Blog — Qcoda | AI Engineering Governance

Qcoda — AI Engineering GovernanceQcoda is AI Engineering Governance for product teams: raise the concerns before the coding starts, catch the drift before it ships, and keep every decision on the record. Built into your existing PM and SDLC workflow — on your hardware, with your models. Works with the AI coding tools your engineers already use (Copilot, Cursor, Claude Code, aider, custom agents).Humans decide. AI executes. Nothing ships without alignment.How it worksQcoda turns plain-text feature requests into enterprise-grade specs in minutes — contextualized against your code, fully validated, and risk-evaluated before a single line is written. Hand the spec to a developer or an AI coder; the vetting work that used to take weeks compresses into the sprint where the change actually ships.Three guardrails

Alignment before code — ambiguous requirements get flagged before the pipeline burns time on the wrong problem.

Full decision traceability — every product decision is ledgered with date, rationale, and outcome.

Dual ownership, zero ambiguity — product owns what and why; engineering owns how.

Operational privacy by designRun Qcoda fully isolated — open-weight models on hardware you control via LLMesh, with no required third-party AI or compute provider. Or use the same guardrails over hosted endpoints (Azure OpenAI, AWS Bedrock, custom).What Qcoda means for your role

For Product & Biz — real-time observability into what is being built and why; ambiguous requirements flagged before sprint planning; decisions and rationale ledgered automatically.

For Ops & Execs — authoritative answers about product decisions and status without chasing engineering; one ledger powers board updates, roadmap, marketing, and training content.

For Engineering & Tech — specs arrive validated, scoped, and traceable to business intent right inside the IDE; build the right thing the first time.

For your AI coding tools — a drift gate that keeps generated code on-spec: before a PR opens, Qcoda checks the code against the validated spec (scope, tests, resolved concerns) and blocks anything that has drifted from intent.

Frequently asked questions

What is Qcoda in one sentence?

AI Engineering Governance — an orchestration layer that helps create, accelerate, and validate specs, ledgers decisions, and keeps AI-generated code aligned with business intent.

Who is it for?

Product and engineering teams that have adopted AI coding tools (Copilot, Cursor, Claude Code, aider, custom agents) and need governance over what gets built.

What is Qcoda not?

Not a code generator. Not an AI IDE. Not a code review tool. Not a ticket-tracker replacement. Not a no-code platform. Qcoda sits above the build layer as the governance and decision-record layer — closer to a financial ledger for product decisions than a developer productivity tool.

Does it require sending data to a third-party AI?

No. Inference can run entirely inside your perimeter via LLMesh on open-weight models. Hosted endpoints (Azure OpenAI, AWS Bedrock) are optional.

Where does it integrate?

IDE-side with your AI coding tools; PM-side with your existing work-item systems; inference-side with private or hosted LLM endpoints.

What pricing tier is available today?

Early access — join the waitlist at qcoda.com/#waitlist.

Team

Andrew Schwabe — CEO. Serial entrepreneur. Founded ForMotiv (behavioral analytics) and Saigon AI.

Rebecca Joy — Co-Founder, Finance & Operations. Six-time co-founder. CEO of Saigon AI. UC Berkeley data science.

Gwen Cheylan — Co-Founder, Strategy & Market Positioning. Four-time founder. CEO of Talential. Former CTO of Kiwipay.

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