Markdown source

Slides: How we taught agents to use good retrieval - Hanna Lichtenberg, Mixedbread AI

Source Video

How we taught agents to use good retrieval - Hanna Lichtenberg, Mixedbread AI

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: none.
• OCR decision: ready — diagram slide with small labels and axis text

• Recreated text/layout view: open HTML recreation
• AI slide classifier: content_slide confidence 0.93
• Text source: none.
• OCR decision: ready — dense quote and bullet text

• Recreated text/layout view: open HTML recreation
• AI slide classifier: content_slide confidence 0.99
• Text source: agent_vision.
• OCR decision: ready — timeline graphic with small table text

Slide text:

Agent trajectories - timeline

• Recreated text/layout view: open HTML recreation
• AI slide classifier: content_slide confidence 0.99
• Text source: agent_vision.
• OCR decision: ready — tool-call table and nested UI text are small

Slide text:

Agent trajectories - tool calls

Hidden Non-Slide Evidence

• `slide-001.jpg` — title_card confidence 0.97; speaker intro card with headshots and names

Classification audit: raw/sources/slide-ai-classification/slides/1IdzkRVmWAA/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.