Ai agents

Using Agents in Production: Past Present and Future // Euro Beinat

Using Agents in Production: Past Present and Future // Euro Beinat

A deep dive into how Prosus is deploying over 30,000 AI agents to create an 'AI Agentic Workforce'. The talk covers the transition from simple assistants to trusted senior colleagues, the internal tooling developed, and the crucial organizational strategies used to overcome adoption barriers and foster a bottom-up culture of innovation.

From Chat Fatigue to Instant Action // Donné Stevenson

From Chat Fatigue to Instant Action // Donné Stevenson

A discussion on the evolution of AI agent interaction, moving beyond simple text-based chat to create intuitive, GUI-driven experiences. The talk covers the practical challenges and solutions in building an impactful agent for busy professionals, focusing on quick actions, efficient data streaming, and enhanced interactivity.

Context Engineering 2.0: MCP, Agentic RAG & Memory // Simba Khadder

Context Engineering 2.0: MCP, Agentic RAG & Memory // Simba Khadder

Simba Khadder of Redis introduces Context Engineering 2.0, a new paradigm for AI agents that unifies structured data, unstructured data (RAG), and memory into a single, schema-driven surface. He critiques current methods like Text-to-SQL and direct API wrapping, proposing a unified context engine to provide reliable, observable, and performant data access for agents.

Enterprise-ready MCP // Jiquan Ngiam

Enterprise-ready MCP // Jiquan Ngiam

Jiquan Ngiam, CEO of MintMCP, discusses the paradigm shift from static programs to dynamic AI agents, outlining the significant security risks involved—supply chain vulnerabilities, third-party data poisoning, and inadvertent agent behaviors—and presents a three-pronged strategy for enterprise readiness: comprehensive monitoring, preventative guardrails, and secure, role-based deployment of Model Context Protocols (MCPs).

A Playground for AI Engineers

A Playground for AI Engineers

Paulo Vasconcellos from Hotmart details their journey of building "Agent as a Product", explaining how they blend classic ML models with LLMs for efficiency, evolve their MLOps platform for the generative AI era, and create real business value through AI-powered tutors and sales agents.

Exploits of public-facing apps are surging. Why?

Exploits of public-facing apps are surging. Why?

A deep dive into the 2026 IBM X-Force Threat Intelligence Index, exploring the shift to exploiting public-facing applications, the rise of AI agent-related threats, critical AI infrastructure flaws, and the need for a more human-centric approach to threat intelligence.