| name | Nate B. Jones — Orchestration Intelligence |
| description | Multi-agent coordination architecture using the DPVI pattern (Decompose-Parallelize-Verify-Iterate) and harness-first design principles |
Nate B. Jones — Orchestration Intelligence
The jagged frontier of AI is not a property of intelligence — it's an artifact of missing organizational structure. Apply human team management principles to agents, and the frontier smooths.
Core Capability
Design, audit, and optimize multi-agent orchestration systems using the DPVI pattern — the convergence architecture independently built by Anthropic, Google DeepMind, OpenAI, and Cursor. This skill treats harness design (memory, task files, progress tracking, restart procedures) as the primary determinant of agent success, not model intelligence. It classifies work by domain verifiability to determine safe delegation levels.
What This Skill Produces
| Workflow | Output |
|---|
| Orchestration Architecture Blueprint | Complete multi-agent design with planner-worker-judge hierarchy and verification loops |
| Harness Design Audit | Agent scaffolding evaluation with gap analysis and fixes |
| Domain Verifiability Mapper | Work classification into machine-checkable / expert-checkable / unverifiable tiers |
| Sniff-Check Protocol Builder | Evaluation criteria and quality gates for any domain |
| Bloat-to-Depth Optimizer | Multi-agent simplification plan that strips overhead while preserving capability |
| Orchestration Telemetry Feedback | Self-optimizing layer — instruments coordination decisions, detects inefficiency patterns, feeds retrospectives into future runs |
When to Deploy
- Designing a new multi-agent system or coordinating >3 agents
- Agents are capable but inconsistent — suspect harness issues
- Deciding what work to delegate to agents vs. retain for humans
- Agent system growing complex and showing diminishing returns
- Building evaluation criteria for AI-generated work in any domain
- Multi-agent pipeline runs repeatedly and should get more efficient over time
Stacking Opportunities
- + Nick Saraev (Agentic Workflows): Self-annealing + harness design = self-correcting agent systems
- + Oren (Taste Mastery): Sniff-check protocols + CEV evaluation = formal quality layer for agent outputs
- + Nate B. Jones (Agent Deployment Strategy): Deployment + orchestration = complete agent lifecycle coverage
- + Nate B. Jones (Intent Engineering): Specification width + DPVI decomposition = bulletproof task design
Key Principles
- Harness before intelligence — Fix scaffolding before upgrading models
- Simplify before complexifying — Remove coordination layers before adding them
- convergence as proof — If independent actors build the same thing, adopt it
- Verifiability determines delegation — What you can sniff-check, you can delegate
- Organizational intelligence scales — Human team patterns generalize to agents
Load Order
- Load
genius.md (required — all patterns + hidden knowledge)
- Load specific workflow for task
- Cross-reference
agent-deployment-strategy/genius.md for deployment context
