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Autoloom

Governance Engineering for Coding Agents

Every changemade by a Coding Agent,backed by inspectable evidence.

Weave goals, constraints, engineering methods, action judgments, and verification evidence into agent execution.

Judge before acting, change the next step during execution, and retain reviewable facts and unknowns at delivery.

Download for Windows

Windows x64 · Connect your own model · v0.1.0-alpha.10 · 248 MB

Before · Governance impact
Autoloom governance impact card in English
During · Full trajectory
Autoloom trajectory page in English40-second real task
Delivery · Governance record
Autoloom governance record in English
  1. 1Governance intentGoals and constraints
  2. 2Action judgmentFindings and methods
  3. 3Execution impactChange the next step
  4. 4Evidence recordFacts and unknowns

Governance Engineering

What is Governance Engineering?

Governance is not a report generated after the task. It participates before action, changes the next step during execution, and leaves reviewable facts and unknowns at delivery.

  1. 01Governance intent

    Goals, constraints, acceptance

  2. 02Action judgment

    Findings, methods, impact

  3. 03Execution impact

    Change operations and checkpoints

  4. 04Evidence record

    Execution facts, results, unknowns

Autoloom governance impact card in English

Engineering means governance can enter execution, leave evidence, and withstand review.

01

Executable

A governance judgment must affect the next step, not only produce prose.

02

Traceable

Move from a result back to judgments, tool calls, and source facts.

03

Reviewable

Separate confirmed facts, inferences, and unresolved unknowns.

Rules become part of how the Agent works instead of sitting outside the workflow.

A governance method must change the next step.

Finding: the change is complete, but there is no actual post-change test result.

Action effect: run the existing tests and use their output to decide whether the issue is fixed.

Change necessity

Avoid changing code for its own sake.

Systematic diagnosis

Make the next step answer the observed cause.

Structural entropy control

Limit unrelated changes and duplicate owners.

Evidence-backed delivery

Separate what ran from what it established.

Aegis × Autoloom

One governance approach. Two ways to use it.

Add a standalone method pack to an existing Coding Agent, or use Autoloom with governance checkpoints, trajectory, and records integrated into execution.

Open-source Method Pack

Aegis

Install governance methods in Coding Agent hosts that support Skills.

  • Works across hosts
  • Open methods and workflows
  • Evolves in the Aegis repository
Explore Aegis
Governed Coding Agent

Autoloom

Combines methods, execution checkpoints, full trajectory, and governance records in a Windows product.

  • Enters relevant judgment points during execution
  • Keeps trajectory and governance records inspectable
  • No separate Aegis installation
Watch the real demo

Both follow the same Governance Engineering direction while keeping product, installation, and release ownership clear.

One change leaves four layers of reviewable evidence.

These facts enter the Session record, connecting the result back to the original execution.

  1. 01

    Goal and sources

    Scope, acceptance, relevant sources

  2. 02

    Action judgment

    Finding, method, action effect

  3. 03

    Execution facts

    Tools, command results, file observations

  4. 04

    Delivery record

    Result, evidence references, unknowns

Trajectory makes execution reviewable.

Inspect context, model output, tool calls, arguments, results, and timing by turn.

Autoloom trajectory page in English
Request contextTool resultResult submission

Governance organizes scattered facts into one record.

Move from the overview into action assessments, checkpoints, execution facts, and work results.

Autoloom governance record in English

Governance impact → Checkpoint → Execution facts → Result record

The record supports review; it is not a guarantee that the task is correct.

See Governance Engineering enter a real task in 40 seconds.

  1. 1Find the issue
  2. 2Form governance impact
  3. 3Apply the change
  4. 4Run existing checks
  5. 5Record the result
This demo3 failures → 4 passing1 implementation file changedExisting tests unchanged

The boundaries must be as clear as the governance.

Permission mode
Determines what the Agent may read, change, or execute.
Model connection
Uses a supported account or API configuration.
Project location
The workspace is local; model requests may send relevant context.
Session record
Tasks, tool results, and governance facts remain inspectable.

Start a reviewable task.

  1. 1Download the Windows client
  2. 2Connect a model
  3. 3Open a project and describe the goal and acceptance

The client is free. Your selected provider charges for model usage.

About Governance Engineering

Does governance slow the Agent down?

Governance enters only at relevant decision points and reuses the same Agent and Session. Actual cost depends on the task, model, and checks.

Does a governance record mean the result is correct?

No. It records grounds, execution facts, and unknowns. It does not replace user acceptance or guarantee correctness.

Where does project data go?

The workspace stays on your computer or connected SSH host. Model requests may send relevant context to the selected provider, depending on the task and configuration.

Which actions need authorization?

Permission mode determines what the Agent may read, change, or execute. Actions that need confirmation ask before execution.

Make the next change inspectable.