The self-managing loop
“Self-managing” is easy to say and usually means a scheduler plus a chatbot. In Supernova it means five concrete parts form a closed control system.
The operator supplies a goal state, not a fixed script. Supernova repeatedly compares current evidence with that state, decomposes the remaining delta, executes the next admissible work, and feeds the result back into planning. The recursion terminates when the declared evidence obligations are satisfied; exhausted budgets, denied authority, or unresolved judgment fail loud instead of being reinterpreted as success.
| Control-system role | Supernova mechanism |
|---|---|
| Setpoint | Project vision, requirement graph, and declared evidence obligations |
| Actuator | Issues, delivery workflows, agents, VCS, and operations |
| Sensor | Review, tests, coverage, field metrics, approvals, and external attestations |
| Controller | Workflow for known work; monitoring and scoped judgment for new findings |
| Memory | Wiki, decision ledger, issue history, agent memory, and the correlated event trail |
Start with what should be true
Every project carries a maintained vision. Accepted outcome claims decompose into a directed graph of requirements. Each requirement records why it exists, what depends on it, and what evidence would be proportionate to the claim.
That graph is the project’s setpoint. It gives the system something stronger than “keep the agents busy”: an inspectable definition of the destination and a mechanical way to find uncovered intent, missing implementation, and insufficient proof.
The planning loop continuously compares vision claims with that graph. It can propose missing requirements, decompose accepted outcomes into features, turn those features into specification tasks and implementation wires, and preserve the dependency and evidence relationships between them. Planning is therefore regenerated from current project truth instead of becoming a stale, separate roadmap.
Turn gaps into bounded work
The work generator and audits can surface several kinds of gap:
- a vision claim with no covering requirements;
- a requirement with missing children or proof;
- a failed test, degraded field metric, or expired attestation;
- an operational defect or recurring review miss;
- an adoption failure or coordination bottleneck.
Mechanical checks report facts. They do not silently redesign the project or file arbitrary work. A capability-scoped judgment step decides whether to dismiss the finding, amend the design, or create a reviewed issue. Once the outcome and requirement change are accepted, the ordinary decomposition path can plan the bounded delivery work automatically.
Act through durable, owned mechanisms
Admitted work enters the frontier. Workflows allocate it, agents act in isolated scopes, and VCS and operations perform trusted state changes. Every important action produces a typed event with causal identity, so later evidence can be connected to the decision and change that produced it.
Measure the result
Completion is derived from current evidence rather than an agent’s statement. A passing isolated test may satisfy a narrow code claim; a product-level requirement may also demand coverage, a clean review chain, a field metric, a user-journey exercise, or an independent human attestation.
Evidence can decay. When it does, the requirement’s satisfaction reading can go down without rewriting the historical issue that originally delivered it. That distinction lets Supernova say both “this worked then” and “it is not proven now.”
The new reading becomes the next loop input. A partial success narrows the remaining requirement delta; a failed proof selects repair work; a newly discovered dependency changes the plan. Supernova therefore iterates on observed state rather than blindly replaying the original plan.
Improve the manager too
The same loop can inspect its own behavior: reviewer misses, repeated boot-backs, inaccurate value scores, token waste, dispatch starvation, stale audits, or policy gaming. Proposed changes to the scoring rubric, role instructions, or gates follow the normal decision and approval path.
Predicted value is recorded before work begins and compared with realized outcomes later. That makes the work-selection system falsifiable instead of permanently self-congratulatory.
Know when quiet is legitimate
An empty queue is not automatically success. The frontier is legitimately quiet only when vision claims have covering requirements, required evidence is green and fresh, scheduled audits are current, and no actionable findings remain. Otherwise idle capacity is itself a generator or dispatch defect.
Self-management is bounded
The loop may identify and deliver improvements, but it cannot rewrite its constitutional limits. Protected policy changes require approval under the policy already in force. A stable Supernova version builds a candidate successor in isolation rather than changing the running floor beneath its own judgment.