GitHub’s new ‘Agent Mode’ feature lets AI take the reins for developers
GitHub has launched a new agentic AI tool for developers, dubbed ‘Agent Mode’, alongside a raft of updates to the Copilot service.
Agent Mode enables Copilot to iterate on its own outputs and complete entire user requests in one go, thereby automating broader aspects of the development process. It can also automatically fix errors, suggest terminal commands, and assess run-time errors.
Copilot will now iterate repeatedly on its output until all the necessary subtasks of a prompt are complete, GitHub CEO Thomas Dohmke said, and will infer additional tasks that were not specified but are necessary to fulfill the primary request.
The new agentic capabilities will improve Copilot Workspace, allowing collaborative users to leverage a system of sub-agents in the platform to improve efficiency when generating plans, implementing code, or fixing errors.
“Agent mode will change the way developers work in their editor; and as such, we will bring it to all IDEs that Copilot supports,” Dohmke said.
Another feature introduced to Copilot is the ‘Next Edit’ function, which can automatically identify and suggest edits of a user’s previous changes. Accessed by pressing tab, users will be able to browse suggestions throughout any open file.
Vision for Copilot was also unveiled, which will allow users to create a mock-up piece of code from a snippet of content, such as a shorter portion of code, a screenshot, or an image. With this, Copilot can generate the UI, alt text, and code.
GitHub referred to its forward-looking plan, ‘Project Padawan,’ through which developers will be able to assign entire issues to Copilot, let it complete the task, and then evaluate and review the results.
The next step in AI code assistance
This announcement could mark yet another significant step in AI-based code assistance, which has been gaining huge popularity as a use case amongst developers and businesses. Google recently revealed that over 25% of its proprietary code is now AI-generated, for example.
GitHub has been at the center of the AI coding conversation for a while, having released GitHub Copilot Enterprise in early 2024, which it followed up with the release of GitHub Copilot Workspace a couple of months later.
GitHub touts the benefits of its tools, claiming that GitHub Autofix fixes software vulnerabilities at more than three times the speed of manual fixes, and at more than seven times the speed for cross-site scripting vulnerabilities.
There have been questions raised about the effectiveness of AI coding tools, though, with one study finding that developer performance has largely remained unchanged despite the use of coding tools.
GitHub’s own research paints a more positive picture, however. Based on a survey of 2,000 software engineers and developers, the firm found that many reported several benefits related to AI coding tools.
Many said the tools improved code quality, helped deliver more secure software, improved test case generation, and allowed for the faster adoption of new languages.
These tools also enable better time utilization, with 47% of respondents in the US and Germany using the time they saved for collaboration and system design.
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