When code generation is instant, the bottleneck moves from writing code by hand to direction and review. We changed our delivery to match: AI generates the code, senior engineers direct it, judge it, and ship it. The output is finished software you own.
A senior engineer maps what you need and writes the spec the AI builds against.
All the code is AI-generated against that spec, across the full stack.
Every change is reviewed by a separate adversarial agent and then approved by a senior engineer. Generation is fast; the gate is human.
Finished, documented, tested, and yours, repo and IP included.
Every engagement ships the same four things. They are deliverables, not options.
Not a demo, not a prototype branch. Behavior your users touch.
Code, IP and history. No lock-in, no license back to us.
Generated tests covering the workflows that matter, running on every change, so the next change does not break the last one.
The decisions, rules and tests of the system, connected and queryable, so anyone (human or agent) can continue it. It is why the software stays maintainable after we hand it off.
The difference between AI that underperforms and AI that delivers is not a cleverer prompt, it is context. We give the AI two things before it writes a line: how the system is today, and what it should do. Without them the AI improvises; with them it builds against reality.
The engineering brain: a live knowledge graph of your code and infrastructure, refreshed with each commit.
The specification: your intent and the project's rules, written down and reviewable.
We run a spec-driven workflow built for the leading AI coding agents, so the spec generates the implementation, it does not just guide it. The workflow is a set of versioned artifacts that live in the repo and are reviewed in the PR like any code. One spec feeds implementation, tests and QA from the same acceptance criteria, so there is no second, hand-written test plan to drift.
constitution generated from your real codebase patterns · clarify & analyze optional
Same AI-generated, senior-judged delivery, in whatever shape fits your team.
We take the build end to end and hand you finished, owned software.
Our full-code-generation engineers join your team and ship inside your sprints. Staff augmentation, evolved: AI-generated, expert-directed and reviewed.
We embed specialists who turn the manual and repetitive parts of your SDLC (testing, CI/CD, integrations, data plumbing, releases, internal tools) into AI-driven automation, and they ship application code too.
A senior engineer embeds, runs discovery, owns the spec, directs and judges the AI, and operates the result. One accountable owner, end to end.
How an embed works →From a ticket to a running regression test, with one human gate.
Across roughly ten repositories, test coverage moved from single digits to the high nineties, with thousands of generated tests merged and passing in CI. Regression cycles that took days now take minutes, and the automation surfaced real bugs and secrets manual review had missed.
A requirement becomes a spec, the AI implements it and generates the tests, a developer approves (the one required gate), it deploys on your CI/CD, and a QA card is generated for whatever needs a real environment.
An AI agent with full repo access decides what to test, writes and runs the tests, and drives a real browser through the full user journey, leaving evidence (screenshots and a recording) for every run.
Unit, integration, contract in CI on every PR; end-to-end against the deployed environment in a real browser.
The automation handles execution; the QA engineer reviews the spec for coverage and audits the evidence.
QA automation is also a standalone service: suites built and kept alive for software we did not write. Software QA automation
The methodology behind every claim on this site runs today in real client engagements, not in a lab.
Judgment, architecture, and accountability stay with people who have shipped for years.
Code, IP, repo. No licensing back, no platform lock-in.
Engineering teams across several countries, with years shipping production software.
Finished software you own on its own, and every project is built on an engineering brain: a live knowledge graph of your code and how it connects, decisions, rules and tests included. It keeps the software maintainable and extensible, evolving with your company, and it becomes another module your Company Brain inherits.
Learn about the Brain →Powered by the Neocortex. The intelligence layer that ships with every brain and agent we build. It arrives knowing the job and keeps getting smarter with every deployment.
Meet the Neocortex →We work in your stack when you have one.
Frontier models and coding agents, MCP servers, multi-agent orchestration, multi-model in production where it fits.
TypeScript (Node, Hono, Express) and Python (FastAPI). Next.js and React.
Postgres and pgvector, Redis, vector DBs, Neo4j for graph.
Real-time voice platforms, vision and document pipelines.
Eval suites and holdout testing, Langfuse and Helicone, Sentry and Datadog.
AWS and GCP, Firebase, Docker, Playwright for end-to-end tests.
A leading SaaS in edtech (client): an entire 66-repo codebase moved to an AI-native, spec-driven standard in a 2-day sprint, with an engineering constitution generated from the real code, an automated security audit, full database documentation, and a QA automation suite started.
A leading SaaS in association management (long-running client): started as classic staff augmentation, their developers now on the same AI-native, spec-driven standard, led by our embedded engineers, with custom skills merged into the client's product and full code generation for QA test automation expanding across their products.
One proven methodology across both: the same standard (engineering constitution, spec-driven workflow, skill library, adoption tracking). Most of the code we deliver today is AI-generated.
That is why the QA suite and the evaluation gates are deliverables, not options. Every change is judged by a senior engineer and protected by tests before it ships. You inherit software with its immune system attached.
You do, or we do: your call. The repo is yours, the suite protects every future change, and the engineering brain means the next engineer (yours or anyone's) starts with context instead of archaeology.
Nothing changes hands, because everything already lives in your hands: code, IP, repo, tests, documentation. Zero dependency is part of the spec.
Scope a project in one working session. Scope: defined per project, in the working session.