This podcast presents a clear, step-by-step guide on creating a web crawler system designed for training large language models (LLMs), with a strong focus on a well-structured interview process. The host, a former engineer from Meta, walks listeners through essential stages such as defining both functional and non-functional requirements, pinpointing key entities and data flow, and developing a high-level design. The discussion delves into scalability and robustness, emphasizing the importance of breaking the crawler into smaller, independent stages—like fetching HTML and parsing text—to enhance fault tolerance and maintainability. To wrap up, the podcast recommends utilizing four high-performance AWS instances to achieve efficient crawling within just five days.
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