The EU AI Act for AI Agent Builders
High-risk deadlines moved to 2027, but transparency obligations applied on 2 August 2026 — and they hit conversational …
Read articleDesign patterns. Protocols. Governance. Everything you need to take AI agents from prototype to production.
Enterprise AI doesn't fail because of models.
It fails because of missing contracts, unclear governance, systems that were never designed for agents, and orchestration patterns borrowed from tutorials instead of production environments.
Agentic Academy is the resource that was missing — practical, opinionated, and built for people who ship.
Whether you're building agents, designing agentic architectures, or leading AI strategy — we've curated a reading path for you.
Engineers building agents
You're hands-on with LLMs and agents. Start with the primitives framework, learn orchestration and error handling patterns, then tackle the gap between prototype and production.
See reading list →Designing agent systems
You're designing how agents fit into enterprise systems. Start with primitives and protocols, then master the patterns that make multi-agent systems work at scale.
See reading list →Governance & strategy
You're responsible for AI strategy, risk, and governance. Start with understanding what agents actually are, then explore governance frameworks and the path from prototype to production.
See reading list →The six fundamental building blocks of AI agent systems: actors, tools, instructions, coordination, interactions, and governance. A practical framework for enterprise agent design.
Read article →High-risk deadlines moved to 2027, but transparency obligations applied on 2 August 2026 — and they hit conversational …
Read articleThe newest MCP specification removes sessions, the initialize handshake, and SSE resumability. What breaks, what …
Read articleAgents fail organisationally before they fail technically. Who owns an agent in production, who is accountable for its …
Read articleCore concepts and architectural patterns for building AI agents. From ReAct to multi-agent systems, memory management to tool integration.
View articles →Design patterns, frameworks, and methodologies for building production-ready AI agents. From the AI Agent Canvas to testing strategies.
View articles →The protocols and standards enabling agent-to-system and agent-to-agent communication. MCP, AsyncAPI, OpenAPI, and the emerging standards landscape.
View articles →Frameworks for governing AI agents in enterprise environments. Risk management, observability, cost control, and avoiding the false economy of speed.
View articles →Connecting AI agents to enterprise systems, data, and workflows. API management, security, authentication, and hybrid human-agent operations.
View articles →Cutting-edge research, academic papers, and scientific advances in agentic AI systems
View articles →Handpicked content from voices we trust in the enterprise AI space.

Hosts Matt McLarty and Mike Amundsen take a look across the digital landscape and identify key focus areas that are currently impacting the world of APIs, Integration, and Business.
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Anthropic's practical guide to building LLM agents. Explores composable patterns from simple workflows to autonomous agents — emphasizing that the most successful implementations avoid complex frameworks in favor of simple, well-understood building blocks.
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A practical guide to designing high-quality tools for AI agents. Covers how to build prototypes, run evaluations, and iteratively improve tools through agent collaboration — with key principles on token efficiency, tool selection, and effective descriptions.
Read blog →Markus Müller (Global Field CTO for API Management, Boomi) and Matt McLarty (CTO, Boomi — O'Reilly author, API Experience podcast host) bring decades of enterprise architecture experience to every article.
This isn't analyst commentary from the sidelines. It's field notes from practitioners building, advising, and shipping in the enterprise AI space.
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