Engineering standards for an AI-native org
Learn the standards floor that governs every repository in an AI-native estate: the floor rules, naming, commits and versioning, testing and quality, API design, configuration, secure SDLC, CI/CD, and observability and reliability. By the end you'll be able to make changes that pass the org gates by default. Cogitave's own standards are the worked example throughout.
Modules9
Duration236 min
Levelintermediate
Prerequisites
- Basic familiarity with Git and the command line.
- Completion of the "Onboard to an AI-native codebase" path is recommended.
Modules in this path
- Apply a non-negotiable floor An AI-native org runs on a small floor every human and agent obeys. Study Cogitave's floor - its seven non-negotiable rules and what enforces each, from a commit-msg hook to policy-as-code - then apply a floor like it to your own first change.
- Apply the naming standards Name a new identifier, file, repo, or branch the way an AI-native org does - keyword-first, no redundant prefix, cased by role - and tell a functional keyword apart from a product codename, so your first artifact passes the naming gate by default.
- Commits and versioning Write Conventional Commits whose type, scope, and breaking marker drive Semantic Versioning; see how release-please turns merged commits into a human-approved Release-PR, changelog, and tag; and how the trunk-based, protected-main model gates every release.
- Test to the standard and pass the quality gate Learn how an AI-native org tests a change - the pyramid/trophy shape, the diff-coverage and mutation gates, flaky-test quarantine, the runnable harness, and the craftsmanship review bar - so you can test your own change and get it through the gate.
- Design and version an API Shape a clean, consistent API against a clear API design standard - resources, standard methods, typed errors, cursor pagination, idempotency - then version and deprecate it under a versioning policy so no consumer is ever broken without consent.
- Manage configuration and secrets Classify every value as a constant, a deployment parameter, or a secret; load configuration through the standard precedence chain, parsed once and fail-closed; and keep secrets out of git by referencing them at runtime and committing only encrypted-at-rest .env files.
- Build with the secure SDLC State the security baseline - threat modeling, least privilege, and IAM - and follow the secure development lifecycle that shifts security left, so each stage of a change carries its own security gate instead of a check bolted on at the end.
- Read the pipeline that ships your change Follow a change from a pull request through the canonical CI stage set to a gated production deploy - the ordered gates a pipeline runs, why CI is the real gate, and how the deployment model promotes one signed artifact dev to staging to prod.
- Observability and reliability Instrument a service with OpenTelemetry-spec traces, metrics, and logs, understand why agent traces are kept as evidence, and reason about reliability through SLIs, SLOs, error budgets, and the policy that turns a spent budget into a release freeze.
Related
- The one-model architecture Explain why an AI-native organization runs on one canonical property graph that humans and agents both query, what its node/edge model and identity scheme look like, and why a labeled property graph is the right substrate. Cogitave's Core is the concrete example.
- A native MCP interface to the canonical model Read a canonical model's native MCP interface as the source of truth for how humans and agents query one org's estate - why the surface is native rather than adapted, the protocol contract it commits to, and the tools and resources you call. Cogitave's Core is the worked example.
- Patterns and golden paths Learn to build reuse-first: discover before you generate, start from a patterns catalog, inherit a repository's complete ruleset through the project baseline, and use decision guides for database, infrastructure, and model selection. By the end you'll reach for the named artifact before writing anything new. Cogitave's own patterns catalog is the worked example throughout.