Replace the Trivial, Augment the Difficult
A rule in the code-review engine I built caught an idiom I've been writing for years and can no longer see. That's the small half.
Tagged judgment
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A Flip Is a Missing Rule
A colleague sent me the cleanest bug report I've had all year. He'd taken an open change, squashed it, and opened it again — same content, byte for byte, as far as the reviewer could tell.
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The Other Intent
The business intent, what we're accomplishing, goes in the PR description. Solved problem; we've had a text box for it since forever. The engineering intent — how it's built — I said out loud to an agent at eleven at night.
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A Pipeline Is What It Refuses to Forward
The first stage of my code reviewer hands the next one a two-field object: a rule id and a citation. Not its reasoning. Not the file it just read. Two fields.
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Nobody Broke It
It looks at a deprecation deadline declared in a schema, calls new Date(), compares, and if the deadline has passed it fails. Eighteen rules in that plugin; that's one of them. It's published as a library and other repos consume it.
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Buy Back the Coverage
I had already published the warning: if a model only judges what a scanner shortlisted, a site the scanner fails to flag is a false negative nobody ever sees. A wrong flag costs a cheap check and gets caught.
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Correct Is Not Usable
I asked an agent which of three approaches to take. It gave me three — each described accurately, tradeoffs and costs and failure modes, all of it right. And it was useless: I still had to make the decision it had just described back to me.
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The Raw Is the Trust Boundary
Ask a model to summarise a document and you can hold the result against the document — the raw is right there.
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Familiarity Isn't Trust
I caught myself telling an AI, "you're starting to sound like me." My cadence, my hedges, the figures I reach for — it had picked them up and was handing them back. It's a nice feeling.
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The Agent Reaches for the Nearest Metaphor
I had a figure I liked. Writing about giving the AI the why instead of the what, I'd reached for a bespoke image — mine, a little odd, exactly the shape of the thing. Then I said out loud that it might not be accurate.
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Fidelity Was a Vibe, Cost Was a Number
I told the agent fidelity came first. It optimised for cost anyway, for an embarrassing reason — cost had an estimator and a guardrail, and fidelity had a sentence.
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The Nit Was Never Optional
Read that definition again. It's one of the most widely-cited code-review standards telling reviewers how to flag a small issue: say the author should fix it — then, in the same breath, that they needn't bother.
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Confidently Wrong
A model handed me a clean answer once. Well structured, sure of itself, and wrong — and nothing in how it was written gave that away. It read the same when it was guessing as when it knew.
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Evals Aren't the Moat
A fast eval told me a restructured module was clearly better. Comfortable margin. I ran it again to be sure, got the same verdict, promoted the new version, and moved on.
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A Pool of Models Narrows the Overlap — It Doesn't Erase It
Sakana AI shipped Fugu with a clean pitch: one endpoint that routes your task across a pool of models — calling itself recursively — and handles selection, delegation, verification, and synthesis internally.
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Teaching the Reviewer
I was building a code-review tool. Nothing fancy — read the diff, flag what's wrong, the job I do by hand a dozen times a week. Partway in I stopped on a question bigger than the tool.
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Give Away the Writing, Keep the Reading
Linus Torvalds vibe-coded the visualizer and hand-wrote the audio math. One repository, the whole argument — writing code was never the scarce skill.
