The original title is "I Built an AI Pipeline That Scores 10,000+ Listings Daily Without Breaking the Bank"

Short summary

Author built a production AI pipeline scoring 10K+ job listings daily against profiles. Three cost strategies: batching via OpenAI's Batch API (50% discount), model tiering routing simple cases to cheaper models (70% savings), and caching by content hash (40% hit rate). Technical wins included cursor-based pagination and function calling for output consistency.

• •Batch API enables 50% cost reduction with 30-60 min latency trade-off
• •Model tiering routes simple listings to cheaper models, cutting average cost 70%
• •Aggressive caching by content hash achieves ~40% hit rate for repeat listings

Generated with AI, which can make mistakes.