How are people actually setting up workflows with market data without it turning

<!-- SC_OFF --><div class="md"><p>Just went through a Stanford paper that tracked 51 actual AI deployments - not surveys or sentiment polls, real production systems across 41

<!-- SC_OFF --><div class="md"><p>I'll be upfront about my endgame: I work at a large tech company, I have a niche picked out, and I'm making the move to build and sell AI agents

<!-- SC_OFF --><div class="md"><p>Public datasets on HF or Kaggle can sometimes be too generic, wrong domain, wrong schema, outdated, or just not enough volume to generalize

<!-- SC_OFF --><div class="md"><p>I work in tech and try to keep up with the crazy pace of AI releases, new models, research papers, and useful tools. The problem is there’s so

<!-- SC_OFF --><div class="md"><p>Cursor dropped their new product yesterday and its not a code editor anymore. its an agent orchestration console that happens to have an editor

<!-- SC_OFF --><div class="md"><p>I am trying to understand the current consensus and legal landscape regarding how public data and developer contributions are being utilized by

<table> <tr><td> <a href="https://www.reddit.com/r/ChatGPT/comments/1t6vy7j/the_80_billion_backlog_q1_2026_showed_ai_demand/"> <img alt="The $80 Billion Backlog: Q1 2026 Showed AI

<!-- SC_OFF --><div class="md"><p>I want to believe in agents, but I am stuck in this gap between a cool concept and daily reality. On social media it is always these perfect