From GitHub Issue to Merged PR: My Complete AI-Powered Development Workflow

A few months ago, I was burning through an embarrassing amount of Claude tokens monthly while shipping maybe two meaningful features. The wake-up call came during a debugging session where I spent the better part of an hour having Claude explain why the same function worked differently in different contexts—only to discover I'd been feeding it outdated code samples from three iterations ago. The Cost of Wing-It Development Here's what broken AI development looks like: you start a conversation with Claude about adding user authentication, thirty messages later you're discussing database migrations, then somehow you're refactoring your entire error handling system. Each context switch burns tokens, and worse, the AI starts hallucinating solutions based on code it thinks exists but doesn't. I was treating Claude like Stack Overflow with a conversation interface—throwing problems at it reactively instead of systematically. The result? Half-implemented features, context drift that made debu