AI driven spec development

Source: https://www.instagram.com/reel/DcOsVDVlIpp/?igsi=MTN4cWF6NnNtdTNibA==

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Summary

Top AI engineering teams are shifting to repos with zero handwritten code, where humans write specs and tests and Claude Code (or similar agents) implement and iterate until tests pass. The core skill shift is from writing code to writing precise, testable specifications.

Core ideas

One context card plus 6 ideas

Spec-driven development: The best Silicon Valley AI teams write English specs, not code. Humans define what good looks like, agents write the implementation.
Precision over ambiguity: A spec like the password reset example works because every sentence is a testable condition. No room for interpretation.
Tests before code: Test-driven development isn't new, but it becomes essential with non-deterministic AI tools since you need a hard exit criteria for the agent to check itself against.
The three-step loop: Write the spec, write the tests, then tell the agent to implement until all tests pass and bring back results.
Self-correcting agent loop: Claude Code reads the spec, writes code, runs tests, reads errors, fixes code, and repeats, mimicking how a good engineer works when given a clear target.
Human leverage shifts upstream: The valuable human work is no longer typing code but deciding what counts as correct, what counts as broken, and what the exit criteria are.

Quotes

“The best and fastest AI engineering teams in the Silicon Valley will have repos with literally zero handwritten code.”
@therobertta

“The humans focus on the English and the specification. The agents write the code and implement.”
@therobertta

“Every sentence there is a testable condition. Determinism. No ambiguity.”
@therobertta

“You only get high leverage though when you put your brain on what is good, what is bad, and what's the exit criteria.”
@therobertta

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