AI Agents

Session AI Agents

Actors for Agents: Patterns for Production AI

Tuesday Jun 2 / 01:20PM EDT

We started with the obvious stack: a prompt-chain framework, some glue code, a queue for the slow parts. It demoed beautifully.

Speaker image - Manju Rajashekhar

Manju Rajashekhar

Founder & CEO @Mad Labs, Entrepreneur, Engineering Executive, Founder, Investor

Session AI/ML

Context Engineering at LinkedIn: How We Built an Organizational Context Layer for AI Agents with MCP

Monday Jun 1 / 11:30AM EDT

AI coding agents are powerful out of the box, but they don't know your company. They can't navigate your services, understand your frameworks, query your data systems, or follow your organizational processes.

Speaker image - Ajay Prakash

Ajay Prakash

Senior Staff Software Engineer @LinkedIn

Session AI Agents

Beyond the Prototype: Scaling Framework Agnostic AI Agent Infrastructure with Ray

Monday Jun 1 / 02:30PM EDT

Building an AI agent is easier than ever. However, moving from a local notebook to a production-grade "Agent Engine" that serves large scale web services poses complex problems.

Speaker image - Deepak Mohanakumar Chandramouli

Deepak Mohanakumar Chandramouli

Senior Machine Learning Engineer @Apple, 20+ Years in Distributed Systems and Scalable Data/Compute/ML Infrastructure

Speaker image - Bhumik Vinodkumar Thakkar

Bhumik Vinodkumar Thakkar

Senior Software Engineer @Apple, Expert in Artificial Intelligence and Large-Scale Distributed Systems

Session AI

Beyond Prompting: Context Engineering for Production-Grade AI

Monday Jun 1 / 10:20AM EDT

If you're building production-grade AI apps, you may know an uncomfortable truth: reliable model outputs require far more than clever prompting.

Speaker image - Ricardo Ferreira

Ricardo Ferreira

Principal Developer Advocate @Redis, Expert in Distributed Systems, Databases, and Software Development, Previously @AWS, @Elastic, and @Confluent

Session Responsible AI

Opening the Black Box: Critical Explainability for AI Agent Tool Selection with Kiji Inspector

Monday Jun 1 / 02:30PM EDT

AI agents that autonomously select and invoke tools are becoming ubiquitous—yet their decision-making remains a black box. When an agent chooses to query a database instead of searching the web, what internal representations drive that choice?

Speaker image - Hannes Hapke

Hannes Hapke

Head of 575 Lab @Dataiku, Google Developer Expert for ML/AI, Member of the Google Developer Board, Previously Principal ML Engineer @Digits