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Forge: Multi-Agent Code Fixes
See a multi-agent system that automatically generates, tests, diagnoses, and fixes code using architectural patterns until it passes all tests.
Forge solves the fundamental problem with AI code generation: tools generate fast but have no quality control, no institutional memory, and can’t fix their own mistakes. Every generation starts from scratch with the same errors repeating.
This demo shows a multi-agent orchestration system where specialized AI agents coordinate to produce production-ready code through intelligent iteration. Testing agents run security scans, performance benchmarks, and functional tests. When tests fail, review agents analyze root causes and coordinate generation agents to apply fixes using a library of 28 proven architecture patterns. The system loops until all tests pass—automatically.
You’ll see the complete workflow: plain English requirements decomposed into tasks, parallel code generation using KnowledgeForge patterns, automated testing that catches real issues, AI-powered diagnosis tracing failures to root causes, and iterative fixes applied until the codebase is deployable. The live demo shows actual test failures, the diagnostic reasoning, and automated remediation in under 60 seconds.
This isn’t prompt engineering or chat interfaces. It’s agents managing agents—planning, generating, testing, diagnosing, fixing, and deploying without human intervention between requirement and production-ready result. Built with Claude Sonnet 4, Docker-isolated testing, and semantic search across engineering patterns. Open source, working production tool, building real applications today.