---
title: "Slides: I Run a Fleet of AI Agents Across Three Machines. Here's What Broke. - Kyle Jaejun Lee, KRAFTON"
category: "slides"
video_id: "4kYl2_mqmnQ"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: I Run a Fleet of AI Agents Across Three Machines. Here's What Broke. - Kyle Jaejun Lee, KRAFTON

## Source Video
[I Run a Fleet of AI Agents Across Three Machines. Here's What Broke. - Kyle Jaejun Lee, KRAFTON](https://www.youtube.com/watch?v=4kYl2_mqmnQ)

## 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/4kYl2_mqmnQ/slide-001.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-001.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: agent_vision.

Slide text:

> The fleet
> MacBook
> heavy coding + personal projects
> macOS · sleeps
> Linux A
> long-running coding tasks
> headless · always-on
> Linux B
> short-lived personal side projects
> headless · always-on

![[assets/slides/4kYl2_mqmnQ/slide-002.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-002.html)
- AI slide classifier: `content_slide` confidence `0.95`
- Text source: agent_vision.
- OCR decision: ready — product UI screenshot with many small text elements

Slide text:

> The fleet, on screen

![[assets/slides/4kYl2_mqmnQ/slide-003.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-003.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: agent_vision.

Slide text:

> I don't compact — I reset.
> compact
> X slow
> X can't choose what survives
> X dropped = gone
> reset
> fresh agent
> re-reads the files
> continues

![[assets/slides/4kYl2_mqmnQ/slide-004.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-004.html)
- AI slide classifier: `content_slide` confidence `0.95`
- Text source: agent_vision.
- OCR decision: ready — dense CLI and diagram content with small text

Slide text:

> Failure 1 agents do the work instead of dispatching it

![[assets/slides/4kYl2_mqmnQ/slide-005.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-005.html)
- AI slide classifier: `content_slide` confidence `0.96`
- Text source: agent_vision.
- OCR decision: ready — dense multi-pane terminal/grid layout with small text

Slide text:

> Failure 2 panes too small

![[assets/slides/4kYl2_mqmnQ/slide-006.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-006.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: agent_vision.
- OCR decision: ready — diagram with small labels and embedded terminal-style content

Slide text:

> Failure 4 git credentials collide

![[assets/slides/4kYl2_mqmnQ/slide-007.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-007.html)
- AI slide classifier: `content_slide` confidence `0.99`
- Text source: agent_vision.

Slide text:

> Failure 5 the laptop dies
> The MacBook loses power or drops off the network — and every in-progress job dies with it.

![[assets/slides/4kYl2_mqmnQ/slide-008.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-008.html)
- AI slide classifier: `content_slide` confidence `0.95`
- Text source: agent_vision.
- OCR decision: ready — Discord UI screenshot with many small text elements

Slide text:

> I forgot which machine I'd built the feature on.

![[assets/slides/4kYl2_mqmnQ/slide-009.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-009.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: agent_vision.
- OCR decision: ready — Diagram slide with multiple small labels and boxes that are better suited for OCR than manual transcription.

Slide text:

> The convergence

![[assets/slides/4kYl2_mqmnQ/slide-010.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/4kYl2_mqmnQ/slide-010.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: agent_vision.

Slide text:

> What I'm building on top
> Orchestration manager
> Kubernetes
> If you're running agents at any scale, let's compare notes.


Classification audit: `raw/sources/slide-ai-classification/slides/4kYl2_mqmnQ/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.