Plandex (15,571 Stars) AI Coding Agent 2026

๐Ÿ“˜ Tutorials 2026-08-06 2 min read

Plandex (15,571 stars) is an open-source AI coding agent built for large, real-world tasks: it plans changes, applies them safely, and lets you review diffs before committing.

💡 What You Will Learn

Plandex (15,571 stars) is an open-source AI coding agent built for large, real-world tasks: it plans changes, applies them safely, and lets you review diffs before committing.

📜 Table of Contents

The short answer

plandex-ai/plandex (15,571 stars, Go) is an open-source AI coding agent designed for large projects and real-world tasks. Unlike simple autocomplete, Plandex reads your whole codebase, builds a plan across multiple files, applies changes incrementally, and shows you each diff for review - all from the terminal.

How it works

  1. Plan mode: Plandex analyzes the repo and proposes a multi-file plan
  2. Apply: it implements changes file by file, compiling/testing between steps
  3. Review: inspect diffs, revert individual files, or iterate with follow-up prompts
  4. Track: every change is recorded and can be rolled back

Install and first run

# macOS / Linux
curl -L https://plandex.ai/install.sh | bash
# Then
plandex

Set your API key, then start a session:

cd my-project
plandex tell "refactor the auth module to use async, and update all callers"
plandex diff        # review proposed changes
plandex apply       # apply them

Practical tips

FAQ

Which models does it support? OpenAI, Anthropic, and others via configurable providers.

Is it safe to use on production code? The diff-first workflow is designed for safe review; always inspect before pushing.

Is it free? The CLI is open source (MIT); you pay only for the underlying model API usage.

❓ FAQ

Which models does it support?

OpenAI, Anthropic, and others via configurable providers.

Is it safe to use on production code?

The diff-first workflow is designed for safe review; always inspect before pushing.

Is it free?

The CLI is open source (MIT); you pay only for the underlying model API usage.

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