Posts

Platform Engineering • Ajay Chankramath & Nic Cheneweth • GOTO 2026

Platform Engineering • Ajay Chankramath & Nic Cheneweth • GOTO 2026

Ajay Chankramath and Nic Cheneweth discuss the critical elements of effective platform engineering, emphasizing a product mindset, the foundational role of control planes and API-first design, the common pitfalls of implementing Backstage, and the emerging impact of AI and agents on the platform landscape.

A2A vs MCP: AI Agent Communication Explained

A2A vs MCP: AI Agent Communication Explained

Discover how A2A (Agent2Agent) and MCP (Model Context Protocol) solve critical challenges in AI agent ecosystems. A2A enables seamless communication and collaboration between diverse AI agents, while MCP standardizes an agent's access to external tools and data, fostering robust and interoperable AI workflows.

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).