Hi friend,

Solving hard problems often requires new ways of working.

In 1939, Howard Florey was trying to figure out how to produce enough Penicillin to run a trial in humans. It was a scientific and manufacturing question. But Florey’s genius lay in realising he needed to innovate in how he was approaching finding an answer. He recruited an interdisciplinary team to his lab at Oxford and had them work simultaneously on their respective areas of expertise — something that wasn’t really done at the time. This process soon provided an answer to their Penicillin production problem allowing them to make enough of the substance to test it in a human.

A few decades later, NASA were trying to put a man on the moon. To do so, they had to invent modern project management just to coordinate the 400,000 people working on the problem.

In 2026, the field of mental health faces another hard question: Can we use Artificial Intelligence to improve people’s mental health?

There are many technical and clinical aspects to this question that we still don’t understand. Teams are building on a rapidly changing frontier technology, the evidence base is still emerging, the stakes are high and there are multiple success criteria to consider. Because of this, the old product playbook no longer works. Leaders realise they need to redefine how their teams tackle this question.

Over the last few weeks I’ve been speaking with product and clinical leaders from organisations like Spring Health, Headspace, Grow Therapy and Slingshot to understand more about how they approach this problem.

In this edition of The Hemingway Report, I share seven insights into how these leading organisations are redesigning their teams and processes to build mental health AI.

Let’s get into it.