Slides: What if the harness mattered more than the model? - Aditya Bhargava, Etsy

Source Video

What if the harness mattered more than the model? - Aditya Bhargava, Etsy

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

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

Slide text:

About me

• Staff engineer at Etsy

• Also Etsy's IC Initiative Lead for Agentic Commerce

• Wrote Grokking Algorithms, an illustrated book on algorithms

• Blog at ducktyped.org

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.99
Text source: none.
OCR decision: ready — Dense code and error output are better suited to OCR than direct transcription.

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.98
Text source: none.
OCR decision: ready — Code and terminal text are dense and better handled by OCR.

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.97
Text source: none.
OCR decision: ready — Trace/log output is dense and OCR-suitable.

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.99
Text source: agent_vision.
OCR decision: ready — Code and small bullets are better captured by OCR.

Slide text:

04 - Partial function application (PFA)

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.82
Text source: none.
Slide text: not surfaced (illegible by AI classifier).

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.98
Text source: none.
OCR decision: ready — Terminal diff output is dense and OCR-suitable.

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.98
Text source: none.
OCR decision: ready — Dense benchmark and prompt-diff text is OCR-suitable.

Classification audit: raw/sources/slide-ai-classification/slides/2e9ANoOEn28/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.