Agentic AI Summit 2025
optimization. Learn how to maintain data security with LLM clone models, as well as how to leverage structured output response formats. I'd focus on lessons around building the Troubleshooting Agent here at Monte Carlo, including: - The problem definition (and why this problem was suited for AI) - Getting to production / value - How it's built – a review of the multi-agent architecture built with Claude, LangGraph - What it does – a demo or overview of the user interaction - How we evaluate model quality - Tips for how to get started building agents Attendees will walk away with a deeper understanding of best practices for product research, validations, task splitting, workflows, security, and perhaps the most difficult, knowing when to be patient when it comes to effective Agentic AI development.
About This Conference
optimization. Learn how to maintain data security with LLM clone models, as well as how to leverage structured output response formats. I'd focus on lessons around building the Troubleshooting Agent here at Monte Carlo, including: - The problem definition (and why this problem was suited for AI) - Getting to production / value - How it's built – a review of the multi-agent architecture built with Claude, LangGraph - What it does – a demo or overview of the user interaction - How we evaluate model quality - Tips for how to get started building agents Attendees will walk away with a deeper understanding of best practices for product research, validations, task splitting, workflows, security, and perhaps the most difficult, knowing when to be patient when it comes to effective Agentic AI development.
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Date & Time
Wednesday, January 1, 2025 - Monday, April 21, 2025