Beyond the Backlog
Product Management | AI & Legal Tech Insights
Distilled learnings from my career as a product manager—real-world case studies, frameworks, and the hard-earned lessons behind what worked (and what didn't). Focused on building AI-powered legal tech, product strategy, and leading teams.
Leave Like You're Coming Back
Last week I wrote about what 4.5 years at Ontra taught me. This is the companion piece, about deciding to leave and how to leave well once you do. The decision to leave was one I went back and forth on a lot. I had seen Ontra through much
The Lessons That Only Show Up If You Stay
Four and a half years ago, I joined a Series B startup called Ontra as an associate product manager. My last day is this Friday. Over the last 4 years and change, I've learned a lot and seen a company change from scrappy startup into a scaled legal
Vector Databases, Embeddings, and RAG: Giving LLMs the Context They're Missing
In a prior post, we broke down how large language models actually work — tokenization, embeddings, transformers, context windows, and hallucinations. If you haven't read that one yet, go do that first. This builds directly on it. Here's the key takeaway from that post: LLMs
What Makes an AI Agent an Agent (And When It's Just a Chatbot in a Trench Coat)
Beyond the Backlog, AI Deep Dive, Part 3 In the first post, we cracked open deep learning: nodes, layers, weights, backpropagation, and the fundamental machinery that lets neural networks learn from data. In the second, we zoomed into large language models: transformers, attention, context windows, and the mechanisms that make
How LLMs Actually Work: A Product Leader's Guide to the Tech Behind the Chat Box
In the last post, we cracked open the black box of neural networks. Nodes, layers, weights, backpropagation — the fundamental machinery that powers deep learning. If you missed it, go read that first. Everything in this post builds on that foundation. An LLM is a neural network — a very
Deep Learning Demystified: What Product People Actually Need to Know About Neural Networks
Every product leader I know is making decisions about AI features right now: which capabilities to build, where to invest, and how to evaluate what's real versus what's hype. And yet, I don't think the vast majority of product people know what's
The Changing Role of Product in the Age of AI
A few weeks ago, a PM friend of mine was prepping for an interview at a well-known growth-stage company. We were chatting about the interview process and how it's changed since they were last looking for a new role, and one set of questions in particular was different.
The Agentic Future Demands More Than Agents
There's enormous pressure right now to go agentic. Every product leader I talk to is feeling it — from their boards, their customers, their competitors, and honestly, from themselves. The promise is real. Agentic AI can automate complex workflows, reduce toil, and unlock value that wasn't
The Making of a Manager: What Early Product Leaders Can Learn from Julie Zhuo
I just finished Julie Zhuo's "The Making of a Manager," and while it's technically a book about general management, I found myself dog-earing pages that speak directly to the challenges I face as a product leader early in my management journey. Zhuo's
Your AI Strategy Has a Blind Spot: Internal Adoption
Most product leaders I talk to are obsessed with how to build AI into their products. What features to ship. What models to use. How to differentiate. Those are the right questions — but they're incomplete. The question that gets far less attention: how is your organization actually
The Dream Machine: What a 1960s Computer Visionary Can Teach Today's Product Managers
I just finished "The Dream Machine" by M. Mitchell Waldrop, and I can't stop thinking about J.C.R. Licklider. The book is a biography of Licklider and the history of the early computing revolution. "Lick" (as everyone called him) was a psychologist who
Beyond the Chat Box: Designing AI Experiences That Actually Fit How People Work
This is the third post in my series recapping takeaways from Reforge's AI Strategy course. Part 1 covered how AI accelerates PMF collapse; Part 2 introduced the AI Maker Matrix for user segmentation. This week, I'm diving into something that's been gnawing at me
My Favorite Products of 2025
I'm taking a break this week from my takeaways from the Reforge AI Strategy course to do my EOY breakdown of products I've loved. Every year I find myself quietly building a "favorites list" in my head—the products that actually changed how
AI Maker Matrix: A Framework for AI Product Segmentation
Last time, I kicked off this series on my takeaways from Reforge's AI Strategy course by exploring how AI accelerates PMF collapse. This week, I'm going deeper: who exactly are you building for, and why does getting that wrong doom so many AI products? The framework
Product-Market Fit on Fast-Forward: How AI Compresses the Incumbent Advantage
I’m working my way through Reforge’s AI Strategy course and so far it‘s sparked a lot of great thoughts! In particular, it’s been a forcing function to pressure-test my own instincts about how to build AI products and modify my approach to