Neuruh Research Series

JGI Organization Compiler

How Jeramie General Intelligence compiles the smallest effective temporary organization for a mission, routes each subtask to the right cognition, births and retires bots on evidence, and grows a swarm only while marginal information gain exceeds cost.

Source
JGI V6, Sections 18 to 25, 69, 96, 97, 170
Status
Founder working paper
Review
Not peer reviewed
Claim class
Internal engineering objective
Status note. JGI is an internal engineering objective. Do not publicly claim AGI, ASI, superintelligence, consciousness, sentience, or human-equivalent general intelligence merely because the system performs impressive autonomous work. Capability claims require evidence. Where the paper gives no formula, this page says so and labels the tool formula as an illustrative implementation of the paper concept. Token and dollar figures in the tools are illustrative rates, not measured costs.

What the Organization Compiler is

The Organization Compiler is the part of JGI that answers one question per mission: what is the smallest organization that can do this job well? It does not build a permanent department. It compiles a temporary organization from existing capabilities, temporary workers, and minimal bridges, runs the mission, and dissolves the organization when the mission ends. Only what proved reusable persists.

The twelve sections below are reproduced in full from JGI V6, in order. The five tools after them implement those sections as working calculators. Nothing in the tools invents a formula the paper gives; where a tool needs a number the paper does not supply, the number is labelled illustrative.

Section 18 Planner of Planners

PRIME should not always plan directly.

For complex missions: generate multiple independent plans.

Possible plan generators: PRIME, specialist worker, skeptical worker, economic optimizer, security critic.

Then evaluate them.

Plan utility: expected success, cost, time, risk, reversibility, resource contention, evidence quality.

Choose a winner.

Section 19 Recursive Decomposition

Mission decomposition continues until tasks are: independently executable, verifiable, resource-bounded, authority-classified, small enough to estimate.

Do not over-decompose.

Stop when coordination overhead exceeds decomposition benefit.

Section 20 Cognitive Router

JGI should select the right cognition for each task.

Options may include: PRIME, Grok specialist, large Grok swarm, Claude, GPT, local model, deterministic code, SQL, search, constraint solver, statistical model, human judgment.

LLMs are not automatically the best tool.

Route using: P(success), cost, latency, privacy, tool availability, historical reliability, verification burden.

Section 21 Model Performance Memory

For each cognitive worker maintain performance by task family.

Example: worker/model, domain, task type, attempts, passes, failures, Sentinel rejects, cost, latency, calibration, quality.

Estimate reliability with a Bayesian posterior.

Use this in future routing.

Section 22 Elastic Organization Creation

JGI may create temporary organizations for missions.

Example: MISSION CEO = PRIME. Temporary team: Research Lead, Repo Archaeologist, Engineer, Data Scientist, Economic Analyst, Adversarial Critic, Verification Specialist.

The team dissolves after the mission.

Permanent infrastructure should NOT be the default.

Section 23 Organizational Compiler

For a mission determine: required knowledge, required tools, required parallelism, required independence, required verification.

Then compile the smallest effective organization.

MissionOrganization = existing capabilities + temporary workers + minimal bridges

Section 24 Persistent Bot Birth

A new permanent Bot requires evidence.

Calculate: recurrence, unique context value, distinct ownership, independent schedule need, specialized tool need, long-term learning benefit, minus: coordination cost, role overlap, maintenance cost.

Create only when durable value exceeds cost.

All Bots need: birth reason, scope, authority, metrics, retirement condition.

Section 25 Bot Death

Periodically challenge every persistent agent.

If: low unique value, high overlap, rare usage, weak performance, then: extract useful skills, preserve memory, retire Bot.

JGI should be capable of simplifying itself.

Section 69 Self-Assembling Mission Systems

A mission may require a temporary mini-company.

JGI may assemble: workers, skills, data, tools, workflow, memory, budget.

Execute mission.

Then dissolve organization.

Persist only what proved reusable.

Section 96 Swarm Diversity

When using multiple agents, diversify: roles, prompts, sources, models, assumptions.

Twenty identical agents are not twenty independent opinions.

Section 97 Information Gain Per Agent

Spawn another worker only when: ExpectedInformationGain exceeds coordination + compute cost.

Stop swarm growth when marginal returns fall.

Section 170 Specialization Emergence

If one worker/model repeatedly excels at a task class: increase routing.

If a durable role emerges: consider Skill/Workflow/Bot.

Let specialization emerge from evidence.

Interactive Tools

All token and dollar figures in the tools below use illustrative rates stated next to each tool. The paper gives no token counts, no prices, and no numeric formulas for organization compilation, routing, bot birth, or swarm growth. The formulas here are labelled illustrative implementations of the paper concepts, and every one of them shows its arithmetic so you can check it by hand.

Tool 1. Mission Org Composer Sections 22, 23, 69

Pick an objective. The compiler returns the smallest competent team from the paper Section 22 role set, with a communication topology and a cost estimate.

Cost = total tokens x $5.00 per 1,000,000 tokens (illustrative rate). Total tokens = sum of per-role token estimates (illustrative).

Tool 2. Recursive Decomposition Planner Section 19

Enter a mission. The planner decomposes it until subtasks are independently executable, verifiable, resource-bounded, authority-classified, and small enough to estimate. It stops when coordination overhead exceeds decomposition benefit.

Coordination overhead = leaf subtasks x 150 tokens (illustrative). Depth 3 adds one verification child of 500 tokens per subtask (illustrative).

Tool 3. Cognitive Router Sections 20, 21

Enter a subtask. The router selects the right cognition from the paper Section 20 option list, using P(success), cost, latency, privacy, tool availability, historical reliability, and verification burden. Reliability comes from the built-in Model Performance Memory below, estimated as a Bayesian posterior.

Reliability = (1 + passes) / (2 + attempts). This is the paper Section 21 Bayesian posterior with a uniform prior, applied to the built-in performance memory (illustrative records).
3

Model Performance Memory (built-in records, illustrative)

WorkerTask familyAttemptsPassesFailuresReliability
ClaudeResearch201820.864
GPTCreative151230.765
Local modelConfidential10910.833
Deterministic codeCode252500.963
SQLData analysis212010.913
Human judgmentJudgment161510.889
PRIMEPlanning161420.833
Large Grok swarmResearch10820.750
SearchResearch252230.852

Tool 4. Bot Birth and Death Simulator Sections 24, 25, 170

Score a candidate permanent bot on the paper Section 24 factors. A bot is born only when durable value exceeds cost. Then run the Section 25 death challenge against the roster.

Durable value = sum of 6 benefit scores (0-10 each) minus sum of 3 cost scores (0-10 each). Birth when durable value is 12 or more. The 12-point threshold is illustrative; the paper gives no number.

Candidate bot

Persistent roster

Tool 5. Swarm Diversity and Information Gain Scorer Sections 96, 97, 170

Score a team on the five paper Section 96 diversity axes, then test whether adding another worker is worth it under Section 97: spawn only while expected information gain exceeds coordination plus compute cost.

Diversity = average of the 5 axis scores x 100. Effective independent opinions = team size x diversity / 100. Marginal gain of agent n = 10 x 0.7^(n-1) information units; coordination plus compute cost = 1.5 units per agent (both illustrative). Stop at the first agent whose marginal gain minus cost is below zero.

Specialization emergence Section 170

Enter a worker record. If one worker repeatedly excels at a task class, routing increases; if a durable role emerges, consider a Skill, Workflow, or Bot.

Reliability = (1 + successes) / (2 + attempts). A durable role is flagged when successes are 5 or more and reliability is 0.80 or more. Both thresholds are illustrative; the paper gives no numbers.