Plan mode is now available in Gemini CLI

· Source: Google Developers Blog - AI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, short

Summary

Gemini CLI has introduced "plan mode," a new read-only operational state designed for analyzing requests and planning complex code changes without the risk of accidental modifications. Released on March 11, 2026, this mode allows the agent to navigate codebases, search patterns, and read documentation using tools like `read_file` and `grep_search`, but restricts file modification to internal plans only. Plan mode also incorporates an `ask_user` tool for clarifying goals and gathering missing information through bi-directional communication. It supports read-only MCP tools to integrate context from external developer stacks like GitHub or Postgres. For advanced workflows, the Conductor extension leverages plan mode and `ask_user` for orchestrating multi-step development tracks, with plans to integrate Conductor into Gemini CLI as a built-in mode. Plan mode is enabled by default and utilizes higher reasoning Pro models like Gemini 3.1 Pro for robust architectural decisions.

Key takeaway

For AI Architects designing or implementing complex features, Gemini CLI's plan mode offers a critical pre-flight environment. You should utilize this read-only mode to thoroughly research, map dependencies, and refine strategies with the `ask_user` tool before committing to any code changes. This approach minimizes risks associated with eager modifications and ensures architectural decisions are robust, especially when leveraging advanced models like Gemini 3.1 Pro.

Key insights

Gemini CLI's new plan mode offers a safe, read-only environment for complex code analysis and planning.

Principles

Method

Plan mode restricts Gemini CLI to read-only tools, allowing it to analyze code, dependencies, and documentation, then use the `ask_user` tool to clarify requirements before proposing a solution.

In practice

Topics

Code references

Best for: AI Architect, AI Engineer, Machine Learning Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Google Developers Blog - AI.