---
title: "Slides: HTML is All You Need (for Agents to Make Graphics) - Amol Kapoor, Nori"
category: "slides"
video_id: "JRTAtZ5iBkU"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: HTML is All You Need (for Agents to Make Graphics) - Amol Kapoor, Nori

## Source Video
[HTML is All You Need (for Agents to Make Graphics) - Amol Kapoor, Nori](https://www.youtube.com/watch?v=JRTAtZ5iBkU)

## 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/JRTAtZ5iBkU/slide-001.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/JRTAtZ5iBkU/slide-001.html)
- AI slide classifier: `title_card` confidence `0.99`
- Text source: agent_vision.

Slide text:

> Hi — I’m Amol.
> We deploy an AI employee that understands your company,

![[assets/slides/JRTAtZ5iBkU/slide-002.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/JRTAtZ5iBkU/slide-002.html)
- AI slide classifier: `content_slide` confidence `0.99`
- Text source: agent_vision.

Slide text:

> THE REAL COST
> THE SAME DECK
> 10 hrs
> 25 min
> ↓ 24× faster

![[assets/slides/JRTAtZ5iBkU/slide-003.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/JRTAtZ5iBkU/slide-003.html)
- AI slide classifier: `content_slide` confidence `0.95`
- Text source: none.
- OCR decision: ready — Dense code/proprietary-format slide is better handled by OCR than manual transcription.
![[assets/slides/JRTAtZ5iBkU/slide-004.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/JRTAtZ5iBkU/slide-004.html)
- AI slide classifier: `title_card` confidence `0.99`
- Text source: agent_vision.

Slide text:

> NO.
> agents aren't the problem.

![[assets/slides/JRTAtZ5iBkU/slide-005.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/JRTAtZ5iBkU/slide-005.html)
- AI slide classifier: `content_slide` confidence `0.96`
- Text source: none.
- OCR decision: ready — Multi-panel diagram with code and UI text is better suited to OCR extraction than manual transcription.
![[assets/slides/JRTAtZ5iBkU/slide-006.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/JRTAtZ5iBkU/slide-006.html)
- AI slide classifier: `content_slide` confidence `0.96`
- Text source: agent_vision.
- OCR decision: ready — Grid of small cards and labels is OCR-suitable; the slide title is short enough to preserve directly.

Slide text:

> SLIDE DECKS → HTML


Classification audit: `raw/sources/slide-ai-classification/slides/JRTAtZ5iBkU/audit.json`

## 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.