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Cadence

Why Cadence

Left to its own devices, Claude jumps straight to code. It skips the design, leaves plans half-done, and forgets to validate. The traditional answer is to catch the gaps yourself by reading every diff. But when AI writes most of the code, line-by-line review stops being a realistic place to put your attention.

Cadence is built for that new reality.

The bet: spend more time on design, less on implementation

Section titled “The bet: spend more time on design, less on implementation”

Cadence is an AI-first workflow. The bet it makes is that with a capable model writing the code, the scarce resource is no longer typing: it’s direction. So Cadence flips where your time goes: you spend significantly more time on the front half (brainstorm → design → plan) and much less worrying about how any of it is implemented.

When implementation is fast and cheap, brainstorming and intent refinement become the bottleneck, and a workflow that treats them as afterthoughts squanders everything the model is good at. You still work by intent (“I want a credit ledger that shows AWS credits per account”), but instead of letting that intent slide straight into an unreviewable pile of code, Cadence routes it through stages, each with a written artifact and an explicit gate where you decide whether to continue.

You direct judgment at the gates. The machine carries the verification load.

Why gates and readable artifacts are the whole point

Section titled “Why gates and readable artifacts are the whole point”

Once you stop reviewing line by line, “the tests pass” or “here’s the diff” isn’t trust: it’s a leap of faith. Cadence replaces the leap with two things you can evaluate at the level of intent:

  • Readable artifacts at every stage. Brainstorm produces a plain-English stub. Design produces a narrative you can actually follow. The plan is exact, but the design it came from speaks your language. You’re never asked to approve something you can’t understand.
  • Explicit gates between stages. Nothing advances on its own. Brainstorm stops and tells you to run design. Design stops and waits for you to say “approved.” Execute stops at the audit. Each pause is a place where your judgment (the thing the machine still needs from you) is exactly what’s called for.

The mental model is simple: you supply intent and judgment at the gates; the artifacts let you exercise that judgment without reading a single line of code.

How the trust gets built without you reading diffs

Section titled “How the trust gets built without you reading diffs”

Two stages exist specifically so you don’t have to inspect the implementation:

  • Audit checks the work against its own plan: every checkbox backed by real code, no half-finished steps, no quietly-dropped scope, no deferred TODOs smuggled in. It’s an automated reviewer that answers “did it actually do what the plan said?”
  • Validate walks the work as a user would after deploy: the manual and automated checks that confirm the thing behaves the way you wanted.

Together they carry the verification load. You judge intent at the design gate; audit and validate confirm the result matches that intent. That’s the chain that lets you trust what shipped without ever reading a diff.

Where to go next

Section titled “Where to go next”
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