Jennifer Reif

Jennifer Reif

Jennifer Reif

Jennifer Reif

Neo4j developer advocate who turns scattered data into clear steps for building better AI apps

Session

Workshop

Date

Monday, November 30

Level

Intermediate

// AI Engineering Skill /

Grounding models with data

// 01 / Bio

Jennifer Reif is a Developer Advocate at Neo4j, speaker, and writer who helps developers make better use of their data. An avid developer and problem-solver, she explores databases, data modeling, and emerging technologies like AI through hands-on experiments, sharing what she learns at conferences and digital channels around the world. With a background in CMIS and a knack for untangling complex systems, Jennifer focuses on turning scattered data and complex topics into clear, understandable actions to build better applications.

// 02 / The session

Find the wrong evidence before your users do

Abstract

Your agent just gave a customer the wrong refund decision and attached a real company policy to prove it. Now the customer has a screenshot. The passage matched the question. It came from a policy version that didn’t apply to that customer on that date.

In this hands-on workshop you’ll pull apart how that happened and repair it with the simplest approach that works. Then you’ll take on a harder case, where the answer depends on connections across customer, product and policy data. A small set of checks shows when the system has found applicable evidence, and when it should stop.

What you’ll learn

Spot evidence that matches but doesn’t apply

Use graph connections across your data

Know when an agent should stop

What to bring

Laptop

Free Neo4j Aura instance

set up before the session

GitHub account

Skills you’ll practice

AI DEV · BY DEEPLEARNING.AI

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