{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Chain of Thought | AI Agents, Infrastructure & Engineering","title":"Agents Are Overtaking Humans in Search: Why Search Must Be Rebuilt","html":"","width":"100%","height":180,"duration":3427,"description":"Saahil Jain joined You.com as a founding engineer in 2020, when it was a consumer search engine competing with Google. Now its CTO, he builds search for AI agents, and he argues that however smart models get, they will still need tools to find out what is happening in the world.\nHis analogy: we built the self-driving cars before the roads. He walks through which work he expects to move inside the model, why better models made harnesses matter less, and why cheaper open models and routing are giving harnesses a new job. He says he changed his mind on that last point in the past few months.\nThen we get into how agents search differently than people do: thousands of queries at once, recall over ranking, and a much wider range of latency needs. Saahil traces a query from fan-out to the index to re-ranking, and explains why You.com judges search by whether the agent answered the question, and why he trusts customer evals and benchmarks that change over time more than static public ones.\nWe cover:\n- Core intelligence versus augmented intelligence, and the self-driving cars that arrived before the roads\n- Which tasks Saahil expects models to absorb, and where unverifiable rewards slow them down\n- Why frontier labs keep going vertical while open-model labs give weights away\n- How stronger models shrank the gap between good and bad harnesses, and how routing across open models can revive them\n- How You.com post-trains models with its search tool while trying not to overfit to any one model\n- How agent search differs from human search: query volume, context, ranking and latency\n- The life of a query: subqueries, lexical and semantic indexes, re-ranking and enrichment\n- Why static benchmarks can be memorized, and what dynamic benchmarks and customer evals measure instead\nMentioned in this episode:\n- I Paid an AI Agent $8 to Write About its ‘Life’: https://newsletter.chainofthought.show/p/i-paid-an-ai-agent-8-to-write-about\n- MotionBench: https://motionbench.sh\nConnect with...","thumbnail_url":"https://img.transistorcdn.com/KnEL-9mfZGF096BNQ33xaE_zVyhLvBNV8rHifHuvYgc/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hYWM2/NmYwMjc4MmJiYTYw/ZTI5NGZhNzRhNmZh/NTU0OC5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}