Phase 4: Recursive Self-Improvement - Bootstrap Achievement

[abrichr]

Phase 4: Recursive Self-Improvement

The ultimate goal: OpenAdapt can record and improve its own development process.

Vision

OpenAdapt building OpenAdapt - Full recursive bootstrap where the system can:

1. Record any development task on command
2. Create new workflows programmatically
3. Improve existing workflows
4. Self-optimize based on execution metrics

Recursive Levels

Level 1: Record Development Tasks ✅

Status: Achieved in Phase 1

Record specific tasks:

• Generate screenshots
• Run tests
• Create PRs

Level 2: Record Workflow Creation

Goal: Record the process of creating a new workflow

# Record the meta-workflow
with WorkflowRecorder(
    name="create_workflow",
    description="Record the process of creating a new workflow"
) as recorder:
    # Manually create a new workflow:
    # 1. Create new file in workflows/
    # 2. Implement Workflow subclass
    # 3. Add to __init__.py
    # 4. Create example usage
    # 5. Add tests
    pass

# Now replay to create new workflows programmatically!
executor = WorkflowExecutor(
    workflow_name="create_workflow",
    parameters={
        "workflow_name": "my_new_workflow",
        "description": "What it does"
    }
)
result = executor.execute()
# New workflow created automatically!

Level 3: Record Recording Process

Goal: Record the process of recording a workflow

# Record the meta-meta-workflow
with WorkflowRecorder(
    name="record_workflow",
    description="Record the process of recording a workflow"
) as recorder:
    # Manually record a workflow:
    # 1. Start WorkflowRecorder
    # 2. Perform task
    # 3. Stop recorder
    # 4. Verify manifest created
    pass

# System can now record arbitrary tasks on command!
executor = WorkflowExecutor(
    workflow_name="record_workflow",
    parameters={
        "task_description": "Open browser and navigate to URL",
        "workflow_name": "browser_navigation"
    }
)
result = executor.execute()
# New workflow recorded automatically!

Level 4: Full Bootstrap

Goal: System can improve any part of itself

User provides high-level goal:

"Improve screenshot workflow to be 50% faster"

System:

1. Records current workflow execution
2. Analyzes performance bottlenecks
3. Records improved version
4. Evaluates improvement
5. Deploys if better

Tasks

1. Meta-Workflow: Create Workflow

• Record creating a new workflow file
• Record implementing Workflow subclass
• Record adding to __init__.py
• Record creating example usage
• Record adding tests
• Test replaying to create new workflow

Deliverable: Can create new workflows programmatically

2. Meta-Workflow: Record Workflow

• Record starting WorkflowRecorder
• Record performing a task
• Record stopping recorder
• Record verifying manifest
• Test replaying to record arbitrary tasks

Deliverable: Can record new workflows on command

3. Workflow Optimization

• Collect execution metrics (time, CPU, errors)
• Identify bottlenecks
• Propose optimizations
• A/B test original vs optimized
• Deploy better version

Example metrics:

• Execution time
• Success rate
• Resource usage
• User intervention required

Files: playback/optimization.py, playback/metrics.py

4. Workflow Library Expansion

Use meta-workflows to create:

• Test execution workflow
• PR creation workflow
• Documentation update workflow
• Benchmark evaluation workflow
• Model training workflow

Each created programmatically via the "create workflow" meta-workflow!

5. Self-Improvement Loop

1. Execute workflow → Collect metrics
2. Analyze performance → Identify issues
3. Propose improvements → Record new version
4. A/B test → Compare metrics
5. Deploy better version → Update library
6. Repeat

Files: playback/self_improvement.py

6. Autonomous Development Agent

Vision: User gives high-level goal, system executes

User (on mobile): "Add dark mode to benchmark viewer"

System:
1. Searches for similar workflows
2. Records implementation (or uses existing workflow)
3. Runs tests
4. Generates screenshots
5. Creates PR
6. Posts result to GitHub for user review

Files: playback/autonomous_agent.py

7. Documentation

• Document recursive levels achieved
• Add examples for each meta-workflow
• Create video demos
• Write blog post/paper on approach

Files: docs/RECURSIVE_BOOTSTRAP.md, docs/examples/

Dependencies

• All previous phases complete
• Metrics collection infrastructure
• A/B testing framework
• Claude Code for high-level reasoning

Success Criteria

✅ Level 1: Record development tasks (Phase 1)
✅ Level 2: Programmatically create new workflows
✅ Level 3: Record arbitrary tasks on command
✅ Level 4: Self-optimize workflows based on metrics
✅ Autonomous: Execute high-level goals without human intervention

Philosophical Implications

This achieves true recursive self-improvement:

• System can modify its own code
• System can improve its own efficiency
• System can create new capabilities
• System documents its own behavior

But safely:

• All changes version controlled (Git)
• A/B tested before deployment
• Human reviews via GitHub PRs
• Transparent execution logs

Estimated Effort

20-30 hours (meta-workflows, optimization, autonomous agent, documentation)

But: Each subsequent task gets faster as system improves itself!

Related Issues

• Depends on: Phase 4: Recursive Self-Improvement - Bootstrap Achievement #4 (Phase 3: GitHub Integration)
• Enables: Truly autonomous OpenAdapt development

Resources

• Recursive Self-Improvement in AI
• AutoGPT - Similar autonomous agent concept
• Self-Modifying Code