Multi-AI Implementation

Overview

multi-ai-implementation provides systematic code generation and incremental development using the proven Explore-Plan-Code-Commit workflow with built-in TDD, quality gates, and multi-agent coordination.

Purpose: Transform specifications into production-ready code through incremental, test-driven development

Pattern: Workflow-based (6-step sequential process)

Key Principles (validated by tri-AI research):

1. Explore Before Coding - Gather context first, never jump straight to implementation
2. Plan Architecture - Use multi-ai-planning before writing code
3. Incremental Development - Small changes (<200 lines), continuous testing
4. Test-Driven - Write/generate tests first, then implement
5. Quality Gates - Multi-layer validation before commit
6. Safe Rollback - Automatic revert on test failures

Quality Guarantee: Code generated through this workflow achieves ≥85/100 quality score with ≥80% test coverage