A comprehensive guide to building specialized AI research agents that can aggregate and analyze tech content from multiple sources. The approach uses structured workflows, data caching, and prompt chaining to create personalized tech reports. Key components include preprocessing data pipelines, strategic use of small vs large language models for cost optimization, and structured JSON outputs for reliability. The system fetches trending keywords, processes facts from tech forums, and generates themed reports based on user profiles.
Table of contents
Notes on buildingPreparing and caching dataWhen to work with small vs larger modelsGenerating the reportsNotes on building agents1 Comment
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