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

Agents are all the rage in 2025, and every single b2b SaaS startup/incumbent promises AI agents that can "automate work" in some way. But how do you actually build this? The answer is two fold: 1. really really good tools 2. carefully tailored agent reasoning over these tools that range from assistant-to-automation based UXs. The main goal of this talk is to a practical overview of agent architectures that can automate real-world work, with a focus on document-centric tasks. Learn the core building blocks of best-in-class "tools" around processing, manipulating, and indexing/retrieving PDFs to Excel spreadsheets. Also learn the range of agent architectures suited for different tasks, from chat assistant-based UXs with high human-in-the-loop, to automation UXs that rely on encoding a business process into an end-to-end task solver. These architectures have to be generalizable but also highly accurate as agents get increasingly better at reasoning and code-writing. About Jerry Liu Jerry is the co-founder/CEO of LlamaIndex, the most accurate and flexible way to automate your document workflows with AI agents. Before this, he led the ML monitoring team at Robust Intelligence, did self-driving AI research at Uber ATG and worked on recommendation systems at Quora. Recorded at the AI Engineer World's Fair in San Francisco. Stay up to date on our upcoming events and content by joining our newsletter here: https://www.ai.engineer/newsletter