Coevolve
Coevolve is the improvement capability inside Teammately correctness infrastructure. It lets agents and engineers pursue multiple candidate directions from benchmark evidence, evaluate those candidates through the same canonical path, and continue from stronger branches without losing the goal, chronology, or evidence behind the current frontier.
Definition
Coevolve is realized through Improve and durable Improvement Sessions. A session starts from selected benchmark evidence and a target Harness. A Goal Contract turns a free-form objective into pinned target identities, measurement bindings, constraints, unresolved items, and permitted intervention boundaries. Once confirmed, that contract governs future work without rewriting earlier evidence.
Sessions can use Work or Evolve behavior. Work supports bounded implementation and review. Evolve supports parallel candidate exploration across epochs and retains a frontier based on current evaluation evidence. Candidate Harness versions become meaningful only when canonical Runs return observable results.
Decision checkpoint
| Situation | Improvement action | Evidence requirement |
|---|---|---|
| One known candidate change needs implementation | Start a Work session | Confirmed Goal Contract and pinned target evidence |
| Several hypotheses should compete | Start an Evolve session | Explicit authorization, measurement bindings, and comparable evaluation path |
| An external coding worker will implement | Prepare a scoped worker package | Returned Harness version or evaluation request before claiming observable progress |
| A candidate looks stronger | Inspect the current frontier | Canonical evaluation receipts support the retained position |
| Exploration exposes missing correctness or coverage | Return the observation upstream | Identify the policy, rubric, case, or coverage artifact that must change |
Evidence-backed branching
Candidate exploration is not a sequence of undocumented edits. Each proposal should state the hypothesis and its relationship to the Goal Contract. Evaluation receipts bind candidate identity to benchmark identity and result. Narrated trajectories can explain the work performed, while chronology records durable transitions, agent activity, pauses, resumptions, and terminal state.
The current frontier is not simply the newest candidate. It represents the candidates retained by the session's evidence and goal constraints. A candidate can improve one slice and regress another; the frontier and comparison views keep that tradeoff visible.
Bridge between experts and engineers
Improvement can reveal that the candidate is not the only incomplete part of the system. A missing coverage tuple, unclear rubric, contradictory policy, or insufficient case material should become an upstream contribution opportunity. This is how Coevolve connects coding agents to domain experts: engineering work is guided by benchmark evidence, and newly discovered correctness questions return to focused expert work.
External workers remain bounded. Teammately may prepare a package for Codex, Claude Code, or another worker, but it records only the work returned through the defined contract. It does not infer private activity or fabricate a working state.
Worked example
Parallel grounding hypotheses
An Evolve session starts from failures involving conflicting policy documents. One candidate changes retrieval filtering, another changes source ranking, and a third changes answer construction. Each saved Harness version is evaluated against the pinned benchmark. The frontier retains the candidates supported by grounding and uncertainty rubrics, while a newly observed source-authority ambiguity becomes an Expert Contribution opportunity.
Related workflows
Related reference pages
Source confidence
Doctrine-backed: this page defines Coevolve as the public capability. The Improve pages provide code-backed session, contract, candidate, and frontier behavior.