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Fireworks AI Blog·Model·28d ago·~1 min read

3/28/2026 The Fine-Tuning Bottleneck Isn't the Algorithm

TL;DR: Integration friction and slow iteration cycles are the bottlenecks that actually stall fine-tuning — not the algorithm. We share the patterns we see across engagements, how teams like Cursor and Genspark broke through them, and where the workflow is heading: toward fully agentic fine-tuning loops that close themselves. Most teams that come to us for fine-tuning are not struggling with the training algorithm. They are struggling with everything around it: getting reward functions to talk to internal APIs without leaking data, waiting days between experiments because each step lives in a different tool, and figuring out whether the problem even calls for SFT, RFT, or DPO. Over the past year, working with a select group of the most innovative startups, digital natives, and Fortune 500 companies, we have seen these patterns repeat across every engagement. Every team that comes…

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