Imagine facing a tough problem at work, and instead of asking one colleague, you gather four different experts in the same room, each handling the part they're best at.
That's essentially what GitHub just built into Copilot, in a project called HydraFusion.
Instead of picking one AI model to write your code start to finish, HydraFusion looks at the task, breaks it down, and routes different pieces to different models from different providers, each handling what they do best.
One model might be great at understanding overall architecture, another excels at writing tests, another at performance tuning. HydraFusion builds a full execution plan, like a conductor assigning parts to an orchestra.
This isn't entirely new. GitHub already had automatic model selection. What's different is that this happens dynamically, at runtime, instead of being a fixed choice made upfront.
The expected result is frontier-level performance without being locked into any single model.
What does this mean for developers? Your coding assistant isn't getting smarter because one model got stronger. It's getting smarter because it finally learned how to pick the right expert at the right moment.
🔗 Original Source & Reference: https://www.infoq.com/news/2026/09/github-hydrafusion/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global
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