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From Consumers to Builders: Turning 200 of our Team into Agent Creators in Two Weeks
Ben Maraney explains how Forter enabled R&D teams to build internal AI agents fast by simplifying tools, using custom MCP servers, and removing organizational roadblocks to maximize engineering ROI.
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APIs for Agents: Rethinking API Programs in the MCP Era
Jim Gough and Andreea Niculcea explain how Morgan Stanley leverages Architecture as Code with CALM and MCP to scale secure, compliant API platforms for AI agents and future protocols like A2A.
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Context Engineering at LinkedIn: How We Built an Organizational Context Layer for AI Agents with MCP
Ajay Prakash shares how LinkedIn built Contextual Agent Playbooks and Tools to give AI coding agents internal stack context, automating 600+ workflows and raising productivity 20%.
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Architecting the Data Layer for AI Agents: from Transactional Systems to MCP and Semantic Models
Fabiane Nardon explains how to architect enterprise data platforms for AI agents, balancing precision, security, and token costs using MCP, data mesh, and semantic web technologies.
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The Right 300 Tokens Beat 100k Noisy Ones: The Architecture of Context Engineering
Baruch Sadogursky and Patrick Debois explain context engineering antipatterns in coding agents, demonstrating how skills, right-tool retrieval, and external memory optimize developer workflows.