Raw capture โ€” raw/workgraph.md


url: https://github.com/graphwork/workgraph date_fetched: 2026-07-05 backfilled: true


The work OS for human/AI organizations.

WG stands for works good.

Agents can come and go. The graph remains.

WG records what needs doing, who or what claimed it, what blocked it, what evidence was produced, where judgment entered, what failed, what was retried, and how the work changed over time.

Launch the operating surface:

wg tui

Most AI systems center the agent. WG centers the work.

AI can generate more work than humans can inspect.

WG exists because the hard problem is no longer only execution. It is knowing what was done, what failed, what evidence exists, where judgment entered, and how the organization should respond.

Generation, evidence, validation, repair, and human judgment stay in the same durable structure โ€” so judgment can catch up to generation instead of being flattened by it.

WG is not primarily a chatbot, an agent benchmark harness, a project-management app, or an agent orchestration framework (LangGraph, CrewAI, AutoGen).

Those categories center messages, scores, tickets, or agents.

WG centers answerable work: tasks with dependencies, claims, evidence, validation, failures, handoffs, artifacts, and history.

WG was not designed by starting with agents and adding orchestration.

It started from a theory of organizations: work needs decomposition, dependency, role, motivation, coordination, evaluation, memory, and adaptation.

The implementation maps those organizational primitives into a working system. Read the theory โ€” it is foundational, not optional, reading.

Poietic PBC was formed, organized, and grant-funded through WG. These are not demos. They are public traces of real institutional work:

The company is not a wrapper around the product. The company is an output of the product.

cargo install --git https://github.com/graphwork/wg
wg init
wg tui
wg init --route claude-cli                                  # Claude (default)
wg init --route codex-cli                                   # Codex
wg init -m nex:qwen3-coder -e https://your-endpoint:8080    # any OpenAI-compatible
wg service start
wg tui

The loop: declare work, let the service dispatch it, watch the graph evolve.

Everything lives in .wg/:

.wg/
  graph.jsonl         # task graph (one JSON object per line)
  config.toml         # configuration
  agency/             # roles, tradeoffs, agents, evaluations
  service/            # runtime state (daemon PID, registry, logs)
  functions/          # workflow templates

Plain text. Diffable. Inspectable without the tool. If wg disappeared tomorrow, the work would still be there.

Watch the organization think.

MIT