2.2.2 – Self-Compliance & Hygiene Edition

Historic milestone: CORE successfully governed its own major refactoring cycle with zero constitutional violations maintained throughout.

Changed

• Completed deep modularity refactoring (4 big files → 17 focused single-responsibility modules)
• Hardened Mind/Will/Body separation (fixed layer leaks, tracing exclusions, race conditions)
• Switched planning to deterministic passive_gate (no more unnecessary LLM calls)
• Unified IntentGuard.check_transaction API for cleaner constitutional validation
• Major repository hygiene cleanup (removed .archive/, binary/temp files, updated .gitignore)

Removed

• Legacy .archive/ directory
• Temporary refactor cast files (core-refactor.cast)
• Any leftover sensitive or unnecessary files

Notes

• Real self-governance in action: the constitutional runtime actively flagged issues during development
• Technical debt reduced further, codebase now even cleaner and more maintainable
• Ready for next leap toward A3 strategic autonomy

This release is dedicated to perfect hygiene and self-compliance. Thank you to everyone following the journey!

v2.2.0 — Universal Workflow Pattern

🎯 Universal Workflow Pattern — The Operating System

This release establishes the foundational architecture for autonomous operations at scale. CORE now has a universal orchestration model that closes all loops, enables self-correction everywhere, and provides the substrate for fully autonomous conversational operation.

Philosophy Shift

Before 2.2.0: Collection of autonomous capabilities with ad-hoc orchestration
After 2.2.0: Universal workflow pattern that composes all operations

What Changed

Universal Workflow Pattern — Every autonomous operation follows:

INTERPRET → ANALYZE → STRATEGIZE → GENERATE → EVALUATE → DECIDE

Component Architecture — 40+ components organized by constitutional phase:

• Interpreters (INTERPRET) - Parse intent
• Analyzers (PARSE) - Extract facts
• Evaluators (AUDIT) - Assess quality
• Strategists (RUNTIME) - Make decisions
• Orchestrators (RUNTIME) - Compose workflows

Self-Correcting Loops — Pattern-based adaptation:

• "Did result improved?" - Relative quality
• "SOLVED?" - Multi-dimensional gate
• "Continue trying?" - Holistic termination

What This Enables

✅ Now: Universal pattern for all autonomous operations
🔄 Soon (Q1 2026): Full core CLI conversational autonomy
🎯 Future: A3 Strategic Refactoring, Web/API interfaces

Migration Status

• Foundation documented (3 papers)
• Pattern compliance: ~12% complete
• 2 commands using pattern (clarity, test generation)
• 11 commands pending migration

Full details: See CHANGELOG.md

The workflow closes all loops — that's why this release is foundational.

v2.0.0 - A2 Autonomy Achieved: Autonomous Code Generation

🎯 Major Milestone: A2 Autonomy Achieved

CORE has achieved Level 2 Autonomy - autonomous code generation with constitutional governance.

🚀 Key Achievements

• ✨ 70-80% autonomous code generation success rate (up from 0%)
• 🎯 100% semantic placement accuracy (up from 45%)
• 🧠 Semantic infrastructure operational: 513 symbols, 66 module anchors, 48 policy chunks
• 🛡️ Constitutional compliance enforcement preventing AI agents from "going off the rails"
• 🔄 Enhanced self-healing with autonomous remediation

📊 The Autonomy Ladder

✅ A0: Self-Awareness          Knowledge graph, symbol vectorization
✅ A1: Self-Healing            Autonomous fixes for drift, formatting, compliance
✅ A2: Code Generation         Create new features with constitutional governance
🎯 A3: Strategic Refactoring   Next frontier - multi-file architectural improvements
🔮 A4: Self-Replication        Write CORE.NG from scratch

🏗️ What's New

Autonomous Code Generation

• Context-aware code generation with rich semantic understanding
• AI agents operate within defined "autonomy lanes" with constitutional boundaries
• Semantic search and graph traversal for accurate code placement
• Policy-aware code generation ensuring constitutional compliance

Semantic Infrastructure

• 513 symbols vectorized in knowledge graph
• 66 module anchors for semantic code placement
• 48 policy chunks enabling AI understanding of governance rules
• Architectural context builder for system-wide awareness

Constitutional Governance

• Active monitoring with violation tracking and autonomous remediation
• Micro-proposal system for safe, auditable changes
• Cryptographic signing for constitutional amendments
• Continuous audit preventing AI agents from exceeding safe boundaries

Quality Improvements

• Test coverage tracking (48-51%, target 75%)
• Test success rate: 0% → 70-80%
• Service Registry architecture with dependency injection
• Enhanced database integration and secrets management

📖 Full Details

See CHANGELOG.md for complete release notes.

🔒 Constitutional AI Governance

CORE's innovation is making AI autonomy safe and auditable:

• All policies stored as human-authored YAML
• AI agents bounded by explicit permissions
• Quorum-based approval for governance changes
• Semantic policy understanding by AI
• Continuous compliance monitoring

Result: Powerful AI agents that are provably bounded by human-defined constraints.

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Installation: See README.md for setup instructions.

v1.0.0 - A1 Release

Changelog

All notable changes to this project will be documented in this file.

[1.0.0] - A1 Release - 2023-10-01

Added

• A1 Autonomy Activated: The system can now autonomously execute simple, self-healing tasks via the micro-proposal workflow.
• Database as Single Source of Truth: All operational knowledge (CLI commands, LLM resources, cognitive roles, domains) is now managed in a PostgreSQL database, eliminating YAML file drift.
• Transactional Integration Workflow: The core-admin submit changes command now performs a multi-stage, transactional integration process that is automatically rolled back on any failure, ensuring repository integrity.
• Autonomous Capability Definition: The system can now autonomously analyze new, untagged code and propose dot-notation capability keys using semantic context from its vector database.
• Refactored CLI with Verb-Noun Grammar: All core-admin commands have been refactored into a clear, predictable verb-noun structure (e.g., check audit, manage database).
• Explicit Dependency Injection: Introduced CoreContext to explicitly pass shared services, removing global singletons and improving testability.

Changed

• Consolidated Architecture: Refactored system/ and agents/ directories into a clean, layered architecture under src/ (core, features, services, shared).
• Consolidated SQL Migrations: All database migrations are now in a single, idempotent 001_consolidated_schema.sql file for simplicity and clarity.
• Upgraded to pydantic-settings: Configuration management now uses the modern pydantic-settings for environment variable loading.

Fixed

• Vectorization Service: The vectorization pipeline was repaired and now correctly uses CognitiveService for generating embeddings.
• Numerous Import Paths: Corrected dozens of import paths to align with the new, consolidated src/ architecture.

v0.2.0

v0.2.0 — MVP: Autonomous Application Generation (2025-08-15)

Highlights

• First MVP that can autonomously scaffold a governed application from a high-level goal.
• Nightly constitutional audit + capability drift checks in CI.
• Starter Kit: default profile shipped.
• CLI: core-admin new, core-admin agent scaffold, core-admin proposals ....

Upgrade notes

• Use Python 3.11+.
• Install with poetry install.
• Run checks locally: black --check . && ruff check . && pytest.