Slides: Building an ACP-Compatible Agent Live — Bennet Fenner, Zed

Source Video

Building an ACP-Compatible Agent Live — Bennet Fenner, Zed

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 0.96
Text source: none.
OCR decision: ready — Dense multi-column agent catalog with many small labels; OCR is the better extraction path.

Recreated text/layout view: open HTML recreation
AI slide classifier: content_slide confidence 0.93
Text source: none.
OCR decision: ready — Code editor screenshot with small source text; OCR will capture the code more reliably than vision transcription.

Hidden Non-Slide Evidence

`slide-001.jpg` — speaker_stage confidence 0.95; Speaker-on-stage shot with a projected title; not a standalone content slide.
`slide-002.jpg` — title_card confidence 0.98; Intro/title card with branding and speaker inset, not a content slide.
`slide-005.jpg` — sponsor_logo confidence 0.99; Branding/closing card only; no presentation content to extract.

Classification audit: raw/sources/slide-ai-classification/slides/HsxQICTLF84/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.