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Workflow Evolution Method: V12 v1

Workflow Evolution Method: V12 v1. A source-qualified account of the method, capability boundaries and required evidence.

Method specification
This is the retained source text, not a new validation of its claims. Numerical results and comparative claims require the accompanying source review before public reuse.

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Provenance, authorship and editorial notes

Workflow Evolution Method: V12 v1

Id

method-workflow-evolution-v12-v1

Project

AI workflow research

Source path

conduir-evolution/delivery/methods/WORKFLOW-EVOLUTION-V12.v1.md

Source sha256

04155edaea6808d93bd19219e5220ff4dd8f4c4a1541606aee6d644adeed1a18

Repo head

61278260a6a877769ef025356ecc5feb1d53f1b4

Date
Not recorded
Author
Not recorded
Document status

Method specification

Summary

Workflow Evolution Method: V12 v1. A source-qualified account of the method, capability boundaries and required evidence.

Evidence concerns
  • A preserved method or proposed capability is not a certified autonomous controller.
  • These documents retain their historical scope; no implementation or learning experiments were run for this website task.

Workflow Evolution Method: V12 v1

Status: METHOD_PRESERVED_GENERIC_CONTROLLER_NOT_PROVEN

Stable invocation: $workflow-evolution <subject> or /workflow-evolution <subject>

Purpose

V12 is the outcome-to-learning method that was used to develop and evaluate workflows. Its value is
that completion does not stop at theory, code, merge, or deployment. It asks whether the result was
independently reviewed, reusable by a fresh AI, effective in the intended environment, converted
into a bounded lesson, and used to establish a better successor baseline.

The name V12 came from the original twelve barriers, B0-B11. The later B12-B15 extension closes
the compound-learning loop. The stable user-facing name is workflow-evolution; users do not need
to remember the historical version label.

Barrier contract

StepBarrierRequired outcome
1B0 OBJECTIVE_FREEZEFreeze intended outcome, beneficiary, acceptance, boundaries, and authority.
2B1 BASELINE_MEASUREDMeasure current truth before intervention.
3B2 DELTA_GRAPH_VALIDDescribe the evidenced difference between baseline and outcome.
4B3 ROAD_OPTIONS_REVIEWEDProduce and independently challenge materially different roads.
5B4 OPERATOR_STEP_SELECTIONPreserve operator selection of the next bounded road.
6B5 SUPPLY_RECONCILEDReconcile demand with existing services, contracts, tools, and evidence.
7B6 STEP_ADMISSIONAdmit one bounded step with authority, controls, recovery, and acceptance.
8B7 STEP_RESULTPerform only the missing delta and retain exact result evidence.
9B8 STEP_RESIDUEPackage reusable contracts, evidence, procedures, findings, and limits.
10B9 INDEPENDENT_REVIEWIndependently review the exact subject and evidence.
11B10 READBACKGive the residue to a fresh AI and observe whether it can discover and reuse it.
12B11 EFFECT_MEASUREDMeasure actual behavior in the required environment.
13B12 LEARNING_CANDIDATEConvert success, failure, and rejected theories into a candidate lesson.
14B13 NEW_BASELINEMeasure the post-intervention state using a comparable method.
15B14 NEXT_ROADSGenerate successor opportunities from new evidence.
16B15 OPERATOR_DECISIONLet the operator choose, defer, revise, or close the next road.

Invocation behavior

1. Read METHOD-REGISTRY.v1.json and report the resolved method status.
2. Pin the subject, direct inputs, governing documents, and non-goals.
3. Start at B0; do not jump to a later barrier because an old artifact appears to satisfy it.
4. Treat each barrier as a claim requiring its own evidence and explicit transition.
5. Use Scoped Delivery as a compiler within B0-B9 where its exact instrument is healthy and its
output fits the problem. Scoped Delivery is not the V12 parent lifecycle.
6. Use a fresh agent or session for B10 readback when available; give it the durable residue, not
the authoring conversation.
7. Keep SOURCE, BUILT, DEPLOYED, and EFFECTIVE evidence independent.
8. At B12, store a candidate lesson with evidence, limitations, failed alternatives, and source
identity. Do not call storage learning.
9. Promote a lesson only after transfer/readback and successor evidence show useful reuse.
10. Finish at B15 with an operator decision or an explicit open decision, never an implied next
cycle.

The current default is a governed manual run. As last recorded on 2026-08-21, Role Fabric and
Temporal could coordinate bounded fixed-topology leaves and a no-effect shadow pilot, but could not
execute an arbitrary end-to-end B0-B15 parent workflow. Do not represent that gap as closed
without fresh exact-subject evidence.

Authority stops

Stopping at one boundary does not invalidate evidence completed before it. Record the run as
partial, identify the exact unmet transition, and preserve a durable resume reference.

Durable run residue

A durable run should identify:

distinct record classes;

Persist stable contracts and accepted evidence in Git. Use Jira for human work projection, Role
Fabric for role-bound work custody, Temporal for orchestration history, the durable channel for
communication provenance, and Cortex for advisory semantic recall with canonical backlinks. None
of those stores replaces the others or grants authority merely by containing a record.

Last recorded position

The method and its evidence were not lost. The repository contains:

The last recorded recommendation was to ratify a closed V12WorkflowSpec, run
V12_PARALLEL_SHADOW_V0, use its manual join ledger as the acceptance corpus for a generic reducer,
add an observer-only V12 parent, and repeat with automatic dependency release while effects remain
disabled. The recorded state explicitly rejected a claim of automated end-to-end B0-B15
execution.

Governing references

Human presentation:

The Confluence page and local recovered preview are explanatory projections. The repository files
above govern the method.

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