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Join Tanmai Gopal, CEO at Hasura, as he discusses the current state of RAG and AI tooling challenges. Gopal explains that RAG has cooled down from its peak popularity, noting that while it works for low-hanging fruit use cases, it fails in mission-critical scenarios where good enough is not the threshold and precision is required. He describes RAG's fundamental limitation as not understanding context, comparing it to using a single hammer for everything, and advocates for agentic approaches that combine RAG with other tools. Gopal predicts that AI reliability will become the dominant topic by year's end, as he observes that newer models have become skilled at convincing themselves and users that they're correct when they're actually hallucinating.
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Join Tanmai Gopal, CEO at Hasura, as he discusses the current state of RAG and AI tooling challenges. Gopal explains that RAG has cooled down from its peak popularity, noting that while it works for low-hanging fruit use cases, it fails in mission-critical scenarios where good enough is not the threshold and precision is required. He describes RAG's fundamental limitation as not understanding context, comparing it to using a single hammer for everything, and advocates for agentic approaches that combine RAG with other tools. Gopal predicts that AI reliability will become the dominant topic by year's end, as he observes that newer models have become skilled at convincing themselves and users that they're correct when they're actually hallucinating.
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