How to Orchestrate Claude, Codex, and Gemini CLI Together

March 7, 2026 • Frank Albanese • 12 min read

Every AI coding agent has a personality. Claude Code is the deep thinker that will refactor your entire module and explain why. OpenAI Codex is the sandbox specialist that runs code in the cloud and comes back with verified results. Gemini CLI is the free-tier explorer that lets you experiment without watching your billing dashboard. Using just one is like having a toolbox with only a hammer. Using all three together — that’s where the real leverage is.

This guide covers how to run Claude Code, Codex, and Gemini CLI simultaneously, assign tasks based on each model’s strengths, share context across agents, and keep your costs under control. The result is a multi-model orchestration workflow that produces better code faster than any single agent can alone.

Why Use Multiple Agents

The case for multi-model orchestration comes down to a simple observation: no single model is the best at everything. Each has been trained differently, optimized for different tasks, and comes with different infrastructure.

Claude Code excels at complex reasoning, multi-file refactoring, and understanding deep codebases. When you need an agent to read 50 files, understand the architecture, and make coordinated changes across multiple modules, Claude is the one to call. Its context window is massive, its reasoning is nuanced, and its code quality is consistently high.

OpenAI Codex operates in a cloud sandbox. It can install dependencies, run tests, execute scripts, and verify its own work — all without touching your local machine. This makes it ideal for long-running tasks, dependency-heavy builds, and anything where you want isolation from your development environment.

Gemini CLI runs on Google’s infrastructure with a generous free tier. For exploration, prototyping, and quick questions, it’s hard to beat the economics. Gemini 2.5 Pro also has strong performance on code generation benchmarks, making it a capable workhorse for straightforward implementation tasks.

Setting Up Your Multi-Agent Workspace

The first step is getting all three agents installed and accessible from your terminal. Then you need a workspace that lets you manage them without constantly switching between windows.

In Beam, create a workspace for your project and set up three tabs — one for each agent. Name them clearly: “Claude — Architect,” “Codex — Executor,” and “Gemini — Explorer.” Use ⌘1, ⌘2, and ⌘3 to jump between them instantly.

This layout means you always know which agent is doing what. No confusion. No context mixing. Each agent has a dedicated lane.

The Orchestration Workflow

Here’s how a typical multi-agent session looks in practice. Suppose you’re building a new REST API with authentication, a database layer, and a frontend integration.

Step 1: Assign Claude the architecture. Claude Code gets the hard thinking: designing the API schema, choosing the authentication pattern, defining the database models, and writing the core business logic. Claude reads your entire codebase, understands your conventions, and produces code that fits your existing architecture.

Step 2: Assign Codex the execution. Once Claude produces the core implementation, hand Codex the build-and-verify tasks. Let it install dependencies, run the test suite, set up the database migrations, and verify that everything compiles and passes. Codex runs in an isolated cloud sandbox, so it can install system-level dependencies without polluting your local environment.

Step 3: Assign Gemini the exploration. While Claude architects and Codex executes, use Gemini for the quick-turnaround tasks: generating sample data, exploring library options, writing documentation drafts, or prototyping the frontend components. The free tier means you can iterate rapidly without cost pressure.

Sharing Context Across Agents: Git as the Source of Truth

The biggest challenge with multi-agent orchestration is context synchronization. Each agent has its own conversation history, its own understanding of the project, and its own set of files. How do you keep them aligned?

The answer is simple: git is your source of truth. Every agent reads from and writes to the same repository. When Claude finishes a refactor, commit the changes. When Codex verifies the build, the results are in the repo. When Gemini generates a prototype, it’s written to a branch.

Your CLAUDE.md file serves as the shared context document. It contains your architectural decisions, coding conventions, and project-specific instructions. Each agent reads it at session start, ensuring consistent output regardless of which model is generating code.

Matching Tasks to Models

The key to effective orchestration is knowing which model to use for which task. Here’s a practical mapping based on real-world experience:

Give to Claude Code: Anything that requires understanding the full codebase. Multi-file refactors. API design. Database schema decisions. Complex debugging that spans multiple layers. Code review of Codex or Gemini output. Writing tests that exercise edge cases you’ve identified.

Give to Codex: Tasks where execution verification matters. CI/CD pipeline setup. Dependency management. Build configuration. Performance benchmarks. Integration tests that need a real database. Anything that benefits from sandboxed execution.

Give to Gemini: Exploration and prototyping. Evaluating library options. Generating boilerplate. Writing documentation. Quick one-off scripts. Formatting and linting. Tasks where you want fast iteration without worrying about cost.

Cost Optimization

Multi-agent orchestration can get expensive if you’re not strategic. Here are the principles that keep costs under control:

• Use Gemini for the first pass. Before spending Claude tokens on exploration, let Gemini do the initial research. Once you know what you need, give Claude the focused, well-defined task.
• Use Codex for verification, not ideation. Codex’s sandbox is expensive per-task. Don’t use it for brainstorming. Use it to verify that the code Claude wrote actually works.
• Keep Claude sessions focused. Claude Code is the most capable and the most expensive. Feed it well-scoped tasks with clear acceptance criteria. Don’t let it wander.
• Batch similar tasks. Instead of switching agents per task, batch all architecture tasks for Claude, all verification tasks for Codex, and all exploration tasks for Gemini.
• Monitor token usage. Track your spend per agent per week. Adjust the balance based on where you’re getting the best return.

Advanced Pattern: Agent Cross-Review

One of the most powerful orchestration patterns is using one agent to review another’s output. Claude Code is exceptional at reviewing code it didn’t write. After Codex generates a solution, pipe the output to Claude for architectural review. After Gemini produces a prototype, have Claude assess whether it fits your project’s conventions.

This cross-review pattern catches issues that a single agent misses. Each model has different blind spots. Claude might over-engineer. Codex might take shortcuts. Gemini might ignore your project’s patterns. Cross-review surfaces these issues before they hit production.

Key Takeaways

• Each agent has strengths. Claude Code for reasoning and architecture. Codex for sandbox execution and verification. Gemini CLI for free exploration and prototyping.
• Git is your context synchronization layer. All agents read from and write to the same repository. Shared memory files keep them aligned.
• Match tasks to models. Don’t waste Claude tokens on boilerplate. Don’t use Codex for brainstorming. Don’t use Gemini for complex multi-file refactors.
• Cross-review catches blind spots. Use one agent to review another’s output. Different models have different failure modes.
• Cost optimization is about task routing. Use the cheapest capable agent for each task. Escalate to more powerful models only when needed.