Aider

Terminal-based AI pair programmer that edits code and commits to your local Git repo.

4.4 (5)

Overview

Aider is a command-line coding assistant that lets developers collaborate with large language models directly inside their terminal. It works against your local Git repository, reading existing source files, applying multi-file edits, and automatically committing changes with descriptive messages so every AI-driven modification is tracked in version history. Designed for real codebases, Aider builds a map of your project to give the model relevant context, supports a wide range of programming languages, and can be paired with models from providers like OpenAI, Anthropic, and others, including local models. It fits naturally into existing developer workflows without requiring a separate IDE, web app, or proprietary platform.

Key features

  • Local Git repository integration
  • Automatic commit messages for AI edits
  • Repository map for codebase-aware context
  • Multi-file editing and refactoring
  • Support for multiple LLM providers
  • Voice input and image context options

Use cases

AI-Assisted Refactoring Across Files

Refactor functions, rename symbols, or restructure modules across multiple files in a local repo, with Aider applying coordinated edits and committing each change to Git.

Auditable AI Code Changes via Git

Keep a clear history of AI-driven modifications by letting Aider auto-commit each edit with a descriptive message, making it easy to review or revert changes.

Terminal-Native Pair Programming

Collaborate with an LLM from the command line without leaving your existing editor or workflow, using repo-aware context to implement features or fix bugs.

Model-Flexible Coding with Local or Cloud LLMs

Pair Aider with OpenAI, Anthropic, or local models to match cost, privacy, and quality needs while working on the same codebase.

Pros & Cons

Pros

  • Runs in the terminal alongside existing dev tools
  • Automatic Git commits keep changes auditable
  • Handles multi-file edits with project context
  • Supports many models and language backends

Cons

  • Command-line interface has a learning curve
  • Requires API keys and can incur token costs
  • Quality depends on the underlying model chosen
  • Less visual feedback than GUI-based assistants

Reviews

4.4

Average from 5 ratings.

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Elena Rossi

Use it every day

Honestly didn't expect to like it this much. Voice input and image context options is exactly what I needed, and supports many models and language backends. I do wish quality depends on the underlying model chosen, but I reach for it almost every day now and it just clicks.

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Wei Chen

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on voice input and image context options, and runs in the terminal alongside existing dev tools caught me off guard. still, I'd recommend giving it a real trial.

E

Ethan Brooks

Solid for our team

We rolled this out across the team last quarter and automatic Git commits keep changes auditable. Multi-file editing and refactoring fits neatly into how we already work, and repository map for codebase-aware context removed a step we used to do by hand. Requires API keys and can incur token costs, which is the main caveat, but it has held up under daily use.

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Pierre Dubois

Solid for our team

We rolled this out across the team last quarter and automatic Git commits keep changes auditable. Multi-file editing and refactoring fits neatly into how we already work, and local Git repository integration removed a step we used to do by hand. Quality depends on the underlying model chosen, which is the main caveat, but it has held up under daily use.

S

Sofia Lindqvist

Years in this space

I've evaluated a lot of these over the years. What stands out here is voice input and image context options — handled better than most — and runs in the terminal alongside existing dev tools. Less visual feedback than GUI-based assistants is my one real gripe. Worth the time if this is your use case.

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