🧠 Lessons Learned: X/Twitter Daily Summary Project

About This Document This is a retrospective written after building the X/Twitter Daily Summary Tool — a Python application that automatically fetches posts from your X (Twitter) home timeline, groups them by author and engagement, and feeds them through an AI pipeline to generate a strategic intelligence report written in the style of a geopolitical brief. The tool supports two AI backends: Gemini (Google Cloud): Fast, high-quality, but costs API credits. Ollama (Local): Runs entirely on your own hardware, free to use. This document captures the real challenges we ran into, the decisions we made, and the insights we'd apply if starting over. It is written for someone who wants to build something similar. 1. API Costs: Discover, Measure, Then Mitigate What happened: The X API is priced pay-per-request. $25 was loaded as credits and the tool was run for the first time on a real 24-hour timeline. The result: fetching ~800 posts cost approximately $4 in a single run. That's a concrete, mea