The idea is simple: encode your team's standards into an automated cloud agent that runs before you ever see the PR. Turn your best practices into an AI reviewer.

Vibe coding gives you velocity, but chiseling gives you quality. It's the critical human judgment that separates a prototype from production code.

By Patrick Erichsen, Software Engineer at Continue If you've ever watched an AI agent slowly read file after file, one at a time, you know the pain. What should take seconds stretches into minutes as the model politely waits for each operation to complete before starting the next.

Last week, Anthropic introduced the Model Context Protocol (MCP), a new open protocol that "enables seamless integration between LLM applications and external data sources and tools". Also last week, Continue added support for MCP! Let’s explore why MCP is well-suited for Continue and how you can use

Anthropic’s rollout of prompt caching, also known as context caching, follows similar offerings from providers like DeepSeek and Google and has been getting a lot of attention recently. At Continue, we're particularly excited about the potential impact on engineering teams, as prompt caching can significantly reduce costs