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    Google Releases Conductor: a context pushed Gemini CLI extension that shops data as Markdown and orchestrates agentic workflows

    Naveed AhmadBy Naveed Ahmad03/02/2026Updated:03/02/2026No Comments3 Mins Read
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    **Google’s Conductor Revolutionizes AI Code Generation with Gemini CLI**

    Hey there, fellow tech enthusiasts! Today I’m stoked to share with you a game-changing innovation from Google – Conductor, an open-source extension for Gemini CLI. This context-driven workflow is about to disrupt the way we approach AI code generation, and I’m excited to dive into its features and benefits.

    So, are we saying goodbye to those clunky chat-based coding sessions? You bet! Conductor is all about maintaining a persistent context list within the repository, capturing essential project info like product objectives, constraints, tech stack, workflow guidelines, and style guides as Markdown files. This ensures the AI conduct is repeatable across machines, shells, and team members.

    **How Conductor Works**

    To get started, simply install Conductor by running the command `gemini extensions set up https://github.com/gemini-cli-extensions/conductor –auto-update`. You’ll then have access to Conductor commands inside Gemini CLI when you’re in a project directory. The workflow begins with project-level setup using the `/conductor:setup` command. This interactive session helps build the base context by asking about the product, users, requirements, tech stack, and development practices. Conductor then generates a `conductor/` directory with several files that define the project’s technical direction and constraints.

    **Tracks: Organize Your Work like a Pro**

    Conductor introduces the concept of tracks, which represent models of work like features or bug fixes. You can create a track with a brief description or title, and Conductor will generate a directory under `conductor/tracks//` containing `spec.md`, `plan.md`, and `metadata.json`. These files define the detailed requirements and constraints for the track, as well as a step-by-step execution plan.

    **Implementing with Conductor: The Magic Happens**

    Once the plan is ready, you can hand over control to the agent using the `/conductor:implement` command. Conductor reads the `plan.md` file, selects the next pending task, and runs the configured workflow. Typical cycles involve inspecting relevant data and context, proposing code changes, running tests or checks, and updating job status in `plan.md` and global `tracks.md`.

    **What’s in Store with Conductor**

    This innovation offers a wide range of benefits, including:

    * A structured and repeatable approach to AI code generation
    * Persistence and version management of context and plans
    * Team-level conduct encoded in `workflow.md`, `tech-stack.md`, and style guide information files
    * Code evaluation and discussion of context and plans

    **Get Involved**

    If you’re curious about Conductor, be sure to check out the [repo](https://github.com/gemini-cli-extensions/conductor) and [technical details](https://builders.googleblog.com/conductor-introducing-context-driven-development-for-gemini-cli/). Let’s revolutionize the way we code with Conductor!

    Naveed Ahmad

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