Field Engineering at Databricks|Ex-Microsoft | 40 under 40 | Forbes Tech Council| Senior Member IEEE Princeton
Delighted to share that I have successfully completed an amazing short course on AutoGen. 🚀 AutoGen enables building next-gen LLM applications based on multi-agent conversations with minimal effort. It simplifies the orchestration, automation, and optimization of a complex LLM workflow. Here's my perspective on one of the many applications of agentic design patterns in the financial services industry: an autonomous equity research analysis workflow. ✅ Equity research analyst asks copilot to generate research report on a company or a sector ✅ User proxy agent gives the instructions to planner ✅ Planner agent creates a plan to invoke multiple conversable agents in specific order ✅ Engineer agent writes code to gather real-time market and news data combined with proprietary data ✅ Executor agent runs the code and auto tweaks for performance ✅ Writer agent consumes the quant data from executor and creates a report including investment thesis, financial projections, valuations, potential risks and catalysts ✅ Risk and compliance monitoring agent provide feedback to the writer agent from regulatory lens ✅ Writer agent adjusts the report ✅ Human in the loop to review and confirm the final report Cut the cycle time from days to minutes. 💹 https://lnkd.in/e3Q5QC3c #AutoGen #MicrosoftResearch
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