Imagine having a team of expert AI agents constantly analyzing news, charts, and market trends to predict the best stock moves. That's the promise of FinVision, a new multi-agent framework designed to crack the code of stock market prediction. Unlike traditional methods that crunch numbers and struggle with the nuances of market sentiment, FinVision uses the power of large language models (LLMs) to understand the market like a human expert. Each agent specializes in a different aspect of analysis, from summarizing financial news to interpreting complex candlestick charts. These agents then collaborate, sharing insights and refining their predictions through a unique "reflection" process where they learn from past trades. Tested on tech giants like Apple, Amazon, and Microsoft, FinVision showed promising results, outperforming traditional rule-based and basic reinforcement learning models. While it didn't quite beat the top-performing LLM-based trading agent (FinAgent), it achieved this with significantly less training time, suggesting huge potential for improvement. The secret sauce? FinVision’s reflection module. This allows the AI to learn from its mistakes and adapt to changing market conditions. Imagine an AI that constantly learns and improves its strategies – that's the power of reflection. While not a crystal ball, FinVision offers a fascinating glimpse into the future of AI-driven investing. Integrating news sentiment, technical analysis, and historical performance, this framework aims for smarter, more explainable trading decisions. The next step is to supercharge FinVision with reinforcement learning, allowing it to fine-tune its strategies in real-time. Could this be the key to finally unlocking consistent market-beating returns? Only time will tell, but FinVision represents a significant leap forward in the quest to build an AI that can truly understand and predict the stock market.