Master Gemini CLI's Conductor: The AI-Powered Development Workflow That Actually Works

The Problem Nobody Talks About

You've probably experienced the frustration: you're bouncing between a chat window and your IDE, losing context across sessions, watching AI suggestions drift away from your project's actual constraints. Your codebase has specific patterns, testing strategies, and architectural decisions, but every time you ask your AI assistant for help, you have to re-explain the entire project from scratch.

This is exactly the problem Conductor solves.​

Conductor is a preview extension for Google's Gemini CLI that fundamentally changes how you work with AI-powered development. Instead of relying on temporary chat logs that vanish when you close the window, Conductor roots everything in your codebase itself—persistent Markdown files that become the single source of truth for your AI agent.​

The philosophy is deceptively simple: you stay in control, and your AI works smarter.

What Is Conductor, Exactly?

Conductor is built on a concept called "context-driven development." Rather than diving straight into implementation, you first formalize your intent—your product goals, tech stack, architectural patterns, testing strategies, and workflow preferences. These live as persistent artifacts (Markdown files) inside your repository.​

Here's the genius part: Conductor doesn't just store this context. It uses it to guide every single interaction between you and the Gemini AI agent. The AI understands your project deeply, respects your constraints, and generates code that feels like it was written by someone who actually knows your codebase.​

This is particularly powerful for brownfield projects—existing, mature codebases where AI tools typically struggle. Conductor's philosophy is pragmatic: when you introduce it to an existing project, it initiates an interactive session to help you document your architecture, guidelines, and goals. As you build new features, Conductor updates this shared context, so its knowledge grows alongside your project.​

The Core Workflow: Three Essential Commands

Conductor revolves around three key commands that form a complete development cycle:

1. /conductor:setup – Establish Your Foundation

This is where it all begins. Running /conductor:setup initializes your Conductor context within your repository. During this interactive session, you'll define:​

• Your product: What are you building? What problems does it solve?

• Your tech stack: Languages, frameworks, databases, deployment platforms

• Workflow preferences: Your testing strategy, code review process, naming conventions, documentation standards

• Architectural guidelines: Design patterns, folder structure, performance constraints

Once you establish this foundation, it becomes shared context for your entire team. Every team member running Conductor commands gets the same project understanding—meaning new features built by different people feel cohesive, as if written by a single engineering team.​

2. /conductor:newTrack – Plan Before You Code

When you're ready to tackle a new feature or bug fix, newTrack initializes what Conductor calls a "track"—a high-level unit of work with formal structure.​

Instead of immediately jumping into implementation, Conductor helps you generate two critical artifacts:

1. A specification (spec.md): A detailed, structured description of what you're building, including requirements, acceptance criteria, and edge cases

2. A plan (plan.md): A phased, step-by-step implementation roadmap that breaks the feature into discrete, checkable tasks

Conductor suggests answers based on the context you set up earlier, so building high-quality specs becomes fast and natural. This is the game-changer: you review and approve the plan before any code is written, keeping you firmly in control.​

3. /conductor:implement – Let Your AI Work (Safely)

Once you approve the plan, /conductor:implement unleashes your coding agent. Here's what makes it different from traditional chat-based AI tools:​

• The agent works through your plan.md, checking off tasks as it completes them

• Because state is saved in a file, you can pause, step away, and resume later without losing your place

• You have checkpoints for reverting to previous versions if something goes wrong

• You can edit the plan mid-flight if requirements shift

The AI stays within the guardrails you've established, following your architecture, testing strategy, and coding standards.​

Installation: Get Started in Minutes

Getting Conductor running takes just a few steps:

Prerequisites

• Gemini CLI installed (if you don't have it, run npm install -g @google/gemini-cli)

• Authentication with your Google account

Installation Command

bash

gemini extensions install https://github.com/gemini-cli-extensions/conductor

That's it. Conductor is now installed and ready to use.​

Step-by-Step: Using Conductor on Your First Project

Step 1: Navigate to Your Project

bash

cd /path/to/your/project gemini

Step 2: Initialize Conductor Context

text

/conductor:setup

Follow the interactive prompts to define your product, tech stack, and workflow. Conductor will suggest sensible defaults based on what it detects in your repo.

Step 3: Create a New Track

text

/conductor:newTrack

Describe the feature or bug fix you want to tackle. Conductor generates a spec and plan for your review.

Step 4: Review and Approve

Read through the generated spec.md and plan.md files. Edit them if needed—this is your chance to steer the direction before code touches your repository.

Step 5: Implement

text

/conductor:implement

Watch as Gemini works through your plan, completing tasks systematically while staying within your project's constraints.

Why Conductor Changes the Game

For Individual Developers:

• Stop re-explaining your codebase to your AI assistant every session

• Get AI suggestions that actually respect your architecture and style

• Review implementation plans before code is written

• Pause and resume work seamlessly across different machines

For Teams:

• Standardize how AI agents approach coding tasks across your engineering team

• New team members get instant context about project goals and constraints

• Code generated by AI feels consistent, as if written by your entire team

• Shared context accelerates onboarding and reduces context-switching overhead

For Complex Projects:

• Conductor excels at features more intricate than simple code edits

• Persistent documentation becomes your single source of truth

• Structured planning catches edge cases and requirements gaps before implementation

• Safe iteration through checkpoints and version management

Key Differences from Traditional Gemini CLI Chat

Real-World Example: Building a New API Endpoint

Let's say you're adding a payment webhook handler to your Node.js backend. Here's how Conductor takes you through it:

Step 1: Setup (first time only)
You define that you're building a TypeScript microservice, you use Jest for testing, you follow a repository pattern for data access, and you have strict error handling requirements.

Step 2: New Track
You ask Conductor to "Add a webhook handler for Stripe payment events." Conductor generates:

• A spec outlining the webhook signature validation, event handling, database updates, and retry logic

• A plan with discrete tasks: create the endpoint, validate signatures, add test cases, integrate with existing services

Step 3: Review
You spot that the plan doesn't include logging for audit compliance—you add that requirement to the plan.

Step 4: Implement
Conductor's agent builds the webhook handler, following your TypeScript patterns, using your testing framework, and respecting your error handling standards. You can watch progress in the plan.md file.

In a traditional chat, you'd have explained all of this context multiple times across sessions. Conductor does it once, then uses that intelligence across every future feature.

Pro Tips for Getting the Most Out of Conductor

1. Be thorough during setup: The time you invest in /conductor:setup pays dividends. Define your architecture, constraints, and workflow carefully.

2. Review plans critically: The specification and planning phase is where you catch misunderstandings early. Spend time here—it's the most valuable stage.

3. Update context as you grow: As your project evolves, update your Conductor context files. This keeps your AI agent in sync with your current reality.

4. Use for complex features: Conductor shines on substantial, multi-step features. For tiny one-off edits, traditional chat might be faster.

5. Leverage checkpoints: If an implementation goes sideways, use Conductor's checkpoint system to revert safely.

The Future of AI-Assisted Development

Conductor represents a shift in how developers will interact with AI agents. Instead of dumping prompts into a chat window, you're treating documentation and planning as managed artifacts. Your repository becomes a dynamic, evolving specification that guides every AI interaction.

Google is just getting started—they've committed to significant improvements for brownfield projects in the coming months, particularly in understanding project history and architecture nuance.​

Final Thoughts

If you've been frustrated with AI development tools that lose context, ignore your coding standards, or require constant context-switching, Conductor is worth your immediate attention. It's currently in preview, which means it's still evolving, but the core philosophy—context-driven development with human developers firmly in control—is rock solid.

The magic isn't in the AI. It's in treating your documentation as a first-class artifact and letting that rigor guide smarter, more consistent code generation.

Ready to take control? Install Conductor today and join developers who are rethinking how they work with AI agents.