Articles · Page 2
Older posts from the archive.
The Principal IC Playbook Nobody Shares With You
Reaching principal is the first rung of a new ladder, not the last rung of the old one. What nobody told me about the ownership-autonomy paradox, how leverage works at this level, and the charter model I wish I'd had from day one.
The ESM Mess: JavaScript's Module System Is Still Broken and Here's Why
ES Modules have been the supposed future of JavaScript for nine years. Only 9-27% of the ecosystem has adopted them. What's really going on, and how to survive until the ecosystem commits.
The Three Things Exceptional Engineering Leaders Do (And the One They Stop Doing)
Most engineering leaders excel at one of three pillars and quietly fail at the other two. The three are: providing direction, removing obstacles, foreseeing change. What it takes to build strength across all three.
The Open-Weight LLM Landscape in 2026: What Engineers Actually Need to Know
The open-weight ecosystem has matured faster than most engineers realize. MoE proliferation, hybrid attention, and extended context windows are changing what's deployable on-premise. That matters more than ever for healthcare AI.
Software 2.0 Is Here and It Changed How I Think About Programming
In 2017, Andrej Karpathy argued that neural networks would replace explicit logic as the dominant programming paradigm. Nine years later, that prediction has fully landed. The implications for how we build software are bigger than most engineers want to acknowledge.
Three Ways to Know If Your Career Is Actually Growing
Normal career metrics: title, pay, team size. They tell you how you're doing relative to others. They don't tell you whether you're growing. Three metrics that do.
RAG Isn't Dead. You're Just Using It Wrong.
The 'RAG is dead' narrative is wrong, but it's wrong in an interesting way. What kills LLM context quality in production, and what to do about it.
Fine-Tuning a 70B Model on a Consumer GPU: The Q-LoRA Practical Guide
Q-LoRA + SFTTrainer + Flash Attention v2 means you can fine-tune a 70B parameter model on 24GB of VRAM. What that looks like end-to-end, what it costs in quality, and when to just use the API instead.
Time vs. Timing: The Career Framework I Wish I Had Earlier
I've made bets that paid off because of timing and bets that paid off because of compounding. Confusing the two is how careers stall.