Writing
All posts
Old Ideas, New Machines
The same patterns keep reappearing in new disguises — branch prediction becomes speculative decoding, virtual memory becomes PagedAttention.
My Two Favorite & Greatest Rebrands
Japan and Darius Rucker don't have much in common, but both pulled off some of the most remarkable rebrands in modern history.
Agent-Aware Snapshots with Daytona
A look at using agent-aware snapshots to create and restore the development environments AI agents need more efficiently.
Kubernetes Is the Wrong Primitive for Diverse Workloads
Kubernetes excels at scaling stable services, but short-lived AI workloads often need many distinct, prepared environments that can be launched on demand.
Why I Am Studying Classic Reinforcement Learning Now
Modern AI is rediscovering old reinforcement learning problems: reward design, credit assignment, exploration, evaluation, and learning from feedback.
The Hidden Infrastructure Tax in Coding-Agent RL
Coding-agent RL depends on real software environments, so provisioning and command latency can become a significant part of training cost and rollout throughput.
GRPO: Learning From the Other Answers in the Room
A simple breakdown of GRPO, a reinforcement learning method that removes the need for a separate value model. Full of analogies, and images to make the concept more approachable.
What Longer-Timeline Intuitions About RL Progress Missed
An argument for why AI progress did not slow in the RL regime as much as some longer-timeline intuitions expected.
PPO Explain for beginners
A beginner-friendly breakdown of Proximal Policy Optimization — the RL algorithm that turned raw base models into useful AI assistants.
Hello World
My first blog post — a quick intro to what I'll be writing about.