Your AI agent is making 50 implicit decisions per task. You see zero of them.

Tell Claude Code or Copilot to "build a REST API for a todo app." It'll do it. You'll get working code. But along the way it silently chose: the framework, the ORM, the naming convention, the error handling strategy, the test structure, the validation approach, the status codes, the folder layout. Fifty-plus decisions. You saw none of them. Three features later, you notice your tests are inconsistent. The auth middleware uses a pattern that conflicts with the error handler. The folder structure doesn't scale. You didn't choose any of this, the AI did, and it never told you. This is the actual problem with agentic coding. Not that the code is bad. It's that you lost control of the architecture without realizing it. So I built Defer. Defer is an open-source CLI that sits between you and your AI. You describe a task. The agent decomposes it into explicit decisions with concrete options and tradeoffs. You choose how much you care about each domain, mark it auto (agent decides, you challeng