The work that shapes every session afterwards
This is what progress looks like. Fast, visible, satisfying. AI made it possible to ship things in hours that used to take weeks.
Nobody sees the hooks.
Nobody sees the audits.
Nobody sees the rules that held.
That is exactly the point.
A billing email said 100% of GitHub Actions minutes were used. The budget page showed $0.18 spent of a $100 budget. Both were correct. They were measuring different things. And the gap between them contained three weeks of invisible waste.
What the question found
After the workflow fix
74 min ÷ 18 min, from gh run list audit, May 2026
AI optimises locally.
You optimise globally.
Nobody was doing both.
I had deployed the same site 37 times in one day without noticing. The session goal was: get the deploy done. It got done every time. The cumulative cost of how it got done was invisible until a billing email looked wrong and I followed the question.
Buggy Smart's Railway service was pointed at an abandoned repository while all development continued in the active one. GitHub Actions deployed cleanly. The site looked live. The wrong code ran every day. The AI session had no way to see this: it was optimising within the session, not auditing the full deploy chain.
The fix was not to check more carefully next time. The fix was to make "which repo?" a verified fact, not an assumption.
A deck was built without running the mandatory 4-round quality process. The process was written in CLAUDE.md. It was read at the start of the session. It was ignored during the build. When the rule was pointed out, the answer was not to add more text. The answer was to make the rule un-skippable.
The answer was not
more text in CLAUDE.md.
The answer was a hook.
Every time a rule broke, the instinct was to rewrite the instruction more clearly. Clearer instructions failed just as reliably. The shift was recognising that the problem was the medium, not the message. Instructions live in text. Infrastructure lives in code.
"Add more text to the instructions, see if there is a stronger, more robust approach and build a hook."
Mike Litman, 2026-05-11
Every rule that requires
memory will fail.
Every rule the harness enforces will hold.
Stop trying to remember. Start designing systems where remembering is not required.
Each hook is a rule that cannot be broken. Not by accident. Not by a session that got busy. Not by an AI optimising locally.
Yes. With code review. Pull request gates. Colleagues who catch mistakes. Senior engineers who hold the institutional memory.
This is that, for a team of one working with a system that has no memory between sessions and optimises locally by design.
The hooks are not a productivity trick. They are the institutional memory the AI cannot hold.
Start here tomorrow: open your GitHub billing page. Check Actions minutes used this month. If it is over 50% before mid-cycle, run the workflow audit below. That is your entry point.
What the human's job becomes
Write the code. Run the deploy. Check the output. Repeat. The work was in the doing.
Now
Build the hooks. Run the audits. Ask the confusing question. The work is in making the doing better, permanently.
The floor under output
is rarely the headline.
Build the floor.
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