TL;DR: Gallās Law says a complex system that works is invariably found to have evolved from a simple system that worked, and that a complex system designed from scratch never works. There are two readā¦
2026
Laws & Disorder #4 ā Gall's Law: Great Systems Are Built From Small Bricks, Not Big Plans
Understanding Is the New Bottleneck ā and Your AI Agent Can Fix It
TL;DR: In AI coding the hard part is no longer writing the code, it is understanding the code the agent wrote well enough to keep steering. Geoffrey Littās framing is that the human job shifts from veā¦
Generate-and-Verify: What P vs NP Teaches Us About AI Reasoning
TL;DR: The defining feature of the complexity class NP is polynomial-time verifiability: a candidate answer is cheap to check. The asymmetry that matters shows up in its hardest members, the NP-compleā¦
Laws & Disorder #3 ā Tesler's Law: You Can't Delete Complexity, Only Choose Who Owns It
TL;DR: Teslerās Law, the conservation of complexity, says a system has an inherent amount of complexity that can be reallocated between owners but not simply deleted, and the boundary condition is thaā¦
Stop Guessing Which Coding Agent to Use ā Benchmark It on Your Own Tasks
TL;DR: Generic coding-agent leaderboards donāt tell you which model or tool fits your work at a budget youāre willing to spend. So I built a small task set that mirrors my real work and ran an open-soā¦
The Quadratic Wall: The Algorithmic Race to Beat O(nĀ²) Attention
TL;DR: Standard self-attention costs on the order of nĀ² in the sequence length n, in both arithmetic and the attention-score memory it materialises. Almost every long-context architecture headline of ā¦
Laws & Disorder #2 ā Hyrum's Law: In the Age of Agents, Who Pays for a Broken API?
TL;DR: Hyrumās Law says that with enough users, every observable behavior of your API becomes something someone depends on, whether you documented it or not. The implementation quietly becomes the intā¦
From Robot Soccer to the Agentic World Cup: Why Games Move AI Forward
š¬ Also available as a blog walkthrough video: a narrated screencast of this post. TL;DR: Twenty years ago, a year-long university project group I was part of built a team of soccer-playing cube robotsā¦
Why AI Tokens Are So Expensive ā and What Actually Makes Them Cheaper
TL;DR: Autoregressive LLM generation has two phases with different bottlenecks: prefill processes input positions in parallel and is usually compute-intensive, while decode produces tokens sequentiallā¦
Laws & Disorder #1 ā Conway's Law: Your Org Chart Is Your Real Architecture (and AI Is Redrawing Both)
š¬ Also available as a blog walkthrough video, a short narrated screencast of this post. TL;DR: Conwayās Law says a systemās structure ends up mirroring the communication structure of the organization ā¦