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Measuring and Managing Autonomy

Autonomy from a business and systems point of view can be challenging to manage. This project defines a framework by which managing and measuring autonomy can be designed and implemented.

Most organizations manage autonomy implicitly — it emerges from trust, tenure, and accidents of structure, and is therefore felt but not measured, expanded but never designed, and revoked arbitrarily. This framework makes autonomy an explicit, designed, measurable property of the organization.

The framework in one diagram

flowchart LR
    A[Design<br>decision + blast radius] --> B[Grant<br>autonomy contract]
    B --> C[Measure<br>ledger + telemetry]
    C --> D[Manage<br>expand / contract / re-shape]
    D -->|re-grant, next horizon| B

What's here

Document Purpose
Framework Definitions, the three axes, the five levels (L0–L4), autonomy contracts
Maturity model Six dimensions × five levels grid, scoring rules, the Autonomy Ledger
Assessment The questionnaire and scoring procedure — the practical instrument
Governance loop Grant → Instrument → Observe → Review, with cadence and anti-patterns
Positioning Related work, lineage, open questions, BibTeX
Worked example One team, scored end to end, producing a governance move
AI agents as units First-pass extension: scoring agent units with the same instrument
Ledger format Machine-readable Autonomy Ledger (YAML v1) + health checks
Contract template Autonomy contract + review agenda, ready to copy
Versioning Ruleset/ledger versioning policy — how assessments stay comparable
Changelog Every change, classified by comparability impact

Install

No Python needed — standalone binaries for macOS, Linux, and Windows are attached to each GitHub Release: download autonomy-score-<os>-<arch> and ledger-health-<os>-<arch>, mark them executable, run.

With Python 3.9+ (installs the autonomy-score and ledger-health commands):

pipx install measuring-autonomy    # or: pip install measuring-autonomy

From a clone, the zero-install form keeps working with no packaging step: python3 tools/autonomy_score.py ... (the tools/ scripts are shims over src/measuring_autonomy/).

Quick start: score a team

python3 tools/autonomy_score.py 1 3 2 2 1 1 --current 1

Scores are D1 clarity, D2 capability, D3 guardrails, D4 telemetry, D5 transparency, D6 accountability (0–4 each). The tool applies the weakest-link rule — min(guardrails, telemetry, accountability) — and outputs the safe grant level and recommended move.

python3 tools/autonomy_score.py --self-test   # verify the scoring rules

Track granted autonomy in a machine-readable Autonomy Ledger (v1 YAML format, examples/ledger.yaml) and check its health:

python3 tools/ledger_health.py examples/ledger.yaml   # requires PyYAML (pip install pyyaml)

Try it without a terminal

A dependency-free web version of the assessment lives in site/ (and is published to GitHub Pages when enabled — repo Settings → Pages → Source: GitHub Actions). Open site/index.html locally, tick the items with evidence, and print the scorecard.

The three questions

  1. Design — What autonomy should this unit have, and why? → contracts
  2. Measurement — How much autonomy exists, and how well is it used? → maturity model + assessment
  3. Management — When should autonomy expand, contract, or re-shape? → governance loop

Roadmap

See docs/roadmap.md. Current status: v0.1 draft — the written framework, maturity model, and assessment instrument are complete; next up are validation against real teams and optional tooling.

Contributing

Feedback, corrections, and real-world applications are very welcome — see CONTRIBUTING.md. Use the issue templates to report framework feedback or submit a case study.

License

MIT

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