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Coding Assistants

Overview

An open-source autopilot for VS Code and JetBrains that allows you to build your own custom AI coding experience. You can easily plug in any LLM from any provider.

Continue is an open-source extension that turns your IDE into a configurable AI coding environment where you choose the models, context providers, and behaviors. Rather than locking you into one vendor's stack, it lets you mix local models via Ollama with hosted frontier models and tune everything through simple config. That flexibility makes it a favorite for developers who want to assemble their own assistant.

Key Features

  • Plug in any LLM, local or hosted, per task
  • Custom context providers, slash commands, and rules
  • Autocomplete, chat, and edit modes in VS Code and JetBrains
  • Open-source and fully self-configurable
  • Shareable team configurations

Best For

Power users and teams who want to control exactly which models and context feed their assistant.

Pros & Cons

Pros
  • Maximum flexibility and model freedom
  • Open-source with an active community
  • Easy to combine local and cloud models
Cons
  • Requires configuration to get the best results
  • No managed cloud convenience out of the box
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Pulse Verdict

The modularity master. Continue's open architecture lets you swap models like LEGO pieces, making it the most future-proof coding assistant for power users.

Pricing

Free and open-source; you supply your own model API keys or run local models.

Pricing changes often — confirm current plans on the official site.

Visit Official Website →

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Cursor

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JetBrains AI Assistant

The native AI layer built into the JetBrains IDE family (IntelliJ, PyCharm, WebStorm). It combines multi-model chat, inline completions, and the autonomous 'Junie' coding agent with deep static-analysis context.

Ollama

The leading tool for running large language models locally on your own machine. Features a simple CLI and a massive library of open-weight models.