$FIREWORKS-AI · Fireworks enables globally distributed RL training with custom inference kernels and delta weight synchronization

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extracted intelligence

Sequoia Capital

How Cursor Trained Composer on Fireworks: Distributed Infrastructure for High-Performance RL

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Fireworks enables globally distributed RL training with custom inference kernels and delta weight synchronization

2026-05-26 · 3 company · 4 thematic

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2 bull0 bear1 neu

speakers

federico

Leads research on Cursor's agentic coding model Composer 2, focusing on model training strategy, RL methodology, and specialization for software engineering within the Cursor environment.

dima

Spent months embedded at Cursor building the distributed inference infrastructure for Composer 2's large-scale RL training, including global cluster orchestration, custom kernels, and weight synchronization systems.

quote

“We can globally distribute that across small clusters all over the world. So, I think for the composer to run, we used the four clusters in total that were all over the world, very far away from each other. And we even used some of our pro…”

—dima

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