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Component map

AgentOps is the operations layer for agentic engineering. Its architecture is a federated integration graph: caller-owned intent, context sources, coding agents, software factories, deterministic checks, and independent judgment stay separate nodes joined by typed handoffs. AgentOps supplies the semantic work-and-proof protocol between the nodes; it absorbs none of their state.

Graph nodes and typed handoffs

Node Owned by Handoff toward AgentOps Handoff away from AgentOps
Caller The requesting human or system One resolved intent (bead, issue, or conversation snapshot) The RPI report; every later decision
Context source (tracker, Git, CASS, CM) Its own system Cited evidence with source identity and freshness Nothing — AgentOps never writes its authority
Coding agent The selected runtime One bounded candidate plus factual receipts The same candidate, judged, never edited by the judge
Software factory / execution orchestrator The selected factory Native runtime facts (completion, failure, logs) Verdicts as read-only evidence; never dispatch or repair
Deterministic checks The executable that runs them Factual check receipts Nothing — checks prove facts, not meaning
Fresh validator A context distinct from the author One PASS | FAIL | NOT_PROVEN over exact content Optional verdict.v2 for a declared consumer

The standard traversal across these nodes is the RPI traversal: Plan -> Implement -> fresh Validate -> report and stop. Vocabulary is fixed in the ubiquitous language.

Responsibilities

System responsibility Owns Does not own
Product and fitness Caller-visible outcome, product boundary, terminal evidence, read-only measurements Experiment selection or semantic PASS
Campaign Goal graph, next experiment, cumulative budgets, ratchet, breakers, terminal campaign report Candidate judgment or verdict mutation
Intent One experiment in a caller-owned bead or issue, single-mint exact snapshot, stable criterion IDs, write scope A duplicate AgentOps planning artifact or campaign graph
Experiment One bounded candidate, complete actual changed paths, factual checks, and observed effect receipts Repair loops, Git, delivery, or later work selection
Identity Exact intent, before/final subject manifests, and proof-contract digests Commit, branch, or tracker authority
Judgment Fresh-context evaluation over exact intent and subject; optional verdict.v2 persistence Candidate edits, self-activation, continuation, closure, or release
Evidence Optional atomic content-addressed verdict storage and generic provenance Admission or lifecycle state
Capability evolution Recurrence, causal, toil, and pattern observations; reusable-capability proposals Automatic promotion or policy mutation
Repository checks Deterministic ao gate check execution Semantic judgment
Optional adapters Explicit packet execution, runtime coordination, and runtime facts Selection, retries, integration, or validation authority

The only hard skill graph edge is rpi -> {plan, implement, validate}. A Goal may invoke several RPIs but remains outside that hard graph. Learn and every strategy, specialist, runtime, and factory adapter are optional seams described by the skill system architecture.