AI coding agents often hallucinate dependencies and ignore project standards, creating a frustrating development experience. Google's new Conductor extension for Gemini CLI aims to solve this by introducing Context-Driven Development. It shifts planning from ephemeral chat windows into persistent markdown files within your codebase, ensuring the agent understands your project's architecture before writing a single line of code.

The setup process is straightforward. Running `/conductor:setup` guides you through creating key artifacts like `product.md` and `product-guidelines.md`. This forces a deliberate planning phase. You define your product vision, target audience, and coding standards upfront. This approach works for both new and existing brownfield projects, giving the AI a crucial memory it traditionally lacks.

Conductor manages work through tracks. When you request a feature, like adding authentication, it generates a detailed `spec.md` and `plan.md`. The agent then executes this plan phase-by-phase, creating Git commits with detailed notes for each task. This workflow enforces test-driven development and requires manual verification between phases, preventing the "house of cards" collapse common in AI-generated code.

The result is a robust, auditable development cycle. By forcing the agent to 'measure twice, code once,' Conductor transforms unreliable 'vibe coding' into a disciplined partnership. It allows developers to safely implement complex features in unfamiliar stacks, turning the AI from a forgetful intern into a reliable senior engineer with a persistent, provable trail of work.