops inside my company. The short frame wasn’t enough, so I widened it — a bit of constructivism to explain how people learn, a bit of Palo Alto to explain how people communicate. After enough questions from trainees, I ran into mine: how does a brain that decides actually work?

That’s what led me to Foundations in NeuroLeadership at the NeuroLeadership Institute. A course built for managers, but one that takes the science seriously — some neurobiology, a lot of bias literature, and a single thread: when you understand the brain’s shortcuts, you decide a little better.

What the literature did

The main thing the course left me with isn’t a method. It’s a shift of angle. Biases aren’t bugs; they’re the trade-offs a brain makes to function with too much information and too little time. They’re adaptive — except when the context that built them no longer matches the one you’re using them in.

Reading that is easy. Remembering it at the moment you’d need it — a hire, an investment call, a career move — is something else.

Why a tool

Most decisions don’t wait for you to crack open a textbook. They arrive on a Tuesday at 2pm, in a meeting room or in front of a screen. If bias science is going to be useful outside the classroom, it has to show up then: in two clicks, no account, no tracking.

That’s what Untilt tries to be. Not a coach, not a book, not a personality quiz. A map you consult just before.

What’s inside

50 cognitive biases, 37 decision types, in English and French. Two ways in:

  • Manual. You describe the situation, pick the decision type, and the app surfaces the biases most likely to apply — each with a description, scientific sources, and a few strategies for stepping back from it.
  • AI-guided. You describe the situation in free language; a model call classifies it and proposes the likely biases — which then drop into the same mechanic as the manual path.

No account. No tracking cookies. The full knowledge base is bundled inside the app, with bilingual full-text search and references to the source papers for anyone who wants to check the work.

P.S.

The map keeps growing. The bias × decision matrix was drafted mostly by Claude, from the scientific literature and the materials of my course; it expands in batches, whenever my Claude Max plan has room. It’s a build detail, not the point — but it’s why the numbers feel both precise and provisional.

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