Engineering Practice
Most studios won't show you how the work gets made. This is ours.
MayiLabs runs as a governed, multi-agent engineering organization: a founder as principal engineer and orchestrator, one external contributing engineer, and a fleet of specialized agents operating under written rules. The point isn't headcount theater — it's that a small operation can hold a large surface to a real standard, because the standard lives in code and documents, not in someone's head.
A governed multi-agent operating model
Work is decomposed and delegated to specialized agents — DevOps, security, data, QA, mobile — each initialized from a written context file and bounded by explicit escalation rules. Novel architecture, IAM changes, and anything touching money stop and wait for a human ruling. Autonomy where it's cheap; a hard stop where it isn't.
A layered review pipeline
Every change runs a gauntlet before it merges: static analysis, a quality gate on new-code coverage and duplication, a security scan, and independent AI reviewers that have to agree before a pull request is mergeable. A single reviewer can be wrong; a panel that has to converge is harder to fool.
ADR corpus discipline
Decisions are written down as Architecture Decision Records and treated as load-bearing. When a rule changes, the record changes with it, and the old one is marked rescinded rather than quietly deleted. The corpus is the memory the organization would otherwise lose between sessions.
A seven-pillar security posture
Auth, attestation, least-privilege IAM, secret hygiene, client–server boundaries, structured error capture, and enforced quality gates — each with its own runbook and its own tripwire. Financial-impact surfaces are held to a team-grade observability standard even though the team is small, because that is exactly where a discipline gap costs the most.
None of this is glamorous. It's the difference between a demo and a product in someone's hands.