To address the pain point of difficult context persistence in AI programming, Google has recently launched an open-source preview extension called Conductor. As an extension of the Gemini CLI, Conductor transforms AI code generation into structured, context-driven automated workflows.
Traditional AI-assisted programming typically follows a session-based model, and once the session ends, related product background and technical decisions are often lost. The innovation of Conductor lies in storing product knowledge, technical constraints, and work plans as versioned Markdown files within the code repository. This means that the Gemini agent can read these persistent contexts each time it runs, ensuring consistency and reproducibility of AI behavior across different machines and team members.
In practice, Conductor follows a rigorous lifecycle of "context → specification and plan → execution." Through simple interactive settings, the system automatically generates configuration files including product guides, technology stacks, workflows, and code standards. In addition, Conductor introduces the concept of "Tracks" (task tracking), treating each feature development or bug fix as an independent unit and requiring a clear execution plan before executing code changes.
Currently, this tool is open-sourced under the Apache 2.0 license. The Google research team stated that Conductor is not only suitable for new projects but also helps existing codebases make implicit technical decisions explicit, achieving deeper collaboration transparency between AI and human developers through Git management.
Link: https://developers.googleblog.com/conductor-introducing-context-driven-development-for-gemini-cli/
Key Points:
📂 Persistent Context: Conductor stores the background information required by AI as Markdown and includes it in Git management, completely ending the context loss issue caused by "session-based programming."
📑 Standardized Workflow: Introduces a task tracking (Tracks) mechanism, requiring AI to first develop and pass human-reviewed specifications (Spec) and plans (Plan) before writing code.
🚀 Efficient Command-Driven: Supports project initialization through
/conductor:setup, automatic task execution through/conductor:implement, and provides status queries and Git-level rollback functionality.
