Markdown source

Using LLMs to Secure Source Code

Conference Context

Session Description

Models are now finding and fixing real vulnerabilities at scale. Drawing on Anthropic's work with security teams, this talk walks a six-step workflow — threat model, sandbox, discover, verify, triage, patch — through one running example, shows where orgs actually bottleneck, and gives you a copy-paste path to your first scan.

Media Evidence

Recsys Keynote: Improving Recommendation Systems & Search in the Age of LLMs - Eugene Yan, Amazon (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).

Evidence Graph

This evidence graph is generated from currently linked source material: official schedule text, related video pages, cached transcripts, visible slide text, dense/reconstructed slide pages, and AI slide-classification audits.

Media Signals

Agent Reading Notes

Use these signals to refine the synopsis, topic links, people/company context, and method notes. If a source is a related external video rather than an exact official recording, keep it framed as supporting evidence.

Transcript Status

Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Not fetched yet.

People

Supporting Slides

Synthesis

Synthesized Breakdown

Using LLMs to Secure Source Code ## Conference Context - Date/time: 2026-06-29 · 1:30pm-1:50pm - Track/room: Security · Track 5 - Speaker(s): Eugene Yan - Session type/status: sponsor · confirmed - Track: Security - Room: Track 5 - Session type: sponsor - Status: confirmed ## Session Description Models are now finding and fixing real vulnerabilities at scale. Drawing on Anthropic's work with security teams, this talk walks a six-step workflow — threat model, sandbox, discover, verify, triage, patch — through one running example, shows where orgs actually bottleneck, and gives you a copy-paste path to your first scan. ## Media Evidence Recsys Keynote: Improving Recommendation Systems & Search in the Age of LLMs - Eugene Yan, Amazon (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions). - Source video: youtube-2vlCqD6igVA - Slide deck: Reconstructed Slides: Recsys Keynote: Improving Recommendation Systems & Search in the Age of LLMs - Eugene Yan, Amazon — 2 visible slide image(s); 2 HTML recreation(s).

Speaker And Company Context

Topics Covered

Derived Links And Source Material

Novel Concepts / Clever Methods

Evidence Boundary

This synthesis is based on the official schedule and linked source pages. It should be revisited when exact session recordings or transcript-backed secondary sources are available.