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Throw more AI at your problems


Last week, we published our longest-ever post outlining how we think the AI market will evolve.

In the interest of building AI-powered workers, we’ve also found that returning incrementally useful results can also help make your UX feel more similar to how a person would behave. The first cut at a newly introduced LLM call might just use a generic model, but as you gather more data, you can use that to improve quality by fine-tuning that component to be more precise and reliable. Relying on a handful of incredibly powerful LLMs isn’t going to cut it because compound systems will (again) be faster, more reliable, and higher quality.

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