Dense Slides: How LLMs work for Web Devs: GPT in 600 lines of Vanilla JS - Ishan Anand

Source Video

How LLMs work for Web Devs: GPT in 600 lines of Vanilla JS - Ishan Anand

Method

This deck is slide-only. The existing captured video frame set supplies candidate frames, then local OpenCV rejects sponsor/title/speaker-only frames, crops visible slide surfaces, deduplicates, and saves the cropped slide images.

Cropped Visible Slides

Recreated text/layout view: open HTML recreation
AI slide classifier: title_card confidence 0.98
Text source: agent_vision.

Slide text:

HOW LLMS WORK FOR WEB DEVS

GPT in 600 lines of Vanilla JavaScript

Ishan Anand

Spreadsheets-are-all-you-need.ai

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.97
Text source: none.
OCR decision: ready — dense paper screenshot, small diagram labels, and multi-column technical text are better handled by OCR

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.98
Text source: agent_vision.

Slide text:

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Classification audit: raw/sources/slide-ai-classification/dense/ZuiJjkbX0Og/audit.json