PACT-AX provides primitives for safe collaboration, context sharing, and knowledge transfer between heterogeneous AI agents. Built on the principle that trust scales while control just moves bottlenecks, PACT-AX enables distributed AI collaboration that mirrors the best of human teamwork.
Emotional Intelligence + Artificial Intelligence
PACT-AX integrates human collaboration wisdom with AI technical capabilities:
- Jazz-like improvisation for small-scale agent interactions
- Symphonic coordination for large-scale agent orchestration
- MVI (Minimum Viable Intervention) - maximum collaboration impact with minimal overhead
- Organic trust building through continuous interaction rather than one-time verification
neurobloom.ai Ecosystem
├── PACT-HX (Human Experience Layer) [Planned]
│ ├── Collaborative improvisation frameworks
│ ├── Universal translator for human "operating systems"
│ ├── Designed serendipity with neural rewiring/unwiring
│ └── Leadership multiplication protocols
│
└── PACT-AX (Agent Communication Layer) [This Repository]
├── Context Sharing primitives
├── State Transfer protocols [In Development]
├── Policy Alignment mechanisms
└── Trust Scoring systems
Safe and interpretable context exchange between agents
from pact_ax.primitives.context_share import ContextShareManager
manager = ContextShareManager("agent-001")
context_packet = manager.create_context_packet(
target_agent="agent-002",
context_type="task_knowledge",
payload={
"current_task": "customer_support",
"priority": "high",
"context": "User needs help with billing issue"
}
)Seamless agent handoff protocols inspired by organizational learning theory
- 360-degree awareness checkpoints before critical transfers
- Wealth transfer protocols for capability and knowledge distribution
- Organic resumption after pause states
Cross-agent coordination and conflict resolution
- Generative vs Degenerative Friction detection
- Both/And Intelligence for paradox navigation
- Dynamic collaboration mode switching (Jazz ↔ Symphony)
Confidence levels for agent interactions based on continuous relationship building
- Trust as continuous process, not one-time verification
- Pattern recognition for authentic vs artificial behavior
- Network effects - each interaction strengthens the trust fabric
Agents naturally gravitate toward high-quality collaboration partners rather than forcing interactions.
Build feedback processing capability as deliberately as you build core features.
Creating infrastructure for the next 20 years of human+AI collaboration.
When agents operate from abundance consciousness, collaboration becomes effortless and generative.
from pact_ax.primitives.context_share import ContextShareManager
from pact_ax.primitives.trust_score import TrustManager
# Initialize collaboration managers
context_manager = ContextShareManager("my-agent")
trust_manager = TrustManager("my-agent")
# Share context with trusted agent
if trust_manager.get_trust_score("partner-agent") > 0.7:
context_packet = context_manager.create_context_packet(
target_agent="partner-agent",
context_type="collaborative_task",
payload={"status": "ready_for_handoff"}
)
context_manager.send_context(context_packet)- Individual Mastery → Small Group Jazz → Large Scale Symphony
- Solo thinking → Intimate collaboration (3-4 agents) → Orchestrated coordination (100+ agents)
- No failures, only iterations of learning and expansion
- Always arriving imperfect but arriving beautifully
- Organic timing over forced milestones
- Continuous trust building through authentic interaction
- Network effects - each successful collaboration strengthens the whole
- Quality over quantity in collaboration partnerships
We welcome contributions from developers who share our vision of joyful, abundant collaboration between AI agents.
Our Approach:
- Organic development - let features emerge from real needs
- Both technical excellence AND human wisdom - EI+AI integration
- Open source abundance - share knowledge freely to create more value for everyone
See CONTRIBUTING.md for guidelines.
PACT-AX draws inspiration from diverse sources:
- Organizational Learning Theory (Ray Dalio's Principles)
- Jazz Improvisation Dynamics (collaborative creativity research)
- Abundance Economics (Naval Ravikant's leverage principles)
- Systems Thinking (complex adaptive systems)
- Contemplative Traditions (patience, presence, organic unfolding)
- GitHub Discussions: Share ideas and collaborate on features
- Discord: Real-time conversation with other builders
- Newsletter: Updates on neurobloom.ai ecosystem development
MIT License - see LICENSE file.
Built with 🎵 by the neurobloom.ai community.
Where Artificial Intelligence meets Emotional Intelligence, and collaboration becomes an art form.
neurobloom.ai Team
"We are conduits of creation, building the infrastructure for human potential in the AI age."