From Vibe to Live: How to Build and Deploy Agentic AI Products for Enterprises
GenAI & Data
Rafael Pierre guides participants through the complete lifecycle of building production-ready agentic AI systems for enterprise banking. Drawing from a live pilot deployment using OpenAI Agents SDK and Phoenix Arize, this workshop demystifies multi-agent orchestration, observability strategies, and deployment patterns. Attendees will architect a conversational loan application system, implement agent coordination, and establish monitoring frameworks that satisfy enterprise requirements. This technical session bridges the gap between proof-of-concept demos and scalable production systems through real-world banking use cases.
Time & Place
October 30, 2025
13:30 - 15:00
Hôtel Mövenpick Amsterdam City Centre
Matterhorn I
Limited to 45 participants.
Meet Your Intructors

Rafael Pierre
Founder, Principal AI Engineer, weet.ai
Rafael Pierre is a Principal AI Engineer with a rare blend of experience across both AI hyperscalers and enterprise financial institutions. Having held key roles at Hugging Face and Databricks, he has deep expertise in large-scale AI infrastructure and open-source ecosystems. Rafael has also led the implementation of production-grade AI systems at major financial institutions such as ING Bank and ABN Amro, equipping him with practical insights into deploying conversational AI at scale in complex, regulated environments.
He specializes in advanced AI agent architectures, including Model Context Protocol (MCP), OpenAI Agents SDK, and session management systems designed for long-term memory in multi-agent environments. This powerful combination of hyperscaler innovation and real-world enterprise deployment positions Rafael as a unique voice in bridging cutting-edge AI capabilities with practical business outcomes.
What To Expect
Who Is This For?
Product Managers & Product Owners
AI/ML Engineers & Developers
IT Decision Makers & Enterprise Architects
Data & Platform Engineers
Pre-Requisites
Basic understanding of LLMs and conversational AI
Familiarity with API-based development and Python
Interest in enterprise software deployment
Laptop with ability to run Python applications
What You'll Learn & Do?
Architect multi-agent systems effectively
Implement enterprise observability patterns
Debug agent interactions systematically
Design conversation flows strategically
Agenda & Activities
Agenda for this session:
Getting Settled - 5 mins
Information Session - 40 mins
Break - 5 min
Individual / Group Exercise - 20 min
Q&A/Discussion - 20 min
Reflection - 5 min
Prerequisits:
Basic understanding of LLMs and conversational AI
Familiarity with API-based development and Python
OpenAI API Key
Laptop with Python 3.13 and Docker installed
VSCode
Git for cloning starter repository
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