If you’re an organization leader seeking to generate real-world value with AI, particularly in healthcare, I’d love to help. My experience includes:

• 9 years training as a doctor, 7 years building AI products. I’ve navigated the shift from traditional ML approaches to LLM-powered systems and helped build the playbook for healthcare.
• building evaluation systems that unlock reliable and safe AI, supporting AI’s use in mission-critical industries like healthcare and enabling companies to prove performance for regulatory compliance
• setting up teams, tools and processes to incorporate domain expertise into AI systems

I can guide you through the challenges of AI product development, ensuring your team is set up to move fast, leverage new technology effectively and differentiate you from competitors. I see three critical challenges holding healthcare AI teams back - and I’ve helped companies solve each one.

Building AI products today requires a fundamentally different approach

The arrival of LLMs has created unprecedented opportunities in healthcare AI - but also new challenges that many teams are struggling to fully capitalize upon.

The three critical challenges I see holding teams back are:

1. The MVP-to-production chasm

We’ve seen how easy it is to make an impressive demo - and how hard it is to deploy something that provides real-world value. In mission-critical industries like healthcare, the bar needs to be high.

I help teams design pragmatic evaluations, tailored to their stage of product development, to enable targeted iteration, achieve safe and effective performance and then maintain it through robust post-deployment monitoring. I’ve built systems that have achieved state-of-the-art performance and delighted healthcare users.

2. Domain expertise matters more than ever

With LLMs, words are the new code. Your prompts, instructions, and evaluation criteria are now core parts of your system - and you need a way to systematically bake in the insights from those who deeply understand the domain.

Domain experts and engineers often speak different languages - and traditional software development workflows weren’t designed for this new collaborative paradigm.

I help teams bridge this gap. As a doctor by background who’s spent years building AI systems, I understand both worlds. I’ve designed workflows, tools and processes to convert domain expertise into domain expert LLM applications.

3. Companies are building with yesterday’s playbook

The approach that made sense in the “pre-LLM” era doesn’t work any more. Yet that was only 3 years ago and many companies haven’t caught up.

LLM-powered products require new skillsets and new approaches: context engineering, workflow decomposition and evaluation systems - rather than feature engineering, model architecture design and optimizing for model accuracy.

I’ve lived through this evolution. I operated in this ‘pre-LLM’ world; I built state-of-the-art deep learning algorithms and published the first study to compare AI and doctors. I then spent 2 years building LLM-powered products for healthcare admin at a Sequoia-backed start-up.

I help teams build in an LLM-native way; in how they architect their applications and write code, in how they hire and train their staff and in their operational processes.

Let’s discuss your AI challenges

If you’d like to explore working together, book a discovery call below:

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