Why I Started Splitting Planning, Implementation, Testing, and Documentation in AI Workflows

The author identified two key problems in AI coding workflows: unnecessary cost from using the same model for all stages, and context pollution when a single agent handles everything in one conversation. To solve this, they built agentflow, a CLI tool that splits AI workflows into distinct phases (planning, implementation, testing, documentation), each with its own context window and appropriate model, resulting in improved test coverage and earlier issue detection.