I built an AI to analyze stocks after losing money trading
Why I built this I kept losing money trading U.S. stocks, and realized most of my time was spent reading news and trying to interpret it. After a while, it became repetitive and exhausting. So I bu...

Source: DEV Community
Why I built this I kept losing money trading U.S. stocks, and realized most of my time was spent reading news and trying to interpret it. After a while, it became repetitive and exhausting. So I built a small tool for myself. What it does It takes in news and SEC filings, and turns them into structured daily summaries. Instead of reading dozens of articles, I can quickly see: what moved the market key takeaways per ticker overall market flow after the close 3.Key features Daily market close reports On-demand per-ticker analysis (cached after first run) ETF composition and trend insights Challenges One of the hardest parts was balancing cost vs performance. Initially, I wanted real-time generation, but LLM + data API costs were too high. So I switched to: → generate once after market close → cache results for fast access This reduced costs significantly. What I learned AI feels more like amplification than replacement Small problems can take an entire day to solve Infrastructure (AWS, C