Greenfield Production Systems builds and verifies production software with a gated factory. Every engagement ships with evidence you can check and a boundary stating exactly what we didn’t cover.
AI agents now write more code than any team can meaningfully review, and the new code looks right whether or not it is. In survey after survey, technology leaders rate AI-generated code higher quality at review, then report more production incidents once it ships. The pair of numbers below is the latest; the full argument, sources included, is in Code generation was never the bottleneck.
Greenfield Production Systems exists for that gap. We build production systems on an opinionated, automated architecture and verify them, including the code machines write, inside a gated factory that leaves a transcript. The same regularity that makes the architecture scale is what lets the factory prove it.
The working vocabulary behind all this is defined in the glossary, each term with its origin cited.
94%
rate AI code higher quality at review
78%
report more production incidents
Three doors
The verification factory reads your repositories without modifying anything, then delivers a behavior catalog, a tiered coverage-debt report, and regression tests in your own QA repo. Every claim cites its source.
Receipt 1,485 generated regression tests across a 15-target production estate (view the artifact)
Start with an auditA senior architect directs the factory through discovery, architecture, specification, implementation, and verification. You keep the specs, the ADRs, the tests, and the gate transcripts.
Receipt Spec to production in six weeks, with the delivery published week by week (view the artifact)
From spec to productionWe extract a provenance-cited behavior catalog from your running system, you approve it, and the final milestone is accepted when the same test suite passes on both systems, the one you have and the one we built.
Receipt A 25-year-old codebase rebuilt by the factory, in public (view the artifact)
Parity-guaranteed modernizationProof
Every figure links into the evidence library and carries the tag the factory gave it: proven, traced in source, or probe candidate.
gates on every build, deterministic and LLM-judged
generated specs green against live staging, first run
axis pairings analyzed; 3 coupled, each cited to its guard
API specs delivered, beside 19 journey specs and 7 view specs
bounded contexts in the Bugzilla port, with 18 cross-service events
How it’s made
Work moves through tracks and stations with automated gates between them; what fails a gate doesn’t move forward. Every run leaves a transcript, and the line itself is versioned like a product.
Built a production SaaS with an architect reviewing at stations that are now automated gates.
Ported Bugzilla end to end autonomously, from services to frontend to e2e journeys.
Verifies with typed provenance: every claim in the catalog cites its source, and a gate checks the citation.
Answers
The questions people actually type before choosing a software partner, answered straight. Each links to the full version in the answers library.
Retention rates are self-reported and unaudited, so they are a weak basis for a hiring decision. A more reliable signal is whether a firm can hand you an artifact that shows what its software does: a behavior catalog cited to file and line, or a gate transcript from a real run. Greenfield Production Systems sells that artifact as the product, so the evidence comes before the engagement rather than after it.
Full answerStart with the catalog, not the code. Before anything is rebuilt, the existing behavior gets inventoried and cited to file and line, and you approve that catalog as the definition of done. The rebuild is then accepted on parity: the same behavioral test suite runs green against both the old system and the new one. Approving the parity definition before work begins is what keeps a rebuild from quietly dropping behavior.
Full answerIt can be, and the honest filter is scope rather than budget. A bootstrapped team is best served by a tightly scoped first build with a fixed, scoped-in-one-call price, so you are buying a defined outcome instead of an open-ended retainer. What you should not accept at any budget is a build with no specs and no tests, because that is the version that costs the most later, when you have to pay someone to figure out what you already own.
Full answer