The Cloud Codex — field notes on building with AI agents
$ cat ./codex/README.md
Field notes on building with AI agents.
The harness around the model, what the tokens actually cost, and the platform engineering that keeps it production-grade.
105 essays 2026 vol.01 ● shipping weekly
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Instrument Like a Learning Scientist
The most valuable thing the Dartmouth team built wasn't the grader. It was the fact that they could answer "did completing this lesson's quiz correlate with doing better on the exam?" — per…
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$ ls -t ./essays
[ 01 ]
The Biggest Effect Size Was the Boring Feature
[ 02 ]
The Grader Was Right and the Students Quit Anyway
[ 03 ]
Students Are Adversaries: Red-Teaming an LLM Grader
[ 04 ]
Your LLM Judge Needs a Test Suite
[ 05 ]
Grading Written Answers with an LLM, Properly
[ 06 ]
The AI Tutor Everyone Builds Is the One Students Ignore
[ 07 ]
Build a Self-Improving Agent Harness in an Afternoon
[ 08 ]
Maintainability Is the Last Mile, and It Doesn't Benchmark Away
[ 09 ]
OpenTelemetry Tells You What Your Agent Did. Not Whether It Was OK.
[ 10 ]
An Engineer Costs $250K. Their Tokens Cost $20K. That Math Is a Trap.
[ 11 ]
How to Run an Agent Loop Without Burning Your Token Budget
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