automation

Most projects pin dependency versions to avoid breakage. We automated the opposite: daily upgrades with automatic rollback.

I ran an autonomous agent loop overnight — 43 waves, ~270 dispatches, ~250 vault files produced. Here's what I learned about building systems that work while you sleep.

In AI agent systems, execution commoditizes. Research commoditizes. Coordination commoditizes. Taste — the ability to forecast what will matter — is the bottleneck that doesn't automate away.

Humans handle about three layers of abstraction before working memory fills up. Skills, rules, and frameworks exist to flatten the fourth layer into something you can hold.

Most people use AI tokens when they have a task. The better model: you have tokens, find the best task. It changes everything.

Event-driven hooks in AI coding tools aren't just for linting — they're programmable triggers for life routines, habits, and systems.

When building automation around a third-party app, the first question to answer is: what's the one thing this app does that nothing else can replicate? That feature becomes the tax you pay on everything else.

The most sophisticated solution to a problem is usually a sign you haven't found the right abstraction yet.

Configuration that belongs to the data shouldn't live in the tool. .gitignore figured this out thirty years ago.

The difference between writing down a rule and making the system enforce it — illustrated by a 15-line hook.

When AI coding assistants become workflow orchestrators, the most powerful compiler processes reality, not code.

When implementation becomes automated, human intelligence reallocates to purpose and strategy. The cognitive hierarchy inverts.

The automation tool that creates more coordination work