Posts

Building an Orchestration Layer for Agentic Commerce at Loblaws

Building an Orchestration Layer for Agentic Commerce at Loblaws

Mefta Sadat from Loblaw Digital discusses Alfred, an agentic orchestration layer designed to run AI shopping agents reliably in production. He covers the architecture built with LangGraph and GCP, the role of the Model Context Protocol (MCP) in simplifying API interaction, and practical MLOps strategies for observability, cost management, and ensuring reliability.

Time to become a hacker // Matt Sharp

Time to become a hacker // Matt Sharp

In this talk, Matt Sharp explains that while 2025 is the year of AI agents, it's also the year of cybercrime. The rush to create frictionless, user-friendly agents has led to a neglect of fundamental security principles, creating a perfect environment for hackers who are now using these same powerful AI tools to innovate and scale their attacks.

The Rush to Adopt AI: How to Get it Right & Business Risks • Nick Selby & Sarah Wells • GOTO 2026

The Rush to Adopt AI: How to Get it Right & Business Risks • Nick Selby & Sarah Wells • GOTO 2026

In this interview, Sarah Wells and Nick Selby discuss the significant business risks introduced by the current rush to adopt AI. They cover how AI vendors blur security terminology, how the insatiable need for data creates an enormous blast radius for breaches, and provide a framework for responsible AI adoption through threat modeling, cross-disciplinary governance, and a return to IT fundamentals.

How AI covered a human’s paternity leave // Quinten Rosseel

How AI covered a human’s paternity leave // Quinten Rosseel

A practitioner's guide to deploying a text-to-SQL agent in a real-world business environment. The talk covers the critical lessons learned in moving from concept to production, focusing on the importance of the communication channel (Slack), the necessity of a semantic layer over benchmark scores, and a pragmatic approach to system architecture, testing, and evaluation.

When Agents Learn to Feel: Multi-Modal Affective Computing in Production // Chenyu Zhang

When Agents Learn to Feel: Multi-Modal Affective Computing in Production // Chenyu Zhang

This talk explores the frontier of affective computing in AI agents, proposing a new architecture where emotion is a first-class component. It covers the technical challenges of deploying multi-modal, emotion-aware systems in production—from memory and learning to multi-agent orchestration—and delves into the critical ethical considerations of privacy, manipulation, and scientific validity.

Make Something Agents Want

Make Something Agents Want

The hosts explore the dawn of an agent-driven economy, spurred by tools like OpenClaw and social platforms like MoltBook. They discuss the critical shift for developers to build tools that AI agents, not just humans, will choose, focusing on the new go-to-market strategies, the rise of swarm intelligence, and the essential infrastructure required for this new paradigm.