Writing

Statistics tutorials for people who run evals, notes on things I’ve built, and the occasional essay.

// read in order

Agreement and calibration statistics for LLM judges and human annotators – what survives once chance gets its share.

  1. 1.Understanding Krippendorff’s Alpha
  2. 2.Understanding Cohen’s Kappa
  3. 3.Correlation Is Not Calibration

How sure you are about a benchmark score, and where the next thousand samples should go: uncertainty and experiment design for LLM evals.

  1. 1.Your Benchmark Score Has Error Bars
  2. 2.Paired Deltas: Compare Models on the Questions They Share
  3. 3.Clustered Data and the Sampling Budget
// 12, newest first

2026

  • Agents write most of my Python now, and my own fluency had slipped. Reading and judging code was fine; writing it from a blank file was slower than it used to be.

  • An instrument for finding and drawing strange attractors: 51 chaotic systems rendered live on the GPU, a search that hunts for new ones, and an editor for your own equations.

  • / Judging the Judges, part 3

    You want an LLM judge to replace your human graders, so you run the validation study everyone runs: 200 responses, each scored 1–10 by a human expert and by the judge.

  • / Error Bars for Evals, part 3

    Your agent eval grades 100 conversations, 10 turns each: 1,000 graded rows. The pass rate comes in at 70%, and the naive 95% confidence interval is

  • / Error Bars for Evals, part 2

    Model A scores 390/500 on your benchmark: 78%. Model B scores 400/500: 80%. A two-point gap, and everyone is ready to promote checkpoint B.

  • / Error Bars for Evals, part 1

    Your model scores 78.0% on your team’s 500-question benchmark. A new checkpoint comes back at 79.2%. Merge it?

  • An interactive playground for seeing number theory: 100,000 integers laid out on spiral grids, with classifications, comparisons, and curve-fitting overlays that turn famous theorems into things you…

  • A single-page WebGPU app for exploring escape-time fractals as an instrument rather than a renderer: pan, zoom, switch formulas, and remix colors while the image stays live, all the way down to zooms…

2025

  • / Judging the Judges, part 2

    Your LLM judge and a human reviewer label the same 100 responses as Pass or Fail. They agree on 90. A 90% match rate sounds like the validation can end early.

  • / Judging the Judges, part 1

    You’re building an LLM evaluation pipeline. Four contractors rate 500 model responses as “Good,” “Okay,” or “Bad.” The dashboard shows 87% pairwise agreement, comfortably above the bar your team set…

2023

  • Let’s peer into the future encoded in an AI’s training data. With a bit of prompting, we can bootstrap a journey from today to next year to decades to millenia in the “future” – as a powerful LLM…

  • “Infinite Storyteller” is a generative choose-your-own-adventure, told with state-of-the-art speech synthesis, generative imagery, and presented as a Twitch broadcast in a real-time, 3d game engine.