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ADW System: Autonomous Developer Workflows

Production-grade multi-agent platform that transforms GitHub issues into working code through autonomous SDLC phases. Built on agentic coding principles with intelligent model routing (Claude Sonnet/Opus) achieving 70-78% token cost reduction.

Python
Claude Agent SDK
Multi-Agent
Production
CI/CD
localhost:3000
ADW System GitHub Integration

Key Impact: 12x speed improvement (60 min → 5 min) | 70-78% token reduction | 6,500+ lines of production code

Overview

Built on agentic coding principles, this production-grade platform transforms requirements into working code through autonomous multi-phase workflows. Features intelligent model routing (Sonnet/Opus) achieving 70-78% token cost reduction, pattern library matching for 90% first-attempt success rates, 14 composable workflow orchestrators, 35+ slash commands, and git worktree isolation for 15 parallel workflows.

Challenges

  • Designing multi-phase autonomous workflows that maintain code quality
  • Implementing intelligent model routing to optimize cost vs capability
  • Building pattern library matching for consistent first-attempt success
  • Creating robust git worktree isolation for parallel workflow execution

Results

  • Achieved 12x speed improvement on bug fixes (60 min → 5 min)
  • Reduced token costs by 70-78% through intelligent model routing
  • Built 6,500+ lines of production-grade code
  • 90% first-attempt success rate through pattern library matching

Interested in learning more about this project?

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Joe Dymnioski | AI Strategy & Engineering