Infoconex AI Flywheel Specification v0.2.1

Infoconex AI Flywheel Specification v0.2.1

v0.2.1 is a defect-correction and consistency release following the major conceptual hardening completed in v0.2.0.

This release does not introduce a new operating model. It aligns terminology, supporting documentation, architecture, examples, conformance guidance, and reader-facing summaries with the hardened specification before implementation testing begins.

Highlights

• Restored Adapt to the canonical terminology definition while preserving the explicit no adaptation required outcome.
• Clarified the distinction between execution-time AI reasoning and Stage 5: Adapt.
• Refined the top-level README so the introduction focuses directly on the methodology, with project history maintained in the dedicated History and Development document.
• Established a chronological public release history with links to detailed GitHub release notes.
• Removed the Design Guide section from primary site navigation while retaining the underlying documentation.
• Completed a repository-wide consistency review of the specification, principles, lifecycle, terminology, conformance model, architecture, examples, Design Guide, contributor templates, and reader-facing documentation.
• Aligned Classify with the canonical responsibilities of determining what was learned, whether adaptation is justified, and where resulting learning belongs.
• Completed Persist summaries and architecture views so they consistently represent all supported outcomes:
  • Persist validated learning.
  • Reinforce an existing validated operating pattern.
  • Explicitly resolve that no new persistent learning is justified.
• Clarified that movement across the Moving Determinism Boundary is an outcome of classification rather than a separate learning destination.
• Aligned the Design Guide with the final lifecycle, principle, and conformance terminology.
• Reinforced the canonical conformance structure of:
  • Eight principles.
  • Eight lifecycle stages.
  • Eight principle-aligned conformance assessments.
• Preserved the conformance relationship Requirements → Observable operation evidence → Conformance decision.
• Removed remaining supporting-document language associated with the former conformance-area model.
• Confirmed that successful no-change cycles still resolve lifecycle responsibilities and may reinforce existing validated patterns without manufacturing an adaptation.
• Updated the specification, website, versioning guidance, and release history to v0.2.1.

Issues Addressed

• #30 — Align supporting documentation with hardened specification requirements.
• #43 — Refine README history placement and establish release history timeline.
• #44 — Restore Adapt in the canonical terminology definition.
• #45 — Clarify execution-time AI reasoning versus the Adapt lifecycle stage.
• #49 — Remove Design Guide section from site navigation.

What This Release Represents

v0.2.1 completes the correction and consistency pass following v0.2.0. The conceptual specification is now internally aligned around its eight principles, eight-stage lifecycle, evidence-based conformance model, successful no-change behavior, and final Adapt → Validate → Persist semantics.

The specification is ready to serve as the basis for practical implementation exploration and testing.

v0.2.0 — Expanded Specification and Conformance Model

This release significantly expands and strengthens the Infoconex AI Flywheel Specification.

It completes the v0.2.0 conceptual milestone by refining the lifecycle, principles, learning model, validation requirements, persistence and reuse requirements, supersession model, and evidence-based conformance approach.

Key changes include:

• Clarified the complete Execute → Observe → Evaluate → Classify → Adapt → Validate → Persist → Reuse lifecycle.
• Defined explicit no-change and reinforcing-success paths so improvement does not require adaptation on every cycle.
• Defined validation sufficiency requirements for candidate changes and reusable learning.
• Defined what may qualify as persisted operational learning.
• Defined evidence requirements for demonstrating that persisted learning actually influences future execution.
• Defined how persisted learning may be challenged, superseded, deprecated, invalidated, rolled back, or retired.
• Strengthened the eight principles to reflect the completed lifecycle and learning model.
• Added independently assessable conformance criteria aligned to each principle.
• Updated architecture, examples, terminology, and supporting documentation for consistency with the completed model.
• Prepared the specification and documentation site for v0.2.0.
• Decoupled website asset cache busting from the specification version.

Specification v0.2.0 remains a draft and is intended for implementation testing, public review, further research, and continued refinement.

Infoconex AI Flywheel Specification v0.1.3

Summary

Draft specification release for Infoconex AI Flywheel Specification v0.1.3.

Changes

• Updates current specification version displays to v0.1.3.
• Uses lowercase v for reader-facing specification version references.
• Fixes stale documentation links after the software maintenance example reorganization.
• Improves Infoconex AI Flywheel naming consistency across reader-facing pages.
• Tightens conformance wording to distinguish self-assessed conformance from Infoconex approval, certification, or official status.
• Clarifies conformance requirement sources versus explanatory architecture support.
• Cleans up policy related-document self-links.
• Cleans up Markdown formatting issues found during final validation.

Validation

• Issue #17 acceptance criteria verified.
• Markdown relative links checked.
• Markdown final newlines, trailing whitespace, tabs, and code fences checked.
• git diff whitespace check passed.

v0.1.1 release

Summary

Draft content cleanup release for the AI Flywheel documentation.

Changes

• Applies minor documentation cleanup after the initial release.
• Refines early specification and repository content.
• Preserves the existing methodology while improving clarity and consistency.

Status

This is a pre-v1.0 draft release.

v0.1.2

Summary

Draft release adding GitHub Pages documentation site support.

Changes

• Adds GitHub Pages site functionality.
• Adds site navigation, search, responsive styling, and diagram interactions.
• Adds support for interactive Mermaid diagrams with fullscreen, zoom, and pan.
• Updates the displayed specification version to v0.1.2.
• Preserves the latest specification content from main.

Status

This is a pre-v1.0 draft release.

v0.1.0 initial preview release

AI Flywheel Specification 0.1 — Draft

This is the first public specification release of the AI Flywheel methodology.

The AI Flywheel is an evidence-driven operating model in which AI progressively builds, operates, observes, and improves the system by which work is performed.

Included in this release

• Formal AI Flywheel definition
• Eight core principles
• Eight-stage lifecycle
• Human authority and governance model
• Moving Determinism Boundary
• Authority Boundary
• Evidence-based conformance model
• Architecture and operating-model diagrams
• Worked examples
• Terminology
• Prior-art and framework-comparison research

Release status

Specification 0.1 is a working draft intended for public review, implementation experiments, and continued research. Terminology, conformance requirements, and supporting guidance may evolve before a stable 1.0 specification is published.

A loop repeatsx. A flywheel compounds.