Copilot Workspace Is GitHub's Take On AI-Powered Software Engineering

An anonymous reader quotes a report from TechCrunch: Ahead of its annual GitHub Universe conference in San Francisco early this fall, GitHub announced Copilot Workspace, a dev environment that taps what GitHub describes as "Copilot-powered agents" to help developers brainstorm, plan, build, test and run code in natural language. Jonathan Carter, head of GitHub Next, GitHub's software R&D team, pitches Workspace as somewhat of an evolution of GitHub's AI-powered coding assistant Copilot into a more general tool, building on recently introduced capabilities like Copilot Chat, which lets developers ask questions about code in natural language. "Through research, we found that, for many tasks, the biggest point of friction for developers was in getting started, and in particular knowing how to approach a [coding] problem, knowing which files to edit and knowing how to consider multiple solutions and their trade-offs," Carter said. "So we wanted to build an AI assistant that could meet developers at the inception of an idea or task, reduce the activation energy needed to begin and then collaborate with them on making the necessary edits across the entire corebase." Given a GitHub repo or a specific bug within a repo, Workspace -- underpinned by OpenAI's GPT-4 Turbo model -- can build a plan to (attempt to) squash the bug or implement a new feature, drawing on an understanding of the repo's comments, issue replies and larger codebase. Developers get suggested code for the bug fix or new feature, along with a list of the things they need to validate and test that code, plus controls to edit, save, refactor or undo it. The suggested code can be run directly in Workspace and shared among team members via an external link. Those team members, once in Workspace, can refine and tinker with the code as they see fit. Perhaps the most obvious way to launch Workspace is from the new "Open in Workspace" button to the left of issues and pull requests in GitHub repos. Clicking on it opens a field to describe the software engineering task to be completed in natural language, like, "Add documentation for the changes in this pull request," which, once submitted, gets added to a list of "sessions" within the new dedicated Workspace view. Workspace executes requests systematically step by step, creating a specification, generating a plan and then implementing that plan. Developers can dive into any of these steps to get a granular view of the suggested code and changes and delete, re-run or re-order the steps as necessary. "Since developers spend a lot of their time working on [coding issues], we believe we can help empower developers every day through a 'thought partnership' with AI," Carter said. "You can think of Copilot Workspace as a companion experience and dev environment that complements existing tools and workflows and enables simplifying a class of developer tasks ... We believe there's a lot of value that can be delivered in an AI-native developer environment that isn't constrained by existing workflows."

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