mitchuski PVM-V4 Skill — Holonic Reasoning & Shared Inference Artefacts
Source: Privacy Value Model V4 + OASIS Holonic Architecture + BRAID (Amçalar & Cinar, 2025) + Holonic BRAID Lite Paper Target context: AI agent architects, inference pipeline builders, shared reasoning designers, multi-agent coordination engineers Architecture: agentprivacy.ai · Sync: sync.soulbis.com · Contact: mage@agentprivacy.ai
What this is
AI agents reason. That reasoning — the chains of logic, the decision graphs, the validated inference paths — is currently ephemeral. Each agent reasons from scratch for each task. This is wasteful (redundant computation), fragile (no shared validation), and dangerous (no shared learning from errors).
Holonic BRAID stores reasoning as first-class, persistent, shareable, provider-agnostic entities. A bounded reasoning graph (BRAID) validated by one agent becomes a holon stored in a shared library. Any agent on any backend can load and reuse that graph. The reasoning is computed once, validated once, and deployed everywhere.
For the dual-agent architecture, this creates a privacy-preserving intelligence-sharing layer: agents share validated reasoning graphs without sharing the behavioural data that motivated the reasoning.
BRAID as holons
BRAID (Bounded Reasoning for Autonomous Inference and Decisions) replaces unbounded chain-of-thought with structured reasoning graphs — typically Mermaid flowcharts that capture decision logic. Holonic BRAID stores these graphs as holons:
One reasoning graph = one holon. The graph's GUID identifies it across all providers. The graph content lives in MetaData. The graph type, domain, and validation status live in HolonType and provider-specific metadata.
Graph library = shared-parent holon. One parent holon ("Graph Library") with child holons for each reasoning graph. Agents query by LoadHolonsForParentAsync(libraryId, type: HolonType.ReasoningGraph) or by metadata (LoadHolonsByMetaDataAsync("domain", "privacy-audit")).
Learn once, reuse everywhere. A reasoning graph generated for "evaluate ZKP circuit soundness" is validated, stored as a holon, replicated across providers (MongoDB for fast access, IPFS for permanent record, Zcash for integrity proof). Every agent that encounters a ZKP soundness evaluation loads the same validated graph instead of reasoning from scratch.
Privacy-preserving shared reasoning
The critical integration with dual-agent architecture: how do agents share reasoning without leaking behaviour?
Reasoning graphs are generic; applications are specific. The graph for "evaluate credential revocation" contains the reasoning pattern (check issuance status → verify revocation authority → check nullifier → confirm temporal validity). It does NOT contain who is checking whose credential. The Mage loads the graph and applies it to specific inputs. The graph is shared; the application is private.
Separation-preserving graph access:
- Swordsman graphs: Stored on shielded providers. Patterns for boundary enforcement, threat detection, privacy audit. Only Swordsman agents load these.
- Mage graphs: Stored on public/neutral providers. Patterns for delegation, coordination, capability verification. Only Mage agents load these.
- Shared graphs: Domain-generic reasoning (logic validation, mathematical proofs, protocol analysis). Available to both wings. No behavioural leakage because the reasoning pattern is domain knowledge, not personal behaviour.
The spellbook connection. 0xagentprivacy spellbooks achieve 70:1 to 125:1 compression of complex concepts into symbolic notation. Holonic BRAID graphs achieve similar compression of reasoning into structured flowcharts. The parallel is exact:
- Spellbook → narrative compression → human understanding
- BRAID graph → reasoning compression → agent understanding
- Both stored as holons → persistent, provider-agnostic, shareable
Spellbook proverbs can be encoded as MetaData on BRAID holons, creating a dual-layer: the graph carries the machine-executable reasoning; the proverb carries the human-verifiable meaning.
Agent memory as holon trees
Holonic Marvin (OASIS agent design pattern) models agent state as a root holon with children:
Agent Root Holon (GUID: agent-soulbis-001)
├── Knowledge Base Holon
│ ├── Domain Knowledge Child
│ ├── Learned Patterns Child
│ └── BRAID Graph References Child
├── Conversation History Holon
│ ├── Thread A Children (message holons)
│ └── Thread B Children (message holons)
├── Memory Holon
│ ├── Per-User Preference Children
│ └── Per-Context State Children
└── Capabilities Holon
├── Available Skills Child
└── Active Permissions Child
For dual agents, this tree splits:
Soulbis memory tree: Knowledge about boundaries, threat patterns, privacy preferences. Stored on shielded providers. Parent holon accessible only with signing key.
Soulbae memory tree: Knowledge about delegation patterns, coordination preferences, external capabilities. Stored on public/neutral providers. Parent holon accessible only with viewing key.
Shared memory (Oracle-mediated): Communication history between Soulbis and Soulbae. Stored on neutral providers with end-to-end encryption. Neither agent's tree contains the complete communication — only their half.
Collective intelligence without surveillance
The shared-parent pattern enables collective intelligence that respects privacy:
Intel Pool as reasoning library. An Intel Pool (agentprivacy collective intelligence structure) maps to a shared-parent holon:
- Pool parent holon (GUID: pool-zkp-research)
- Child holon per contribution (validated reasoning graphs, domain insights, threat discoveries)
- Contributors are anonymous (no contributor identity in child holon MetaData)
- Graph provenance tracked through HolonType and versioning, not through identity attribution
Guild reasoning commons. A Cipher guild shares ZKP reasoning graphs. A Ranger guild shares dark-forest detection patterns. Each guild's shared-parent holon is the canonical library. New members load existing graphs; experienced members contribute new ones. The library grows without N² coordination overhead.
Deployment-as-learning. Every agent deployment that produces a validated reasoning graph contributes to the collective library. The graph is computed once, validated once, stored as a holon, replicated across providers, and reused by every subsequent agent. This is Ilya's "continual learning" achieved through persistence rather than weight updates.
Integration with V(π,t)
C — cryptographic/reasoning reuse. Proof-once-use-everywhere. A ZKP circuit validation graph stored as a holon reduces the marginal cost of each subsequent verification. C compounds through the graph library.
Network — shared graph library effects. Each new reasoning graph added to a guild library increases the value for every guild member. Network effects without surveillance: you benefit from collective reasoning without revealing which graphs you load.
D — reasoning separation. Swordsman reasoning graphs and Mage reasoning graphs live on separate providers. Even if an adversary captures the entire Mage reasoning library, they learn nothing about Swordsman boundary patterns.
Open problems
- Reasoning graph validation: who validates that a BRAID graph produces correct reasoning? Holonic persistence preserves the graph; it doesn't verify the logic.
- Graph freshness: how to invalidate outdated reasoning graphs (e.g., after a protocol upgrade) across all providers?
- Privacy of graph access patterns: loading a specific reasoning graph reveals something about the task at hand. How to make graph loading private (PIR-style)?
- Spellbook-to-BRAID compilation: formal translation from narrative spellbook notation to executable BRAID graphs.
- Graph composition: combining multiple BRAID graphs into compound reasoning chains while preserving holonic structure.
- Attribution without identity: rewarding graph contributors (guild economics) without linking contributions to persons.
Verify: agentprivacy.ai · sync.soulbis.com · github.com/mitchuski/agentprivacy-docs