---
title: "Reconstructed Slides: Why Agent Engineering — swyx"
category: "slides"
video_id: "5N33E9tC400"
sourceLabels: ["Cropped public YouTube video frames", "Local OpenCV slide-region detection", "Local RapidOCR"]
---

# Reconstructed Slides: Why Agent Engineering — swyx

## Source Video
[Why Agent Engineering — swyx](https://www.youtube.com/watch?v=5N33E9tC400)

## Method
This deck is reconstructed from the existing video frame captures by detecting likely slide regions with OpenCV, cropping/upscaling those regions, deduplicating similar crops, and OCRing the cropped slide images locally. It is a cleaner companion to the full-stage frame deck.

## Reconstructed Slides
![[assets/reconstructed-slides/5N33E9tC400/slide-001.jpg]]

- Source frame: `slide-001.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `175.78`
![[assets/reconstructed-slides/5N33E9tC400/slide-002.jpg]]

- Source frame: `slide-002.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `166.49`
![[assets/reconstructed-slides/5N33E9tC400/slide-003.jpg]]

- Source frame: `slide-003.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.79`
![[assets/reconstructed-slides/5N33E9tC400/slide-004.jpg]]

- Source frame: `slide-004.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `155.53`
![[assets/reconstructed-slides/5N33E9tC400/slide-005.jpg]]

- Source frame: `slide-005.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `166.4`
![[assets/reconstructed-slides/5N33E9tC400/slide-006.jpg]]

- Source frame: `slide-006.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `175.35`
![[assets/reconstructed-slides/5N33E9tC400/slide-007.jpg]]

- Source frame: `slide-007.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `175.61`
![[assets/reconstructed-slides/5N33E9tC400/slide-008.jpg]]

- Source frame: `slide-008.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `163.26`
![[assets/reconstructed-slides/5N33E9tC400/slide-009.jpg]]

- Source frame: `slide-009.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `177.27`
![[assets/reconstructed-slides/5N33E9tC400/slide-010.jpg]]

- Source frame: `slide-010.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `156.63`
![[assets/reconstructed-slides/5N33E9tC400/slide-011.jpg]]

- Source frame: `slide-011.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `175.08`
![[assets/reconstructed-slides/5N33E9tC400/slide-012.jpg]]

- Source frame: `slide-012.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `160.42`
![[assets/reconstructed-slides/5N33E9tC400/slide-013.jpg]]

- Source frame: `slide-013.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `175.23`
![[assets/reconstructed-slides/5N33E9tC400/slide-014.jpg]]

- Source frame: `slide-014.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `165.8`
![[assets/reconstructed-slides/5N33E9tC400/slide-015.jpg]]

- Source frame: `slide-015.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `166.41`
![[assets/reconstructed-slides/5N33E9tC400/slide-016.jpg]]

- Source frame: `slide-016.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.88`
![[assets/reconstructed-slides/5N33E9tC400/slide-017.jpg]]

- Source frame: `slide-017.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `172.87`
![[assets/reconstructed-slides/5N33E9tC400/slide-018.jpg]]

- Source frame: `slide-018.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `174.45`
## Dense Scene-Detected Slide Candidates
- [[youtube-5N33E9tC400-dense-slides]]