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Chris Lovejoy

Doctor turned ML Engineer/Founder

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Latest posts

Why enterprise tech stacks aren't ready for AI agents — and the primitives that can unlock them

I gave this talk at the 2026 AI Engineer World’s Fair in San Francisco on 2nd July 2026. (Last year, I spoke at the same conference about building a domain-native LLM application.) Recording I will add link once available. Slides Downloadable as a PDF here.

Why your startup equity offer is worth less than you think - and what to do about it

Okay, so you’ve been offered equity: 80 thousand options, with a pre-money valuation of $6M, a double trigger clause, a strike price of $0.60 and a 90-day post-termination exercise window. So… Is that good? With salary, its value is immediate and obvious: you can benchmark the amount against peers and ultimately see it land in your bank account every month. Equity is murkier: What needs to ha...

The Domain-Native AI Organization: How to Leverage Domain Expertise

I gave a talk at the first European AI Engineer conference on 10th April 2026. Recording Slides Downloadable as a PDF here.

The Sour Lesson: A Guide to Building AGI-Pilled Products

With the current rate of AI progress, every AI product builder must confront an uncomfortable question: How should I build my product when my approach could become obsolete with the next model release? You need to serve customers today so you have to ship something using current capabilities - but those capabilities will change. Build too specifically around those limitations and you create te...

The new AI playbook: why LLM-native beats traditional ML in verticals

The emergence of large language models like chatGPT and Claude has fundamentally changed how value can be created in vertical industries using AI. But with this technology comes a new rulebook. Previous AI approaches were characterized by using datasets to train models for specific use cases and then deploying them within existing workflows. With LLM-native approaches, the focus is on stitchin...