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The Problem I Kept Running Into

I was trying to build a system where AI agents could handle complex software projects. You know the kind: "Build me an authentication system with OAuth, JWT, rate limiting, and comprehensive tests."

Traditional agentic frameworks can branch and loop, but they have a limitation: every branch needs predefined instructions. You must write the task descriptions upfront for every scenario you anticipate.

But what about discoveries you didn't anticipate? When a testing agent finds an optimization opportunity, a security issue, or a better architectural pattern?

Here's what I tried instead: Define logical phase types that are needed to solve problems - like "Plan → Implement → Test" - and let agents create tasks in ANY phase based on what they discover.

What Actually Happened: A Branching Tree That Builds Itself

Instead of a rigid sequence, I set up phase types:

• Phase 1 (Analysis): Understanding, planning, investigation
• Phase 2 (Implementation): Building, fixing, optimizing
• Phase 3 (Validation): Testing, verification, quality checks

The key insi...