Built-in lifecycle
The development lifecycle is built into the app.
On most deliveries the evidence lives outside the software: a wiki nobody opens after go-live, a spreadsheet of test results, a roadmap deck that stopped being true in month three. Fusion knows what it is made of, so it keeps that record itself. The roadmap, the workflow gates, the user guides and the test recordings are pages in the application your people already sign in to — and they are current, because the work is what updates them.
Built AI-native
Ask for a change. Everything it touches moves with it.
AI was not added to Fusion afterwards. The framework was built to be worked on by it, which means it knows what it is made of — which spec describes which workflow, which code implements it, which tests cover it, which guide explains it. Ask for a change and it already knows the full list of things that change with it.
Somebody asks for
“Add a risk rating to the intake workflow. Anything rated high should route to the compliance queue for sign-off.”
One sentence, from somebody who does the job — not a change request written by somebody who has to translate it first.
What moves with it
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01
The specs
The workflow spec, the resource specs and the domain model are updated to describe the new field, the new rule and the new route.
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02
The code
Fields, logic, screens and the database migration, written to the conventions the framework already holds.
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03
The tests
Unit and system tests written for the new behaviour, then run. When one fails it fixes the code, never the test.
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04
The user guide
Rewritten against the screens as they now are, and the walkthrough video recorded again.
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05
User acceptance
The task script prepared, the sessions analysed, the findings triaged into issues and queued for retest.
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06
The plan
Roadmap status, changelog entry and tech-debt ledger all brought back up to date.
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07
The release
Deployed, and then verified in production.
4–8h
Request to production
A change of this size lands the same day. The person who asked for it watches it working before they go home, instead of waiting for it to appear in a release three months out.
80/20
AI effort · human effort
AI does the writing: the specs, the code, the tests, the guide. Your people spend their fifth of the effort on the two parts that need a person — deciding what ought to change, and judging whether what came back is right.
It knows what it is made of
The roadmap, the domain model, the specs, the code, the tests and the guides are a declared chain, not a folder of documents that happen to sit near each other. A checker walks that chain and reports anything that no longer agrees with its neighbour.
A named skill for every step
Not one general assistant guessing at your house style. Each step has its own skill, with its own inputs, its own outputs and its own definition of done — shipped and versioned with the framework, so the conventions arrive with the code.
You approve at every checkpoint
The orchestrator stops and waits: at the workflow spec, at the resource specs, at the test coverage. Nothing reaches production because a machine decided it had finished. The work is faster, and the judgement stays yours.
See the lifecycle run — on your workflow, not ours.
The fastest proof is a live one. Take the Challenge and watch the roadmap, the gates, the tests and the guides stay current while the software is built.