June 29 – July 2, 2026 · San Francisco, CA · imported from ai.engineer's public schedule feed

AI Engineer World's Fair 2026 — unofficial import demo

Unofficial demo. This programme was imported from the AI Engineer World's Fair's own public schedule feed to show vibeboard at real conference scale. Not affiliated with, or endorsed by, the organisers.

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Search & RetrievalSession

Pinecone 2.0

Edo Liberty

When
Tuesday, June 3010:45 AM – 11:05 AM · 20 min
Where
Track 3San Francisco, CA · imported from ai.engineer's public schedule feed
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About this session

Autonomous agents are smart but don’t know your business or your objectives. That’s why most agents in the enterprise remain stuck in retrieval loops, burning millions of tokens on processing raw documents

A shift from traditional retrieval systems + agents (aka RAG) to purpose-built knowledge engines is underway.

I'll talk about why moving reasoning upstream and compiling raw enterprise data into specialized, task-specific context artifacts is critical to unlocking reliable agentic workflows. And I'll show you how offloading knowledge management to a dedicated layer enables engineering teams to achieve up to a 90% reduction in token consumption while drastically improving task completion rates, speed, and accuracy.

Speaker

Edo Liberty
Edo Liberty

Founder and Chief Scientist, Pinecone

Edo Liberty is the founder and Chief Scientist of Pinecone. Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 10,000 customers and 1M developers worldwide. Before founding Pinecone, Edo was a Director of Research at AWS and Head of Amazon AI Labs where his team built cutting-edge machine learning algorithms, systems, and services including parts of Amazon SageMaker and OpenSearch. Edo holds a B.Sc in Physics and Computer Science from Tel Aviv University, and a Ph.D. in Computer Science from Yale. As an academic Edo taught at Tel Aviv University and at Princeton and has authored more than 75 papers and patents. His research focused on mathematical foundations of AI, optimization, streaming algorithms, machine learning, numerical linear algebra, and high dimensional data mining.

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