Specflow

AI Copilots are writing 40-80% of enterprise code, but they hallucinate. When developers use GitHub Copilot, Cursor, or Claude Code: AI hallucinates because it lacks accurate context about what code should do Documentation doesn't exist or is outdated in 90% of legacy codebases Code and specs drift apart the moment implementation changes Developers can't trust AI suggestions without time-consuming manual verification The result: Teams spend more time debugging AI-generated code than writing it themselves. The Solution SpecFlow is a verification system that eliminates AI hallucination by giving copilots formal specifications to reference and validating every change against them. How It Works Specification Generation For new features: Generate formal specs from natural language descriptions For legacy code: Auto-generate specs from existing implementations (Cold Start) AI Copilot Integration Native MCP (Model Context Protocol) integration with Claude Code, Cursor, and other AI development tools AI reads specs before generating code, ensuring accuracy from the start Automated Drift Detection After every code change, SpecFlow validates implementation against specification Prevents code-documentation drift automatically Intelligent Review Queue Minor drift auto-resolves with spec updates flagged for review Major conflicts require explicit developer decision Everything tracked with full audit trail