Name: AIFAQ LFDT Lab Workshop
Start: 2025-10-14T10:00:00-04:00
End: 2025-10-14T12:00:00-04:00

# AIFAQ Lab Workshop (LFDT)

**Host:** Linux Foundation Decentralized Trust (LFDT)
**Project:** AIFAQ Lab — Enterprise AI Assistant, Snowflake, Multi-Agent RAG, GitMesh
**Format:** Live demo + hands-on walkthrough + Q&A (virtual)

## Workshop Title

**Building an Enterprise AI Assistant with Multi-Agent RAG (AIFAQ Lab)**
Learn how AIFAQ Lab turns scattered enterprise knowledge into secure, conversational workflows using multi-agent Retrieval-Augmented Generation (RAG). In 90 minutes, we’ll cover the reference architecture, data governance patterns, Snowflake-native packaging considerations, and a live demo of agent collaboration for real business tasks—then guide you through a hands-on prompt + evaluation exercise.

## Who Should Attend

* **Engineering & Data Leaders:** CTOs, Heads of Data/AI, Platform Engineers
* **Builders:** ML/AI engineers, Data engineers, Solutions architects
* **Domain Teams:** Product, Support/Success, Compliance & Security stakeholders

## Key Takeaways

* **Architecture:** How multi-agent RAG differs from single-agent chat; orchestration patterns, guardrails, and observability
* **Data Governance:** IP preservation, PII controls, retrieval quality, and evaluation loops
* **Packaging:** What changes when targeting **Snowflake Native App** delivery and Marketplace listing
* **Hands-On:** Prompt + context design, error analysis, and a simple eval scorecard you can reuse

## Agenda (90 minutes)

1. **Welcome & LFDT Context** (5 min)
2. **AIFAQ Lab Overview & Roadmap** (10 min)
3. **Architecture Deep Dive (Multi-Agent RAG)** (20 min)
4. **Live Demo: Agents Collaborating on a Real Task** (15 min)
5. **Hands-On Mini Lab: Prompting & Quick Eval** (20 min)
6. **Operationalizing: Security, Cost, and Snowflake-Native Path** (10 min)
7. **Q&A and Next Steps (Contribute, Pilot, Partner)** (10 min)

## Speakers

* **Gianluca Capuzzi** — Co-Founders AIFAQ
* **Ryan, Sumana, Jayaram, Lochan** — LFDT Mentee / Enterprise Advisor or Design-Partner Representative

## Prerequisites

* Basic familiarity with LLMs, embeddings, and vector search
* A modern browser; GitHub account if you’d like to follow along with example prompts/evals

## What You’ll Receive

* Slides & architecture diagrams
* A prompt/evaluation template (copy-ready)
* Links to the AIFAQ Lab repo, issues, and contribution guide

## Call to Action

* **Register** to receive the Zoom link and workshop materials.
* Interested in piloting AIFAQ Lab or contributing? Bring a use case—we’ll share the intake form at the end.

Bobbi Muscara

Princeton Blockchain & AI

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