Articles · Page 4
Older posts from the archive.

You Are No Longer a Coder: The Shift from Execution to Direction
After 12 years of building systems by hand, I stopped writing most of my own code. Here is what changed, what I delegated to AI, what I found it cannot 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. Here's 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. Here is what chain-of-thought, best-of-N sampling, and process reward models actually mean for practitioners building real products — and when to use them vs. just 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. Here's the honest accounting of what changed, what broke, and the specific practices that made it worth it.

What the AI Tool Ecosystem Is Actually Telling You
After wasting months on AI tools that sounded great and died within a year, I started reading the ecosystem differently. Here is the framework I use now — and why tool selection in healthcare AI is a compliance problem, not just a productivity one.

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 quietly reshapes how I think about building multi-agent AI systems.
The Death of Institutional Memory: Why I'm Building Atlas (And Why It Matters)
After watching countless organizations hemorrhage critical knowledge with every resignation, I realized we need a fundamentally different approach to capturing and preserving the networks of relationships that actually run businesses.

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 — is the decision that shapes every other technical choice in your build.

The Self-Healing Stack: What AI-Native Infrastructure Actually Means
The AI Cloud vision — where infrastructure monitors, optimizes, and repairs itself — is compelling. Some of it exists today. Most of it doesn't yet. Here's an honest breakdown of what self-healing infrastructure looks like in practice — and what engineers should actually be doing to prepare.







