RCF: AI software,
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The demo runs. The screens look right. Underneath, the agent has made a hundred decisions you never made. Each one quietly wrong in a way that surfaces six weeks later.

The gap AI opened up. Teams plateau at the first; the second is where the senior premium lives. Pulls from the demo-ready vs production-ready concept page.

Copilot. Cursor. Claude Code. Cline. Aider. They are brilliant at auto-complete, refactors, and scaffolding. They do not fix the chain from intent to evidence.

“Use AI responsibly” docs gather dust because they’re advisory, not load-bearing. They sit beside the code, not in the path of the code.

Mandating human eyeballs on every AI diff doesn’t fix the problem. It spends the productivity gain on the wrong activity. The reviewer is reading the output, not checking it against the intent. There’s no intent on file to check against.

Anchor in requirements. Every requirement breaks into user stories. Every story carries acceptance criteria. Every acceptance criterion maps to a test. Code arrives last; its only job is to make the tests pass.

Every line points up to the decision that justifies it, and down to the test that proves it.

From any line of code, trace which AC, which story, which requirement, and who signed it off. From any business decision, trace every test that proves it ships.

The living spec. POs don’t know what they want until they see it; that’s not a bug. Traceability surfaces the gap; the gap becomes the next FBS.

Same shape whether it’s a bug fix, a new edge case, or a whole new module.

Six months after ship, compliance asks: why did this customer get a Tier-2 KYC verdict?

In RCF, the answer is in the AC that scoped the verdict logic, the test suite that asserted it, the FBS that built it, and the human who signed the criterion. The chain holds.

Less time writing code. More time specifying ACs and reviewing for theatre. The senior-engineer premium moves up the stack, from typing to judgement. Pay band intact, role shape different.

They will like this.

They ship more, faster, under a structure that makes their work auditable for the first time. The ladder gets clearer: writing crisp ACs is the new “can they spec well?” interview question.

RCF works on the artefacts: requirements, ACs, tests, code. The Digital Operator works on the people: a digital, self-learning counterpart to a human role.

Each role can get one. PO. Architect. Engineer. QA. Each one watches how that person works, captures the pattern, and contributes to a shared knowledge base that everyone can draw from.

The first instance is live: an engineering Operator that runs the estate, handles routine work, and learns my judgement as it goes.

Most institutional knowledge isn’t the decisions themselves. It’s the why. Intuition. Decision paths. Justifications. The reason you ranked one option above another.

This kind of knowledge doesn’t get written down because the cost of writing it down has always been higher than the cost of carrying it in your head. The Operator inverts that. Every decision, every justification, every priority call is captured in context, as it happens, by the thing that was already in the loop.

RCF: one product delivered end-to-end on the methodology, with PoC tooling. A second product on a different stack is in flight. Team adoption is widening.

The Digital Operator: the first instance, an engineering assistant, runs this estate. It built the methodology rewrite. It builds this site. It builds Stravica’s own tooling.

Early days. The shape is real, the scale is small, what’s possible is being worked out. If you’re heading the same way, let’s talk.

• stravica.ai
• stravica.ai/rcf-methodology/: the methodology, full read
• stravica.ai/rcf-methodology/cto-pitch/: this deck
• Contact: hello@stravica.ai