Official COG Hub

COG

Collaborative Orchestration Governance

Advancing engineering AGI through collaborative orchestration governance. COG studies how AI can move from isolated capability demonstrations to planned, verifiable, reproducible, and collaborative engineering systems.

推进工程化 AGI 实现的人机协同治理框架。

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Governance Map

01 Planning
02 Evidence
03 Evaluation
04 Context Control
05 Orchestration
06 Reproducibility
From isolated capability demos toward planned, verifiable, reproducible engineering systems.

Research

Theory and definitions

Long-form notes on COG theory, AI engineering governance, orchestration, and evaluation.

Learn

Practical learning path

Educational articles and structured paths for understanding evidence-based AI engineering.

COG Eval

Evidence-based evaluation

A future product area for benchmark cards, runner evidence, and community retesting.

What is COG

A governance layer for human-AI collaboration in complex engineering.

COG focuses on planning, evidence, evaluation, context control, orchestration, and reproducibility. The aim is not to present another AI demo, but to make collaborative engineering work inspectable and repeatable.

Core loop

Plan
Execute
Collect evidence
Evaluate
Govern next session

Why now

AI engineering needs stronger operational governance.

AI capability is growing faster than engineering governance.

Complex engineering requires verifiable workflows.

Evaluation must become part of the production loop.

Human judgment remains central for complexity boundaries.

Featured research

Starting points for the COG knowledge base.

Mock research entries separate content from templates and prepare the site for future collections.

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COG Theory v0.1

COG: A Basic Definition

A concise working definition for Collaborative Orchestration Governance and its role in AI engineering.
AI Engineering v0.1

From Plan Mode to Eval-first Engineering

How plan-driven workflows become stronger when evidence, evaluation, and reproducibility are part of the loop.
Orchestration v0.1

Session Governance for Human-AI Collaboration

A research note on context boundaries, multi-session continuity, and reviewable agent work.

Learning path

Move from limits to orchestration.

  1. Start with AI engineering limits.
  2. Learn COG basic concepts.
  3. Practice with evidence-based evaluation.
  4. Move toward multi-session orchestration.

COG Eval preview

A future product area for reproducible AI engineering evaluation.

COG Eval will provide reproducible benchmark cards, runner evidence, by-case analysis, and community test submissions.

Explore COG Eval

Public Record

COG Theory Origin

Canonical definitions, version history, authorship records, and citation guidance.

Theory
Collaborative Orchestration Governance
Version
v0.1 static mockup
Record
Definitions, authorship, version history, and citation guidance.
Status
Canonical origin page placeholder