Stravica
Stravica is where I work out how to build software with AI, and where what gets built lives. RCF, the methodology. The Digital Operator that practises it. Plus the writing that explains both.
Methodology
The Requirements Confidence Framework. A working method for closing the gap between “the AI built something” and “the AI built what you asked for.” Requirements at the apex, acceptance criteria as the contract, traceability built into the data model. The full methodology, end to end, and the lineage that landed it.
Practice
A digital counterpart to a human operator role. It does the work, captures how a human in that role would have done it, and contributes what it learned to a shared institutional store. Built on RCF. First instance running today.
The AI trust gap is a methodology problem, and the industry keeps reaching for tooling instead.
Every AI failure mode has a human equivalent that predates large language models by decades. The common root cause is the one nobody wants to examine.
Requirements used to be somebody's job. Then we hollowed the role out, and now AI is filling the gap with guesswork.
Stravica is a body of work in public. The bar is software that holds up under real use, not software that looks good in a demo.