How to use Aider: AI pair programming tool in the terminal

Aider is a tool focusing on AI programming scenarios. It is an AI pair programming tool in the terminal, deeply integrated with Git, and supports mainstream models such as Claude and GPT-4. This article is based on the official product documentation to sort out its capabilities and suitable usage methods.

Market signals

With over 25,000 stars on GitHub, Aider is one of the most popular projects among open source AI programming tools. In the developer community of Hacker News and Reddit, Aider is a frequently mentioned tool in technical discussions, especially among engineers who prefer command line tools, work on Linux servers, or are not satisfied with the VS Code/IDE plug-in form. According to the benchmark test data officially released by Aider, the combination of Aider and Claude 3.5 Sonnet scored ahead of most similar tools on SWE-bench (Software Engineering Benchmark Test), verifying its actual performance on real code tasks. The project is actively maintained, maintaining multiple version iterations every month, with more than 200 contributors, reflecting the vitality of the strong open source community.

Product capabilities

• Multi-file code editing: Multiple files can be modified simultaneously in a single conversation. Aider automatically understands the dependencies between files and generates consistent cross-file change plans.
• Deep Git Integration: Standard Git commit messages (can use LLM or template format) are automatically generated after each AI modification. All changes have complete version records and rollback is supported.
• Architect pattern: Separates architecture planning and code implementation into two-step LLM calls - the first LLM is responsible for thinking about the solution architecture, and the second LLM is responsible for generating specific code, significantly improving the quality of complex tasks.
• Multi-model support: Supports 70+ LLMs, including Claude 3.5 Sonnet, GPT-4o, Gemini 1.5 Pro, DeepSeek, Ollama local models, etc., which can be freely switched according to task type and cost requirements.
• Voice Coding: Supports voice input commands through the microphone, transcribes the voice into text in real time and then performs programming tasks, freeing both hands.
• Image contextual input: UI screenshots, design drafts, or error screenshots can be passed directly into the conversation, allowing AI to generate corresponding code based on visual information.

Judgment in one sentence: If your workflow is indeed stuck in the above links, Aider is worthy of being put on the candidate list for small-scale verification first; otherwise, it does not need to be introduced for functionality.