Autonomous Workflows Explained

SiftCoder’s magic lies in its autonomous multi-agent workflows. Let’s peek under the hood.

The Multi-Agent Architecture

SiftCoder uses specialized AI agents, each with specific expertise:

Planner Agent

• Analyzes requirements and specifications
• Breaks down features into implementable tasks
• Creates detailed implementation plans
• Identifies dependencies and risks

Coder Agent

• Implements code following detected patterns
• Writes tests for all implementations
• Follows project conventions exactly
• Generates clean, maintainable code

QA Reviewer Agent

• Validates implementations against acceptance criteria
• Runs comprehensive tests
• Identifies issues and deviations
• Ensures quality standards

QA Fixer Agent

• Fixes identified issues
• Re-runs tests to validate fixes
• Ensures no regressions
• Maintains code quality

Investigator Agent

• Safely explores codebases read-only
• Understands code behavior
• Investigates bugs and issues
• Provides detailed analysis

Documenter Agent

• Generates comprehensive documentation
• Creates API references
• Writes user manuals
• Maintains docs up-to-date

The Execution Model

Workflows follow this cycle:

Plan → Code → Review → Fix → Validate → Continue

Each agent hands off to the next, with automatic continuation until:

• All features are complete
• User pauses the workflow
• An issue requires manual intervention

State Persistence

SiftCoder maintains state across the entire workflow:

• Features: Tracked queue with status
• Progress: Saved after each subtask
• Checkpoints: Named restore points
• Knowledge: Patterns learned from codebase

Autonomous vs Interactive

Workflows can run:

• Fully Autonomous: From spec to deployed app
• Interactive: With user approvals at key points
• Paused: Resume later with /siftcoder:continue

Customizing Workflows

You can control workflow behavior:

# Set focus to specific area
/siftcoder:focus src/components

# Pause workflow
/siftcoder:pause

# Resume workflow
/siftcoder:continue

# Check status
/siftcoder:status

Real-World Impact

Teams using autonomous workflows report:

• 10x faster feature development
• 80% reduction in manual reviews
• 95% reduction in bugs reaching production
• 3x increase in developer satisfaction

Conclusion

Autonomous workflows aren’t just faster—they’re better. Each agent brings specialized expertise, and their collaboration produces higher quality code than any single developer could achieve alone.

Ready to try? Run /siftcoder:build with your spec and watch the magic happen!