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

Google has launched Conductor, an open supply preview extension for Gemini CLI that turns AI code era right into a structured, context pushed workflow. Conductor shops product data, technical choices, and work plans as versioned Markdown contained in the repository, then drives Gemini brokers from these recordsdata as an alternative of advert hoc chat prompts.

From chat based mostly coding to context pushed improvement

Most AI coding at the moment is session based mostly. You paste code right into a chat, describe the duty, and the context disappears when the session ends. Conductor treats that as a core drawback.

As a substitute of ephemeral prompts, Conductor maintains a persistent context listing contained in the repo. It captures product objectives, constraints, tech stack, workflow guidelines, and magnificence guides as Markdown. Gemini then reads these recordsdata on each run. This makes AI conduct repeatable throughout machines, shells, and staff members.

Conductor additionally enforces a easy lifecycle:

Context → Spec and Plan → Implement

The extension doesn’t leap instantly from a pure language request to code edits. It first creates a monitor, writes a spec, generates a plan, and solely then executes.

Putting in Conductor into Gemini CLI

Conductor runs as a Gemini CLI extension. Set up is one command:

gemini extensions set up  --auto-update

The --auto-update flag is non-compulsory and retains the extension synchronized with the most recent launch. After set up, Conductor instructions can be found inside Gemini CLI if you find yourself in a mission listing.

Undertaking setup with /conductor:setup

The workflow begins with mission degree setup:

This command runs an interactive session that builds the bottom context. Conductor asks concerning the product, customers, necessities, tech stack, and improvement practices. From these solutions it generates a conductor/ listing with a number of recordsdata, for instance:

• conductor/product.md
• conductor/product-guidelines.md
• conductor/tech-stack.md
• conductor/workflow.md
• conductor/code_styleguides/
• conductor/tracks.md

These artifacts outline how the AI ought to purpose concerning the mission. They describe the goal customers, excessive degree options, accepted applied sciences, testing expectations, and coding conventions. They reside in Git with the remainder of the supply code, so adjustments to context are reviewable and auditable.

Tracks: spec and plan as top quality artifacts

Conductor introduces tracks to characterize items of labor reminiscent of options or bug fixes. You create a monitor with:

or with a brief description:

/conductor:newTrack "Add darkish mode toggle to settings web page"

For every new monitor, Conductor creates a listing beneath conductor/tracks// containing:

• spec.md
• plan.md
• metadata.json

spec.md holds the detailed necessities and constraints for the monitor. plan.md accommodates a stepwise execution plan damaged into phases, duties, and subtasks. metadata.json shops identifiers and standing info.

Conductor helps draft spec and plan utilizing the present context recordsdata. The developer then edits and approves them. The essential level is that each one implementation should comply with a plan that’s express and model managed.

Implementation with /conductor:implement

As soon as the plan is prepared, you hand management to the agent:

Conductor reads plan.md, selects the subsequent pending job, and runs the configured workflow. Typical cycles embody:

1. Examine related recordsdata and context.
2. Suggest code adjustments.
3. Run assessments or checks in accordance with conductor/workflow.md.
4. Replace job standing in plan.md and world tracks.md.

The extension additionally inserts checkpoints at part boundaries. At these factors Conductor pauses for human verification earlier than persevering with. This retains the agent from making use of giant, unreviewed refactors.

A number of operational instructions assist this movement:

• /conductor:standing exhibits monitor and job progress.
• /conductor:evaluate helps validate accomplished work in opposition to product and magnificence pointers.
• /conductor:revert makes use of Git to roll again a monitor, part, or job.

Reverts are outlined by way of tracks, not uncooked commit hashes, which is simpler to purpose about in a multi change workflow.

Brownfield tasks and staff workflows

Conductor is designed to work on brownfield codebases, not solely contemporary tasks. Whenever you run /conductor:setup in an current repository, the context session turns into a strategy to extract implicit data from the staff into express Markdown. Over time, as extra tracks run, the context listing turns into a compact illustration of the system’s structure and constraints.

Crew degree conduct is encoded in workflow.md, tech-stack.md, and magnificence information recordsdata. Any engineer or AI agent that makes use of Conductor in that repo inherits the identical guidelines. That is helpful for imposing take a look at methods, linting expectations, or accredited frameworks throughout contributors.

As a result of context and plans are in Git, they are often code reviewed, mentioned, and adjusted with the identical course of as supply recordsdata.

Key Takeaways

• Conductor is a Gemini CLI extension for context-driven improvement: It’s an open supply, Apache 2.0 licensed extension that runs inside Gemini CLI and drives AI brokers from repository-local Markdown context as an alternative of advert hoc prompts.
• Undertaking context is saved as versioned Markdown beneath conductor/: Recordsdata like product.md, tech-stack.md, workflow.md, and code type guides outline product objectives, tech selections, and workflow guidelines that the agent reads on every run.
• Work is organized into tracks with spec.md and plan.md: /conductor:newTrack creates a monitor listing containing spec.md, plan.md, and metadata.json, making necessities and execution plans express, reviewable, and tied to Git.
• Implementation is managed by way of /conductor:implement and track-aware ops: The agent executes duties in accordance with plan.md, updates progress in tracks.md, and helps /conductor:standing, /conductor:evaluate, and /conductor:revert for progress inspection and Git-backed rollback.

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