Lessons on applying AI in vertical industries
I recently went to the AI Engineer World’s Fair in San Francisco and took away a lot of lessons about how the industry is approaching vertical artificial intelligence, vertical AI agents, and the f...
Chris Lovejoy
About Me
Hi, I'm Chris Lovejoy 👋 I build AI products for complex, domain-specific verticals like healthcare and life sciences.
Currently: Member of Technical Staff at Anthropic.
Previously: founding team at Anterior (healthcare LLM startup backed by Sequoia/NEA), medical doctor, academic researcher, and ML engineer. (I describe that journey here).
I write about building vertical AI products that generate real-world value. I previously wrote a book about learning medicine and lectured on AI for healthcare.
Popular
- Own your vertical: A playbook for building a domain-native LLM application (100k+ views)
- Machine Learning for Healthcare video series (50k+ views)
- The Academic Knowledge Management (AKM) system that 10x'd my research productivity
- The Truth Is In The Title? Video Title Generation as a novel training objective for video summarisation
- Mission-Critical Evals at Scale: Learnings from 100,000 medical decisions
- AI versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies (1,000+ citations)
- I created my own YouTube algorithm (to stop me wasting time) (100k+ views)
Recent Essays
7 eval mistakes that can kill your AI product (and how to avoid them)
When done right, evals can be the backbone of product development, enabling teams to build great products that users love. Done wrong, evals can become a massive time sync that never add any real v...
Own your vertical: A playbook for building a domain-native LLM application
Here’s a talk I gave for the AI Engineer World Fair (4th June 2025). Recording Summary Slides Downloadable as a PDF here.
Who to hire first for your LLM product team? 3 principles for building LLM product teams
Team is the single biggest predictor of success – but there’s no ‘playbook’ yet for what teams building LLM products should look like. At Anterior, we’ve gone from first mover in the health insura...
My winding, unplanned path from Doctor to AI Startups (and all the steps in between)
In 2020, as the peak from the first wave of COVID subsided in the UK, I worked my final shift as a medical doctor. Since then, I’ve worked as a data scientist, founded a VC-backed start-up, been an...
Mission-Critical Evals at Scale: Learnings from 100,000 medical decisions
Here’s a talk I gave for the AI Engineer Summit (22nd Feb 2025). Recording Summary Slides Downloadable as a PDF here.
Relying only on offline evals is playing with fire: why you must evaluate on live production data
So you’ve followed the rule book: you’ve created your labelled datasets, used them to iterate against as you improve your LLM product, and you’re going live with early customers. Metrics look good,...
I fired my personal coach and built one with AI - it knows me better, gives great advice and saves me $$$ every month
Last year, I tested out building an AI performance coach to replace my human one. It’s much better so I cancelled my human one altogether. It knows me better, gives great advice and improves itself...
5 ways to reduce the risk and impact of hallucinations in your LLM product
I’ve been building apps powered by LLMs for the past 2 years - mostly in healthcare where the stakes are high. The single most common question I get is: “So.. how do you deal with hallucinatio...
Learning AI - where to start in 2024
An academic medical doctor recently asked me: “I want to learn about AI - should I learn to code? should I learn maths?” My response was: It depends what type of ML you want to do. I find it help...