HN Reading Lists Can Be Mined as Skill Graphs for AI Agent Training

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A Hacker News thread started by a Django-based financial engineering lead seeking book recommendations to bridge gaps in numerical methods, concurrency, and systems thinking attracted 48 points and 17 community responses. A developer and writer argues that such reading list threads are more than book suggestions — they implicitly encode prerequisite skill chains and capability boundaries within a domain. For AI agent builders, these community-curated sequences can be converted into structured training data by extracting entities, relationships, and capability mappings from the discussion. The author proposes a minimal extraction pipeline using the Anthropic API to parse threads into JSON-formatted skill dependency graphs. The core insight is that the order in which the community recommends books reveals the hidden curriculum separating competent engineers from exceptional ones — a structure directly applicable to training domain-aware agents.

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