This release adds 3 notable features for engineering teams evaluating rollout.
Published 2mo
AI Agents & Assistants
✓ No known CVEs patched
✓ No known CVEs patched in this version
Summary
AI summaryAgents can autonomously synthesize, test, propose, and deploy new capabilities with full audit trails.
Full changelog
Phase 4: Agent Autonomy — Self-Extension
Agents autonomously synthesize, test, propose, and deploy new capabilities.
Self-Modification Cycle
- Gap Detection: Autonomy loop finds no capability matching intent
- Synthesis: Generate new capability from gap description
- Autonomous Testing: Create and run test cases (80% mock pass rate)
- Proposal: Submit to quorum for multi-agent approval
- Deployment: Register in execution engine immediately on approval
- Usage: Agent can now use newly deployed capability
Integration Points
- AutonomyLoop (v2.7.0): Calls process_gap when no capability found
- CapabilitySynthesis (Phase 3): Optional integration for advanced synthesis
- AgentQuorum (Phase 3): Proposal voting mechanism
- ExecutionEngine (v2.6.0): Capability registration and deployment
Key Features
- Autonomous synthesis: Agents generate capability names, descriptions, and pseudo-code
- Built-in testing: Synthesized capabilities auto-tested before proposal
- Decentralized approval: Quorum votes on new capabilities (multi-agent governance)
- Full history: Complete audit trail of gaps, syntheses, tests, deployments
- Multi-agent isolation: Each agent's self-extension is independent
Capability Properties
- Name: Auto-generated from intent keywords
- Description: Semantic description of capability purpose
- Input/Output Schema: Defined during synthesis
- Implementation Sketch: Pseudo-code template for implementation
- Confidence Score: 0.0-1.0 agent confidence in synthesis
- Test Success Rate: Pass rate from autonomous testing
What This Enables
- Open-ended agent autonomy: Agents no longer limited to pre-defined capabilities
- Adaptive problem-solving: Agents synthesize capabilities for unforeseen challenges
- Collective intelligence: Quorum voting prevents bad syntheses from deploying
- Runtime extensibility: New capabilities available immediately after approval
- Self-improving loops: Agent can observe patterns and synthesize optimizations
Example Flow
Agent pursuing goal: "deliver notifications"
↓ detect gap: no notify capability
↓ process_gap("send notifications to users")
↓ synthesis: synthesize_notify_capability
↓ test: run test cases (4/5 pass = 80% success)
↓ propose: submit to quorum
↓ quorum approves: 3/4 agents vote yes
↓ deploy: register notify_sender to execution engine
↓ resume goal: now execute execute_step with new notify_sender capability
Test Coverage
- 15 integration tests, all passing
- Gap detection and recording
- Capability synthesis with metadata
- Autonomous testing with pass rates
- Proposal to quorum
- Deployment to execution engine
- Full cycle gap → synthesis → test → deploy
- Synthesis history tracking
- Gap resolution status transitions
- Integration with execution engine
- Multi-agent isolation
- Self-modification metrics
Architecture
All systems operate in embedding space:
- Gaps recorded with semantic intent descriptions
- Synthesized capabilities have semantic descriptions
- Quorum proposals include semantic context
- Execution engine registers by capability ID
- Full causality chain: intent → gap → synthesis → test → proposal → deployment
Progression
- v2.6.0: Execution + Reasoning (19 tests)
- v2.7.0: Autonomy Loop (9 tests)
- v2.8.0: Self-Modification (15 tests, total 43/54)
- v2.9.0: Self-Improvement (11 tests planned)
- v3.0.0: Complete Autonomous Agent (15+ tests planned)
Phase 4 Progress: 43/54 tests (80%)
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Earlier breaking changes
- v5.7.32 Web dashboard removed; operator panel is canonical UI
Beta — feedback welcome: [email protected]