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Building AI agents with Claude in Google Cloud's Vertex AI | Code w/ Claude

Building AI agents with Claude in Google Cloud's Vertex AI | Code w/ Claude

Ivan Nardini from Google Cloud demonstrates how to build, enhance, and productionalize AI agents using Google Cloud's agent stack. The session covers the challenges of deploying agents and introduces the Agent Development Kit (ADK) for building, the Vertex AI Agent Engine for managed deployment, and protocols like MCP and Agent-to-Agent for tool integration and inter-agent communication, using Claude on Vertex AI as the core LLM.

Enterprise AI Adoption Challenges

Enterprise AI Adoption Challenges

Paul van der Boor and Sean Kenny from Prosus detail the journey of Toqan, an internal AI platform that evolved from a Slack experiment into a sophisticated agentic system. They share insights on driving enterprise adoption, key metrics for measuring productivity, and their future vision of an "AI Workforce" where employees architect AI agents to automate complex, cross-system tasks.

Scaling Enterprise-Grade RAG: Lessons from Legal Frontier - Calvin Qi (Harvey), Chang She (Lance)

Scaling Enterprise-Grade RAG: Lessons from Legal Frontier - Calvin Qi (Harvey), Chang She (Lance)

A summary of the talk by Harvey and LanceDB on building a highly optimized retrieval architecture for the legal profession. It covers challenges like query complexity and data scale, the importance of evaluation, and how LanceDB's multimodal lakehouse architecture provides the necessary foundation.

Layering every technique in RAG, one query at a time - David Karam, Pi Labs (fmr. Google Search)

Layering every technique in RAG, one query at a time - David Karam, Pi Labs (fmr. Google Search)

David Karam, formerly of Google Search, presents a pragmatic framework for enhancing RAG systems, advocating a "quality engineering" approach. The talk progresses through a ladder of techniques, from in-memory retrieval and BM25 to custom embeddings, re-ranking, and advanced orchestration, emphasizing that the choice of technique should be driven by empirical analysis of system failures ("loss analysis") and balanced by a "complexity-adjusted impact" mindset.

Building a Smarter AI Agent with Neural RAG - Will Bryk, Exa.ai

Building a Smarter AI Agent with Neural RAG - Will Bryk, Exa.ai

Will Bryk, CEO of Exa, explains why traditional keyword-based search is insufficient for AI agents and introduces a new paradigm of neural, semantic search. He demonstrates how a hybrid approach, combining neural for discovery and keyword for precision, enables AI agents to perform complex, multi-step information retrieval tasks that were previously impossible.

Balaji Srinivasan: How AI Will Change Politics, War, and Money

Balaji Srinivasan: How AI Will Change Politics, War, and Money

Technologist Balaji Srinivasan joins a16z's Erik Torenberg and Martin Casado to discuss the limitations and societal impact of AI, framing the conversation around the concept of "Polytheistic AGI"—multiple, culturally-specific AIs—versus a singular, god-like intelligence. They explore the practical system-level constraints on AI, its surprising evolution, the critical role of cryptography in grounding AI in reality, and the future of work and security in an AI-driven world.