What you can do with Kvendra

Kvendra is for developers who run AI-assisted development and want it to be traceable. Each of these is a real workflow that the entity + transaction + changelog model makes auditable rather than ephemeral. The common thread: an agent does the work, but every meaningful step lands as typed state you can later query and explain.

Feature pipelines

Plan, implement and ship a feature as one orchestrated workflow. The agent opens a transaction, drafts the requirement and design entities, then promotes them from draft to active only when the work actually lands — so a half-finished feature never pollutes the knowledge base. Because the transaction is the unit of change, either the whole pipeline's state commits together or none of it does.

Bug pipelines

Triage and fix bugs with the same discipline. A bug report becomes a typed entity; the analysis, the test that reproduces it, and the fix are drafted inside a transaction and linked back to it. The draft-to-active flow keeps speculative findings separate from confirmed ones, and the relations between report, cause and fix stay queryable long after the fix ships.

Incident RCA and postmortems

When something breaks in production, capture the incident as a first-class entity with a root-cause analysis and a written postmortem. From it you can derive the follow-up work — the runbook, the requirement, the preventive pattern — each as its own linked entity. The changelog records who changed what and when, so the postmortem is grounded in an audit trail rather than memory.

KB-driven documentation

Generate documentation from the same knowledge base that drives the work, so the docs cannot quietly diverge from reality. Each manual or page is backed by typed entities; when the underlying facts change, the document is regenerated from them. (This site is built exactly this way.)

Regression suites

Run regression suites and persist each execution as a typed run entity — not a log line that scrolls away. Results accumulate as queryable history you can compare against expectations, and a failing run can spawn a linked issue automatically, so a regression becomes tracked work the moment it appears.

Release management

Cut releases as typed entities with an automatically assembled changelog. The release gathers the transactions and entities that landed since the last one, so the changelog is derived from what actually changed rather than hand-curated notes — and the trace from a release back to each feature, bug and incident it contains stays intact.

These workflows ship as Skills, built on the Platform. See how it works to follow the wiring.