DeepSeek multi-agent pipeline for collecting game guides
10/24/2026 — 10/24, 00:19·1 sources (all)·1 reports (all)
Key takeaways
- A game company intern shared a DeepSeek-based multi-agent pipeline that spends about 10B tokens over two days, uses cache hits to cut costs…
A game company intern shared a DeepSeek-based multi-agent pipeline that spends about 10B tokens over two days, uses cache hits to cut costs below one-tenth, and runs 40+ subagents crawling different sites. The write-up covers heterogeneous web collection, PDF parsing, text and OCR extraction, field extraction, multi-round correction, batch processing, and unified formats.
Latest turnA game company intern described building a DeepSeek-based multi-agent pipeline that burned about 10 billion tokens in two days, using cache hits to cut cost below one-tenth and running 40-plus sub-agents to write site-specific crawlers. The post walks through web collection, PDF parsing, OCR, chunk-level summarization, retries, and field normalization for niche guide data.
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A game company intern described building a DeepSeek-based multi-agent pipeline that burned about 10 billion tokens in two days, using cache hits to cut cost below one-tenth and running 40-plus sub-agents to write site-specific crawlers. The post walks through web collection, PDF parsing, OCR, chunk-level summarization, retries, and field normalization for niche guide data.
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