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Using Local Coding Agents

The article discusses setting up and using local coding agents with LLMs (Large Language Models) to assist with software development tasks directly on a developer's machine, comparing different approaches and tools available for running these agents locally.

Background

- The article discusses using AI coding agents that run entirely on a user's own machine (locally) rather than relying on cloud-based services like OpenAI's ChatGPT or GitHub Copilot. - Key tools mentioned include Ollama (a tool for running LLMs locally), Aider (an AI pair-programming tool), and Continue (an open-source AI code assistant that integrates with VS Code and JetBrains). - Reasoning for local agents: privacy (code never leaves your machine), no API costs, offline capability, and full control over which model you use — at the cost of needing a powerful GPU and more setup effort. - The broader context: there has been a rapid shift from closed, cloud-only AI coding assistants to open, local alternatives, driven by better open-source models (e.g., CodeLlama, DeepSeek Coder) and growing concerns about data security and vendor lock-in.

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Using Local Coding Agents

Background

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