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DSPy Is All You Need
TLDR: we used DSPy-style recursive prompt optimization to train a browser agent that solves Brett Adcock's 30-step challenge in 265 seconds at $0.06 per run, with GPT-OSS 120B matching frontier performance after training. 2 weeks ago, Brett Adcock posted a public browser agent challenge; the website
How We Train Models at Freesolo
TLDR: reinforcement learning cut our monthly inference costs by 98.32%, improved performance on our internal benchmark, and reduced latency by 66%. Freesolo builds people search infrastructure, which involves indexing hundreds of millions of LinkedIn profiles and training models to first query and t
Building SOTA People Search
Originally when Freesolo was first started when it was still called Linkd, there was one database for each school with approximately 10k profiles per school. That means that there is a lot of room for inefficiency. However, when we decided to build people search for the entire world and started work
