Session led by Jerry Liu, Co-founder and CEO at LlamaIndex

Learn the building blocks of autonomous agents, including core architectures, planning methods, memory systems, and leading development frameworks.

Learn the building blocks of autonomous agents, including core architectures, planning methods, memory systems, and leading development frameworks.

Learn the building blocks of autonomous agents, including core architectures, planning methods, memory systems, and leading development frameworks.

Dive into advanced reasoning, multi-agent coordination, tool chaining, self-healing workflows, and emerging security challenges.

Dive into advanced reasoning, multi-agent coordination, tool chaining, self-healing workflows, and emerging security challenges.

Dive into advanced reasoning, multi-agent coordination, tool chaining, self-healing workflows, and emerging security challenges.

Focus on real-world applications with sessions on agent evaluation, reliability, deployment strategies, and cumulative demo showcases.

Focus on real-world applications with sessions on agent evaluation, reliability, deployment strategies, and cumulative demo showcases.

Focus on real-world applications with sessions on agent evaluation, reliability, deployment strategies, and cumulative demo showcases.

The enterprise adoption of AI agents is accelerating, but significant challenges remain in making them truly reliable and effective. While coding assistants and customer service agents are already delivering value, more complex document-based workflows require sophisticated architectures and data processing capabilities. How do you design agent systems that can handle the complexity of enterprise documents with their tables, charts, and unstructured information? What's the right balance between general reasoning capabilities and constrained architectures for specific business tasks? Should you centralize your agent infrastructure or purchase vertical solutions for each department? The answers lie in understanding the fundamental trade-offs between flexibility, reliability, and the specific needs of your organization. Jerry Liu is the CEO and Co-founder at LlamaIndex, the AI agents platform for automating document workflows. Previously, he led the ML monitoring team at Robust Intelligence, did self-driving AI research at Uber ATG, and worked on recommendation systems at Quora. In the episode, Richie and Jerry explore the readiness of AI agents for enterprise use, the challenges developers face in building these agents, the importance of document processing and data structuring, the evolving landscape of AI agent frameworks like LlamaIndex, and much more. Links Mentioned in the Show: LlamaIndexLlamaIndex Production Ready Framework For LLM AgentsTutorial: Model Context Protocol (MCP)Connect with JerryCourse: Retrieval Augmented Generation (RAG) with LangChainRelated Episode: RAG 2.0 and The New Era of RAG Agents with Douwe Kiela, CEO at Contextual AI & Adjunct Professor at Stanford UniversityRewatch RADAR AI  New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

This session is repeated. One of the biggest promises for LLM agents is automating all knowledge work over unstructured data — we call these "knowledge agents". To date, while there are fragmented tools around data connectors, storage and agent orchestration, AI engineers have trouble building and shipping production-grade agents beyond basic chatbots. In this session, we first outline the highest-value knowledge agent use cases we see being built and deployed at various enterprises. These are: Multi-step document research, Automated document extraction Report generation We then define the core architectural components around knowledge management and agent orchestration required to build these use cases. By the end you'll not only have an understanding of the core technical concepts, but also an appreciation of the ROI you can generate for end-users by shipping these use cases to production.

Unlock the power of generative AI and data. Join experts from LlamaIndex and Google Cloud databases and learn how to seamlessly integrate LlamaIndex with AlloyDB and Cloud SQL for PostgreSQL, enabling your apps to reason, act on your data, and leverage the performance of Google Cloud. We’ll share real-world examples and code. Discover new possibilities for building advanced gen AI applications.

Are LLMs useful for enterprises? Well, what is the use of a large language model that is trained on trillions of tokens but knows little to nothing about your business.

To make LLMs actually useful for enterprises, it is important for them to retrieve company's data effectively. LlamaIndex has been at the forefront of providing such solutions and frameworks to augment LLMs.

In this episode, Jerry Liu, Co-founder and CEO of LlamaIndex, joins Raja Iqbal, CEO and Chief Data Scientist at Data Science Dojo, for a deep dive into the intersection of generative AI, data. and entrepreneurship.

Jerry walks us through the cutting-edge technologies reshaping the generative AI landscape such as LlamaIndex. He also explores Retrieval Augmented Generation (RAG) and fine-tuning in detail, discussing their benefits, trade-offs, use cases, and enterprise adoption, making these complex tools and topics not just easily understandable but also fascinating.

Jerry further ventures into the heart of entrepreneurship, sharing valuable lessons and insights learned along his journey, from navigating his corporate career at tech giants like Apple, Quora, Two Sigma, and Uber, to starting as a founder in the data and AI landscape.

Amidst the excitement of innovation, Raja and Jerry also address the potential risks and considerations with generative AI. They raise thought-provoking questions about its impact on society, for instance, whether we're trading critical thinking for convenience.

Whether you're a generative AI enthusiast, seasoned entrepreneur, or simply curious about the future, this podcast promises plenty of knowledge and insights for you.

Exploring agents with frameworks like Langchain and vector databases; learn how to build apps that can perform tasks autonomously.

Learn how to tune models on your own treasure trove of data.

Image generators like Midjourney and Stable Diffusion have gotten stronger and stronger in record time. Learn to leverage them for max effect now.

Learn about fine tuning, prompt tuning, guardrails, and middleware to make LLMs more consistent and reliable.

Find out about the latest attack vectors and how LLMs and generative AI present security challenges for teams and how you can mitigate those problems.

Jerry Liu is the CEO and co-founder of LlamaIndex. LlamaIndex is an open-source framework that helps people prep their data for use with large language models in a process called retrieval augmented generation. LLMs are great decision engines, but in order for them to be useful for organizations, they need additional knowledge and context, and Jerry discusses how companies are bringing their data to tailor LLMs for their needs. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.  The Analytics Engineering Podcast is sponsored by dbt Labs.