23:13
Evaling Video Slop — Maor Bril, Character.ai
Maor Bril, a two-year veteran of Character.ai, addresses a widening gap in the AI video space: while generation models like Kling, Se...
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20:24
From Agent Traces to Agent Simulations — Rustem Feyzkhanov, Snorkel AI
Rustem Feyzkhanov, head of the AI platform team at Snorkel AI, presents the case that private benchmarks built from production traces...
17:57
Loop Engineering from First Principles — Kyle Mistele, HumanLayer
Kyle Mistele, co-founder of HumanLayer, presents a principled engineering framework for building AI coding loops that work in product...
21:17
Evals-Driven Development for a Mental Health AI Coach — Akele Reed & Dave Revere, SonderMind
Akele Reed and Dave Revere from SonderMind present the engineering architecture behind Sonder, a clinically grounded AI mental health...
19:29
How Evals and Prompts Shape Agent Behavior — Preetika Bhateja & Daniel Bump, YouTube Ads
Preetika Bhateja and Daniel Bump, engineers on the YouTube Ads image and video models team at Google, share practical lessons from bu...
20:36
From Signal to PR: Anatomy of a Self-Improving Agent — Jason Lopatecki, Arize
Jason Lopatecki, co-founder of Arize AI, delivers a technical deep-dive at the AI Engineer conference on how to build agents that imp...
20:27
Video Has No Memory. Here’s How We Built One. — James Le, TwelveLabs
James Le, Head of Developer Relations at TwelveLabs, presents at AI Engineer World's Fair on building a memory layer for video intell...
21:18
Why Agentic Systems Need Ontologies — Frank Coyle, UC Berkeley
Frank Coyle, a computer science educator at UC Berkeley with over 35 years of experience and a background in neuroscience, delivered...
20:54
Citation Needed: Provenance for LLM-Built Knowledge Graphs — Daniel Chalef, Zep AI
Daniel Chalef, co-founder of Zep AI, presents at AI Engineer World's Fair on engineering provenance and lineage into LLM-built knowle...
18:04
Local Agentic Theory For Mobile Games — Shafik Quoraishee & Joanne Song, The New York Times
Shafik Quoraishee and Joanne Song from The New York Times present experimental research on running local AI agents for accessible mob...
15:58
From Systems of Record to Systems of Context — Omri Bruchim, monday.com
Engineering managers Omri Bruchim and Tor from monday.com presented at AI Engineer on how the company is transforming its work manage...
20:42
CrabRAG: Why Automated Assistants Need Graph Memory, Not More Tokens — Stephen Chin, Neo4j
Stephen Chin, head of developer relations at Neo4j, delivered a conference talk at AI Engineer presenting CrabRAG — a graph-based mem...
19:20
Your agent architecture has a half-life of 6 months — Dan Farrelly, CTO, Inngest
Dan Farrelly, CTO and co-founder of Inngest, takes the AI Engineer conference stage to argue that every agent system has a measurable...
18:02
The Desktop Frontier — Ahmad Osman, Osmantic
Ahmad Osman of Osmantic delivers a data-heavy conference presentation tracking the rapid compression of AI capability into consumer a...
25:38
Why Your Agent Disagrees With Itself (And What To Do About It) – Diane Lin, Datadog
Datadog AI lead Diane Huang Lin — formerly of Alexa, Vicarious (now Google DeepMind), and Zscaler — presents a systematic treatment o...
12:08
Enterprise Agents Have a Structure Problem – Ishita Daga, Tesla
Ishita Daga, a machine learning engineer at Tesla building enterprise agents, argues that when a data agent gives a wrong answer, the...