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Continue.dev

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dev is an open-source AI coding assistant that plugs into editors like VS Code and JetBrains IDEs, letting developers connect any language model — cloud or self-hosted — for chat, autocomplete, and agentic code editing.

Definition

Continue.dev is an open-source AI coding assistant that plugs into editors like VS Code and JetBrains IDEs, letting developers connect any language model — cloud or self-hosted — for chat, autocomplete, and agentic code editing.

Overview

Continue.dev differentiates itself from proprietary AI coding tools by being open source and model-agnostic: rather than shipping with a single fixed model, it lets developers configure which large language model powers each feature, whether that's a hosted API from Anthropic, OpenAI, or Google, or a self-hosted open-weight model served through Ollama or a similar local inference server. This matters for teams with data-privacy requirements, cost constraints, or a preference for open-weight models, since Continue can be pointed entirely at infrastructure the organization controls. The extension provides the now-standard set of AI coding features — inline autocomplete, a chat sidebar for asking questions about the codebase, and "edit" or "agent" modes for making targeted or multi-file changes — built on top of a configurable context system that can pull in open files, retrieved documentation, terminal output, or custom context providers defined via its configuration file. Because Continue is open source, its context-retrieval and prompting logic is inspectable and extensible, and developers or organizations can build custom context providers, slash commands, or tools tailored to their own codebase and workflows. Continue.dev is often positioned as the open-source, customizable alternative to closed tools like GitHub Copilot or Cursor, appealing particularly to engineering teams that want to standardize on a specific model provider, run assistants against private/on-prem model deployments, or avoid vendor lock-in on the underlying AI model powering their coding assistant.

Key Features

  • Open-source VS Code and JetBrains extension for AI-assisted coding
  • Model-agnostic — supports Anthropic, OpenAI, Google, and self-hosted/local models
  • Inline autocomplete, chat sidebar, and agentic multi-file edit modes
  • Configurable via a JSON/YAML config file for models, context providers, and commands
  • Extensible context system for pulling in docs, terminal output, or custom sources
  • Can be pointed entirely at self-hosted or on-prem model infrastructure
  • Community-driven development with public roadmap and plugin ecosystem
  • No vendor lock-in to a single model provider

Use Cases

Standardizing a team's AI coding assistant on a chosen model provider or self-hosted model
Running AI code assistance against private, on-premises LLM deployments for compliance
Comparing outputs across multiple models for the same coding task
Building custom context providers tailored to an organization's codebase or tools
Providing AI coding assistance in air-gapped or highly regulated environments
Giving open-source contributors a free, transparent alternative to proprietary AI IDEs

Alternatives

History

Continue is an open-source AI code assistant for Visual Studio Code and JetBrains IDEs, offering autocomplete, chat, and inline editing backed by large language models. It is developed by Continue Dev, Inc., a San Francisco company founded in June 2023 by Ty Dunn and Nate Sesti, which went through Y Combinator's Summer 2023 batch. Released under the Apache 2.0 license, Continue's distinguishing feature is model and provider flexibility: developers choose which models to use and where they run, from cloud providers like OpenAI, Anthropic, and Google to locally hosted models via Ollama, LM Studio, and llama.cpp. It became one of the most widely adopted open-source alternatives to GitHub Copilot and Cursor.

Frequently Asked Questions

From the Blog

Frequently Asked Questions

21 categories · pick one to explore

Does SkillVeris have a tech blog, and what does it cover?
Yes, the SkillVeris blog has over 500 articles covering AI and machine learning, programming, web development, DevOps, cloud, security, databases and career guidance. Articles are practical and answer-first, and many use the Learn Through Hobbies approach, teaching technical concepts through cricket, music, gaming or cooking analogies. Everything is free to read.
What is the SkillVeris tech glossary and how big is it?
The SkillVeris glossary is a free reference of roughly 2,000-plus technology terms, each with a clear plain-language definition. It spans AI, programming, web, DevOps, cloud, security and database vocabulary, so whenever a lesson, article or job description uses jargon you do not recognise, the glossary gives you a fast, reliable answer.
Are the developer cheat sheets on SkillVeris free to download?
The cheat sheets are completely free to use, like everything else on SkillVeris. Each sheet condenses a language or tool into its essential syntax, commands and patterns for quick reference while coding. They are designed for rapid lookup during real work, complementing the deeper explanations found in study notes and courses.
Which programming references and cheat sheets are available?
Cheat sheets cover the platform's main domains, including programming languages, AI and ML tooling, web development, DevOps, cloud, security and databases, matching the topics of the 37 live courses. Each sheet lists related reading links and hashtags, so you can jump from a quick reference into fuller study notes or blog articles.
How do I find the meaning of a technical term quickly?
Search the SkillVeris glossary, which holds around 2,000-plus terms with concise, plain-language definitions. Each entry gets to the point in its first sentence, then links to related reading like blog posts or study notes for deeper context. It is faster and more consistent than sifting through scattered search results.
Is the SkillVeris blog good for beginners learning to code?
Yes, many blog articles are written specifically for beginners, and the Learn Through Hobbies style makes them unusually approachable: you might learn Python concepts through cricket or understand APIs through cooking. With 500-plus articles across skill levels, beginners can start with fundamentals and keep reading as they advance, entirely free.
Can cheat sheets replace full courses for learning a language?
No, cheat sheets are references, not teaching tools; they assume you already understand the concepts and just need syntax or commands fast. To actually learn a language, take a structured SkillVeris course with its 24–40 lessons and assessments, then keep the cheat sheet beside you while practising in Code Lab.
How often are new blog articles published on SkillVeris?
The blog grows regularly and already exceeds 500 articles, with new posts added as courses launch and technologies evolve. Topics track the platform's catalogue across AI, programming, web development, DevOps, cloud and security, so checking the Blog section periodically surfaces fresh tutorials, explainers and career-focused pieces, all free to read.
Does the glossary cover AI and machine learning terms?
Yes, AI and machine learning vocabulary is a major part of the roughly 2,000-plus term glossary, covering everything from foundational terms to modern concepts around LLMs, RAG and MLOps. Definitions are plain-language and answer-first, which helps when dense AI papers or course lessons throw unfamiliar jargon at you.
Are there cheat sheets for interview preparation?
Cheat sheets work well as interview-day refreshers because they compress syntax, commands and key concepts into scannable references. For dedicated preparation, combine them with the SkillVeris interview questions feature, which includes readiness scoring, plus study notes for depth. Reviewing a relevant cheat sheet just before an interview steadies recall under pressure.
Can I read the tech blog without signing up?
Yes, the blog is freely readable, and SkillVeris never charges for content. All 500-plus articles are open, covering tutorials, concept explainers and career advice. Creating a free account adds value elsewhere on the platform, like course progress tracking and certificates, but reading the blog requires no commitment at all.
How is the SkillVeris glossary different from Wikipedia?
The glossary is purpose-built for learners: definitions are short, plain-language and answer-first, sized for a quick lookup mid-lesson rather than a deep encyclopedic read. Entries also cross-link to related SkillVeris study notes, blog posts and courses, so a definition becomes a doorway into structured learning instead of a dead end.
Do blog articles use the Learn Through Hobbies method?
Many blog articles teach technical topics through hobby analogies, a hallmark of the SkillVeris blog, so you will find articles explaining programming through cricket, machine learning through music, or system design through cooking. The analogy is the teaching device; the article still delivers the real technical concept underneath.
Where can I find quick programming references while coding?
Open the SkillVeris cheat sheets, which are built exactly for that moment: compact, scannable references for syntax, commands and common patterns across languages and tools. Keep the relevant sheet in a browser tab while you work in Code Lab or your own editor, and dip into the glossary for terminology.
Is there a glossary entry for terms I meet in job descriptions?
Very likely yes, with roughly 2,000-plus terms across AI, programming, web, DevOps, cloud, security and databases, the glossary covers most jargon that appears in tech job descriptions. Decoding a listing this way helps you judge role fit honestly and prepares you to discuss those terms in interviews.
Are the blog articles written for the Indian tech audience?
The blog serves Indian learners plus a worldwide audience. Content stays globally relevant while acknowledging realities that matter in India, such as free access being essential for students and freshers, and career guidance that connects naturally to the SkillVeris jobs portal, which aggregates roles across India, UK, USA, Germany and Remote.
Can I suggest a topic for the blog or glossary?
SkillVeris content grows in response to what learners need, so feedback is welcome through the platform's support channels. If a term is missing from the glossary or a topic deserves an article, telling the team helps prioritise it. Meanwhile, the AI Mentor can answer the question immediately, 24/7, at any depth.
Do cheat sheets and glossary entries link to deeper learning?
Yes, every cheat sheet and glossary entry carries related reading links into study notes, blog articles and courses, plus concept hashtags for discovering similar content. This cross-linking means a thirty-second lookup can smoothly become a structured learning session whenever you decide you want more than a quick answer.
What makes SkillVeris programming references trustworthy?
The references are written to strict internal quality standards, kept consistent with the platform's 37 live courses, and never padded with invented statistics or hype. Definitions and cheat sheets are reviewed against the same content contracts that govern courses, and the answer-first style makes any inaccuracy easy to spot and correct.
How do the blog, glossary and cheat sheets fit into my learning routine?
Use them as satellites around your main course: read blog articles for context and motivation, hit the glossary the instant jargon appears, and keep cheat sheets open while coding. Together with study notes, Code Lab and the 24/7 AI Mentor, they turn passive reading into a complete, free learning system.

What Learners Say

Real journeys from the SkillVeris community — swipe for more.

SkillVeris taught me Python through Cricket. Now I’m building real projects and feeling confident!
Arjun S. · B.Tech Student
The best platform for hobby-based learning. Concepts finally stick.
Priya R. · Data Analyst
I went from zero coding to a portfolio of projects — all by learning through my love for gaming. Landed my first internship!
Kabir M. · CS Undergraduate
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