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Slides: Building AI Agents that actually automate Knowledge Work - Jerry Liu, LlamaIndex

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Building AI Agents that actually automate Knowledge Work - Jerry Liu, LlamaIndex

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

Extracted Slides

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OCR text:

INNOVATIONPARTNER

aws

PLATINUMSPONSORS

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WWindsurf

MongoDB

daily

augment code

Workos

slide-002.jpg

OCR text:

Al Agents can “Automate Knowledge Work"

A big promise of Al agents is making a me eg ey xe ‘

knowledge workers more efficient:

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But does “knowledge work automation” just -

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slide-003.jpg

OCR text:

The Alpha is in Unstructured Data

90% of Enterprise Data Lives in

Documents*

Humans historically needed to read/write ‘i "

juman

these documents.

For the first time, Alagents can reason ets \ \

and act over massive amounts of . —s a Ry

unstructured context tokens. Agent

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slide-004.jpg

OCR text:

Special Release: Excel!

We built an Excel agent capable of:

1. Data Transformation: Transforming wore mmene mrs mmm = . . a

each sheet into a normalized 2D CEN. 0 Teaiela oua pares: he

format. —_

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slide-005.jpg

OCR text:

Automation UX

Use Cases Be aie =

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@ Patient Record Extraction .

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slide-006.jpg

OCR text:

AIE

Document

Agent Use Cases

Real-world use cases

of workflow automation

aws

slide-007.jpg

OCR text:

[Automation + Assistant UX] Financial Due Diligence

CARLYLE

Use Case

An e2e leveraged buyout agent

Impact

“This end-to-end agentic

workflow to do a leveraged

buyout model created

decision-making value in the

tens of millions of dollars.”

LlamaCloud

Excel Normalization

Agent

Document Extraction

Agent

SQL Tool

Vector Retrieval

Tool

File Tool

LlamaIndex

Ask your Excel agent

Due Diligence Copilot

28

slide-008.jpg

OCR text:

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for Document Al

Llamalndex :5 tne most accurate and Custamizable “~—

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with agentic Al,

Backed By: Greylock, NVP

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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.