Coding agents are becoming essential in development due to their impact on efficiency and quality. GitHub Copilot has evolved since its initial launch, introducing features like 'agent mode' which allows users to delegate tasks. Automation facilitated by agents should be balanced with developer involvement to ensure quality outcomes. The choice of large language models (LLMs) influences the performance of agents, necessitating careful consideration. Furthermore, developers’ experience is critical in evaluating the output of these agents and implementing effective solutions in their workflows.
Since GitHub Copilot launched as a preview in Summer 2021, we have seen an explosion of coding assistant products. Initially used as code completion on steroids, some products in this space (like Cursor and Windsurf) rapidly moved towards agentic interactions.
GitHub Copilot added its own "agent mode" as a feature of the integrated chat, through which it is possible to ask an agent to perform various tasks on your behalf. This 'agent mode' should not to be confused with GitHub Copilot 'coding agent', which can be invoked from GitHub's interfaces.
Experience continues to be a vital asset for developers, enabling them to design effective solutions, plan implementations, and critically evaluate the output generated by coding agents.
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