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Using semantic benchmarks to build a self-improving text-to-query agent Conversion
Our text-to-query agent went from 45 seconds on frontier models to 2 seconds on GLM 5.3 Flash, with the same accuracy at 1/20 the cost. This post describes the architecture, evaluation loop, and lessons learned.
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How 2 UC Berkeley dropouts raised $28M for their AI marketing automation startup
A marketing automation startup called Conversation has a founding story that sounds like it could have been an episode of the HBO show
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