---
title: "Slides: LLM Observability, Evaluation, Experimentation Platform — Dat Ngo, Arize"
category: "slides"
video_id: "JsCCrBF7F1g"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: LLM Observability, Evaluation, Experimentation Platform — Dat Ngo, Arize

## Source Video
[LLM Observability, Evaluation, Experimentation Platform — Dat Ngo, Arize](https://www.youtube.com/watch?v=JsCCrBF7F1g)

## Relationship To World's Fair 2026
These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.

## Related Scheduled Sessions
- No individual scheduled session mapping has been assigned yet; treat this as an event livestream deck.

## Extracted Slides
![[assets/slides/JsCCrBF7F1g/slide-001.jpg]]

OCR text:

> PLATINUM SPONSORS
> Braintrust WorkOS OpenAI

![[assets/slides/JsCCrBF7F1g/slide-002.jpg]]

OCR text:

> Sevan bee ne ET a)
> mn . ‘ @ arize 7 .
> cae ‘ LLM Observability, Evaluation,” | ~~, ;
> - Experimentation Platform Be
> Google DeepMind

![[assets/slides/JsCCrBF7F1g/slide-003.jpg]]

OCR text:

> observe
> Registration is open for Arize Observe 2026 →
> Ship Agents that Work
> AI & Agent Engineering Platform. One place for development,
> observability, and evaluation.
> Get Started
> Self-Host OSS
> Powering the world’s leading AI teams
> AIE
> Braintrust WorkOS OpenAI

![[assets/slides/JsCCrBF7F1g/slide-004.jpg]]

OCR text:

> Building GenAl is Hard, So How Are Teams Tackling This?
> 
> vt — ~
> &
> Observability “|
> 
> rs What is happening in my application? Can Erle
> en ba in | root cause down into the problem? Experimentation &
> NX. i
> * x Improvement
> Paar (+) i The ultimate goal of
> Nw observability and evaluation
> 
> . ] : is to know where to iterate
> 
> [5] and know where to improve
> 5 the system
> Evaluation
> How well is the Al product that I've built, ,
> actually performing according my
> criteria?
> | ~s Aorze
> ce a i
> | Al Engineer |
> EUROPE

![[assets/slides/JsCCrBF7F1g/slide-005.jpg]]

OCR text:

> Building GenAI is Hard, So How Are Teams Tackling This?
> Observability
> Evaluation
> Experimentation & Improvement

![[assets/slides/JsCCrBF7F1g/slide-006.jpg]]

OCR text:

> Evaluators
> Create valuator
> QSA
> QA
> AIE
> tepst
> Engineering the future of Al
> \Engineer

![[assets/slides/JsCCrBF7F1g/slide-007.jpg]]

OCR text:

> AI Engineer
> EUROPE
> HTTPS://AI.ENGINEER

## Slide-Derived Subjects To Review
Subject extraction uses video title, related session titles/descriptions, transcript context, and OCR text when available. OCR is best-effort and should be reviewed against the embedded slide images.