GitHub Next

Collaborative AI Engineering: One Dev, Two Dozen Agents, Zero Alignment — Maggie Appleton, GitHub

Apr 26, 2026 · 17:43

Maggie Appleton, a staff research engineer at GitHub Next, argues that the current paradigm of one developer with a fleet of solo agents leads to zero team alignment, making software a team sport that requires shared context. She presents ACE (Agent Collaboration Environment), a multiplayer research prototype that provides shared chat sessions backed by micro VMs and Git branches, enabling real-time collaboration where designers, PMs, and developers can all prompt agents together. The talk emphasizes that implementation is now cheap and fast, so the hard question is "should we build it?" — requiring early, constant alignment to avoid wasted work, coordination debt, and unrequested features. ACE aims to reclaim time for rigorous critical thinking by letting teams plan, build, and review in a single shared space, with proactive agents summarizing team activity and unfinished work. Appleton contends that quality becomes the differentiator in a world of cheap code, and tools like ACE can help teams build a few exceptional things rather than a thousand crappy ones.

GitHub Next Explorations: Rahul Pandita

Feb 8, 2025 · 18:18

Rahul Pandita, a researcher at GitHub Next, presents two explorations: Copilot Next Edit Suggestions and Copilot Workspace. Next Edit Suggestions extends GhostX by suggesting multi-location edits beyond the cursor, such as updating method definitions and documentation when a parameter is added. Copilot Workspace addresses developers' pain points of getting started on tasks, trusting AI output, and retaining control by offering a one-click proposal, built-in runtime verification, and an iterative, collaborative environment. Pandita demonstrates updating a MonoSpace website to add Rust syntax highlighting via a GitHub issue, showing specification generation, planning, and terminal command synthesis. He emphasizes that GitHub Next explores uncertain futures rapidly, learning from experiments like Copilot (which started as a Next project) to shape AI-augmented software engineering without waiting decades.