Agentic chat - think twice, answer once

Agentic chat enhances AI coding assistance by autonomously gathering and refining relevant context from various sources such as codebases, terminals, and the internet, thus improving the quality and precision of responses from language models (LLMs). It addresses the common issue of LLMs providing generally correct but contextually lacking answers by proactively retrieving and analyzing pertinent information before generating responses. This new feature, available to Sourcegraph users like Cody Pro and Enterprise, substantially reduces the need for manual context provision by using tools like Code Search, Terminal access, and web searches to gather necessary details. Agentic chat also integrates with OpenCtx, allowing it to leverage non-code context from tools such as Linear, Jira, and Slack, thereby offering more accurate and context-aware solutions. It requires user approval for executing terminal commands and is designed to keep up with fast-evolving technology landscapes by accessing the latest data online, thus ensuring up-to-date and relevant feedback.

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