Articles · Page 4
Older posts from the archive.
Agency Beats Intelligence: How I Now Hire (And Evaluate Myself)
Raw intelligence is abundant and cheap. The engineers thriving in the AI era are the ones with agency: setting goals, acting under uncertainty, self-correcting. How I changed my interview process to find them.
You Are No Longer a Coder: The Shift from Execution to Direction
I stopped writing most of my own code. What changed, what I delegated to AI, what I found it can't do, and why the hardest part of the transition had nothing to do with technology.
Context Rot: The Silent Performance Killer in Your LLM Application
Your LLM system works great in demos and degrades in production. The culprit is almost never the model. It's what you're feeding it. How to diagnose and fix context rot before it kills your product.
Why Your AI Gets Smarter When You Let It Think Longer
Test-time compute is the most underused lever in production AI right now. What chain-of-thought, best-of-N sampling, and process reward models mean for practitioners, and when to use them instead of grabbing a bigger model.
The Async-First Engineering Team: What Actually Works (And What Doesn't)
I went async-first with my remote engineering team. Productivity went up. Culture took a hit. What changed, what broke, and the specific practices that made it worth it.
What the AI Tool Ecosystem Is Actually Telling You
Tool selection in healthcare AI is a compliance problem, not a productivity one. Most AI tools that sounded great in 2023 are dead or deprecated. The framework I use for betting on the right ones.
What Autonomous Vehicles Taught Me About Multi-Agent AI Design
BAIR researchers discovered that just 5% autonomous vehicle penetration can smooth all highway traffic, with no central coordination. That finding reshapes how I think about building multi-agent AI systems.
The Death of Institutional Memory: Why I'm Building Atlas (And Why It Matters)
Every resignation takes a piece of the organization nobody wrote down. Org charts capture hierarchy, not the relationship networks that keep things running. A different approach to preserving institutional knowledge before it walks out the door.
Vision + Language: How Multimodal LLMs Actually Work (And When to Use Them)
Multimodal LLMs integrate vision through two fundamentally different architectures. Knowing which one you need, and why, shapes every other technical choice in your build.