The Practical Guide to an Iterative Feedback Loop (No Fluff)

Most developers treat AI coding agents like a magic wand. You prompt, it spits out code, you copy-paste, and then you spend the next hour fixing the bugs it introduced. That isn't engineering; it’s gambling. If you want to actually ship production-grade software with an agent, you need a system that forces discipline rather than just speed. That’s exactly why EvanFlow is changing the game for Claude Code users.

Here’s the reality: most agents fail because they lack a feedback loop. They hallucinate values, drift from the original intent, and ignore the fundamental constraints of your codebase. EvanFlow solves this by turning the development process into a series of gated checkpoints. You aren't just asking an agent to "write a feature"; you’re orchestrating a workflow where the agent brainstorms, plans, executes, and iterates—all while you hold the keys to the kingdom.

Why TDD is the Only Way to Scale AI

The biggest mistake I see developers make is treating Test-Driven Development as an afterthought. They write the code first, then ask the agent to "write some tests." That’s backwards. In the EvanFlow model, TDD is the primary discipline inside every single task.

When you run a task, the agent doesn't just dump code into your files. It follows a strict RED → GREEN → REFACTOR cycle. It writes one failing test, implements the absolute minimum code to pass it, and then refactors while the test is still fresh. Because these tests verify behavior through public interfaces, they actually survive your refactors. If you aren't using a TDD-driven iterative feedback loop to manage your agent's output, you’re essentially flying blind.

The Five Failure Modes You Must Watch

Why does this matter? Because of the "Five Failure Modes." Research shows that agents are prone to hallucinated actions, scope creep, cascading errors, context loss, and tool misuse. EvanFlow bakes a checklist into the evanflow-iterate skill to catch these before they hit your main branch.

Here’s where most people get tripped up: they let the agent commit code automatically. Never do this. EvanFlow explicitly stops short of every git operation. It forces you to review the diff, run the quality checks, and verify the UI changes yourself. If the agent tries to auto-stage or auto-commit, it’s a red flag that you’ve lost control of the process.

How to Start Using EvanFlow

You don't need to overhaul your entire workflow to see the benefits. Start by installing the plugin via the Claude Code marketplace: /plugin install evanflow@evanflow. Once it’s active, stop treating your agent like a junior dev who needs constant hand-holding. Instead, give it a clear directive: "Let's evanflow this."

The orchestrator will then walk you through the brainstorm and planning phases. If your plan involves multiple independent units, it will even fork into a parallel coder/overseer setup. This is where the real power lies—having an overseer subagent that can’t modify code but can review the coder’s work against your integration tests.

Does this add a bit of ceremony? Sure. But it’s the kind of ceremony that prevents a 2:00 AM production outage. If you’re tired of cleaning up after your AI, try this today and share what you find in the comments.