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Original documentation, preserved from the repository. Historical projections and scenario ambitions are not evidence of live performance. See the current readiness record for deployment requirements.

AGI Jobs v0 (v2) — Demo → Kardashev II Omega Grade α AGI Business 3 → Kardashev II Omega Grade Alpha AGI Business 3 Demo Ultra

Current operating path

Open the Business 3 workbench guide for the shared website, bounded launch commands, ten computer-work templates and approved-task worker integration. Run npm run demo:kardashev-business:serve from the repository root.

This directory implements a synthetic orchestration simulation. Its token, energy, planetary and validator metrics are not evidence of live settlement, physical infrastructure or production-ready autonomous work. The preserved architecture below describes the intended system; qualify a live deployment using the workbench guide.

Overview

This Python demo models job orchestration, resource accounting and governance. The ASCII-safe launchers provide stable entry points into the canonical implementation. The shared workbench adds task specifications, reproducible evidence checks and an explicit adapter path to a separately configured worker.

Capabilities

Systems Map

Architecture diagram · source preserved below
View original Mermaid source
flowchart LR
    Operators((Mission Owners)) --> demo_Kardashev_II_Omega_Grade___AGI_Business_3_kardashev_ii_omega_grade_alpha_agi_business_3_demo_ultra[[Demo → Kardashev II Omega Grade α AGI Business 3 → Kardashev II Omega Grade Alpha AGI Business 3 Demo Ultra]]
    demo_Kardashev_II_Omega_Grade___AGI_Business_3_kardashev_ii_omega_grade_alpha_agi_business_3_demo_ultra --> Core[["AGI Jobs v0 (v2) Core Intelligence"]]
    Core --> Observability[[Unified CI / CD & Observability]]
    Core --> Governance[[Owner Control Plane]]

Working With This Module

  1. Follow the current operating guide above for the exact command for this engine. Use Python 3.12 from the repository root; the selected Python launch paths use the standard library.
  2. Run npm run demo:kardashev-business:smoke to check all five engines with temporary state and process timeouts.
  3. Run the focused regression and browser checks documented in the workbench guide. Passing them qualifies the tested local behavior, not a live production deployment.
  4. Keep simulation state separate from live job evidence. Qualify the provider, tool permissions, independent reviewer and settlement integration before real operation.

Directory Guide

Key Directories

Key Files

Quality & Governance

Next Steps

Verify admission separately from completion

A finite run can exit successfully while work is still pending. Inspect mission_admission in the emitted status snapshot and the mission_plan_partial or mission_plan_seeded event. planned_count, admitted_count, missing_paths and finalized_count come from the actual local registry. all_admitted does not imply all_work_finalized. No live execution or settlement is attested.

The default supplied plan admits four of its five nodes with current capacity; the remaining node is refused rather than silently expanding the resource budget. To examine a fully admitted smaller plan, use the included single-node variant:

python -m demo.kardashev_ii_omega_grade_alpha_agi_business_3_demo_ultra launch --cycles 3 --no-sim --config 'demo/Kardashev-II Omega-Grade-α-AGI Business-3/kardashev_ii_omega_grade_alpha_agi_business_3_demo_ultra/config/bounded-admission.json'

It preserves the original resource capacities and selects only the existing root job. The observed short run admits one of one requested jobs, with finalization still pending. Use a fresh working/output directory when retaining separate runs. The full original mission and diagrams remain available for partial-admission study.

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