Agentic Academy

Agent Fundamentals

Mon, 01 Jan 0001 00:00:00 +0000

The foundation of agentic AI lies in understanding how agents work at their core. This pillar covers the essential building blocks that every enterprise agent builder needs to master.

What you’ll find here

Agent architectures. Deep dives into ReAct, Plan-and-Execute, and Multi-Agent patterns. When to use each approach and how they perform in enterprise environments.

LLM foundations for agents. How large language models power agentic behavior, from prompt engineering to fine-tuning for specific enterprise use cases.

Agent Design & Frameworks

Mon, 01 Jan 0001 00:00:00 +0000

Building agents that work reliably in enterprise environments requires intentional design and proven frameworks. This pillar focuses on the methodologies that separate successful agent implementations from expensive experiments.

What you’ll find here

The AI Agent Canvas Framework. A structured approach to designing agents that align with business objectives and technical constraints.

Tasks-Skills-Tools framework. How to decompose agent capabilities into manageable, testable, and reusable components.

Design patterns for enterprise agents. Battle-tested patterns for common enterprise scenarios, from customer service to process automation.

Protocols & Standards

Mon, 01 Jan 0001 00:00:00 +0000

Agents don’t operate in isolation—they need to communicate with systems, APIs, and other agents. This pillar covers the protocols and standards that make reliable agent communication possible at enterprise scale.

What you’ll find here

Model Context Protocol (MCP) deep dives. Comprehensive analysis of MCP’s capabilities, limitations, and enterprise implementation patterns.

AsyncAPI for event-driven agents. How AsyncAPI enables agents to participate in event-driven architectures and real-time communication patterns.

OpenAPI and tool definitions. Best practices for exposing enterprise APIs to agents through OpenAPI specifications and tool definition patterns.

Governance & Operations

Mon, 01 Jan 0001 00:00:00 +0000

Enterprise AI agents need governance, not just guardrails. This pillar addresses the operational challenges of deploying agents at scale while maintaining control, visibility, and compliance.

What you’ll find here

Agent governance frameworks. Structured approaches to managing agent behavior, capabilities, and access across enterprise environments.

Risk assessment and mitigation. Practical strategies for identifying, evaluating, and mitigating risks unique to agentic systems.

Observability and monitoring. How to instrument agents for visibility, debugging, and performance optimization in production environments.

Enterprise Integration

Mon, 01 Jan 0001 00:00:00 +0000

AI agents don’t operate in greenfield environments—they must integrate with existing enterprise systems, data sources, and business processes. This pillar focuses on making those integrations successful and sustainable.

What you’ll find here

API management for agent tools. How to expose enterprise APIs to agents while maintaining security, governance, and performance requirements.

Integration platform strategies. Leveraging existing integration platforms and middleware to create robust agent-to-system connections.

Data connectivity patterns. Best practices for connecting agents to enterprise data sources, from databases to data lakes to real-time streams.

Research

Mon, 01 Jan 0001 00:00:00 +0000

Research

Exploring the frontiers of agentic AI through academic research, experimental approaches, and scientific advances.

What You’ll Find Here

Academic Papers & Analysis - Deep dives into recent research papers
Experimental Approaches - Novel techniques and emerging paradigms
Theoretical Foundations - Mathematical and computational theory
Research Trends - State-of-the-art developments in the field
Scientific Methods - Rigorous evaluation and benchmarking

Who This Is For

Researchers, academics, and practitioners interested in the theoretical foundations and cutting-edge developments in agentic AI systems.

The EU AI Act for AI Agent Builders

Tue, 04 Aug 2026 00:00:00 +0000

High-risk deadlines moved to 2027, but transparency obligations applied on 2 August 2026 — and they hit conversational agents directly. What binds you now.

MCP 2026-07-28: The Stateless Rewrite Explained

Thu, 30 Jul 2026 00:00:00 +0000

The newest MCP specification removes sessions, the initialize handshake, and SSE resumability. What breaks, what improves, and what enterprises should do now.

Who Owns the Agent? Team Topologies for AI

Mon, 06 Jul 2026 00:00:00 +0000

Agents fail organisationally before they fail technically. Who owns an agent in production, who is accountable for its decisions, and how to structure both.

RAG, Tools, or Long Context? A Decision Framework

Mon, 22 Jun 2026 00:00:00 +0000

Three ways to get enterprise knowledge into an agent, each with different failure modes. A decision framework based on freshness, authority, and scale.

Cost Attribution for AI Agent Fleets

Tue, 09 Jun 2026 00:00:00 +0000

A single API bill for fifty agents is not a cost model. How to attribute spend per agent, task, and tenant — and build budgets that fail safely.

AI Agents and Legacy Systems: The Other 80%

Thu, 28 May 2026 00:00:00 +0000

MCP assumes a modern API on the other end. Most enterprise value sits behind SOAP, batch jobs, and green screens. How to make agents work with what you have.

Indirect Prompt Injection via Tool Results

Mon, 18 May 2026 00:00:00 +0000

The dangerous prompt injection is not typed by your user — it arrives in a tool response. Why the data path is the real attack surface, and how to contain it.

The AI Agent Canvas: Design Agents on One Page

Thu, 07 May 2026 00:00:00 +0000

A structured design tool for translating business requirements into agent architecture — before you write code. Nine blocks that force the decisions teams skip.

Evaluating AI Agents: Evals That Predict Production

Tue, 28 Apr 2026 00:00:00 +0000

Benchmarks tell you a model is capable. Evals tell you your agent works. How to build golden datasets, LLM judges, and regression suites that catch failures.

Claude Opus 4.7: What's New for Enterprise AI

Thu, 16 Apr 2026 00:00:00 +0000

Opus 4.7 brings a 44-point vision jump, 3× coding improvement on production workloads, a new effort level, and a tokenizer change that will affect your costs.

AI Card: One Standard for Every AI Service

Wed, 15 Apr 2026 00:00:00 +0000

AI Card is a Linux Foundation draft for unified AI artifact metadata with built-in trust. A2A and MCP steering committees are expected to vote on adoption.

AuthZEN: Fine-Grained Authorization for Agents

Wed, 15 Apr 2026 00:00:00 +0000

AuthZEN standardizes the PEP/PDP interface for fine-grained authorization. Here’s how it closes the gap that OAuth scopes alone cannot fill in agentic systems.

The Context Window Problem Is the Client's Fault

Wed, 15 Apr 2026 00:00:00 +0000

Blaming MCP for context window pollution targets the wrong layer. Smart host applications can solve this — but only if the spec gives them enough metadata to work with.

Define Once, Deploy Everywhere: Agent Definition Languages Compared

Mon, 30 Mar 2026 00:00:00 +0000

Multiple specifications aim to become the declarative standard for defining AI agents. We evaluate Oracle Agent Spec, Eclipse LMOS ADL, and NextMoca ADL against what a portable agent definition actually requires.

Error Handling and Recovery in Agentic Systems

Sat, 14 Mar 2026 00:00:00 +0000

Agent failures are not like software bugs. Partial completions, semantic errors, cascade contamination, and cost runaway require fundamentally different recovery strategies than traditional exception handling.

From Primitives to Patterns: How Building Blocks Become Systems

Sat, 14 Mar 2026 00:00:00 +0000

Knowing the 17 agentic primitives is necessary but not sufficient. The real skill is understanding how they compose into architectural patterns that hold up under production load.

From Prototype to Production: What Actually Changes

Sat, 14 Mar 2026 00:00:00 +0000

The gap between a working agent demo and a production deployment is not about code quality. It is about the security boundaries, identity architecture, observability, and operational patterns you have not built yet.

Governance Patterns: Constraining Agents Without Killing Their Value

Sat, 14 Mar 2026 00:00:00 +0000

Agent governance is not about restriction — it is about creating the conditions under which agents can be trusted with progressively more autonomy. Policy, identity, lifecycle, and observability as architectural concerns.

Multi-Agent Coordination: When and How to Split the Work

Sat, 14 Mar 2026 00:00:00 +0000

Multi-agent systems solve problems that single agents cannot — but they introduce coordination costs that most teams underestimate. Discovery, negotiation, partial failure, and conflict resolution are the real design challenges.

Orchestration Patterns: Choosing How Agents Coordinate

Sat, 14 Mar 2026 00:00:00 +0000

Single, sequential, parallel, or hierarchical — the orchestration pattern you choose determines your system’s cost, debuggability, and failure characteristics. Here’s how to decide.

Agentic Governance: A Practical Guide to Governing AI Agent Systems

Mon, 09 Mar 2026 00:00:00 +0000

How do you govern AI agents in production? From API governance and security to observability and lifecycle management, a comprehensive guide to enterprise agentic governance.

How Do AI Agents Work? Architecture, Components, and Patterns

Mon, 09 Mar 2026 00:00:00 +0000

AI agents combine large language models with tools, instructions, and memory to perceive, reason, and act autonomously. Learn how they work, what makes them different from chatbots, and how enterprises deploy them.

Product Engineers Were Ready for This

Thu, 26 Feb 2026 00:00:00 +0000

Organizations that already shifted from software to product engineering will find the AI coding revolution unremarkable. That transition was the real work.

What AGENTS.md Actually Does to Your Coding Agent

Thu, 26 Feb 2026 00:00:00 +0000

The first rigorous benchmark of repository context files finds LLM-generated files hurt performance and raise costs, while developer-written files offer only modest gains.

AI Agent Security in 2026: 88% of Enterprises Report Incidents

Wed, 25 Feb 2026 00:00:00 +0000

Gravitee’s 2026 survey of 919 enterprises reveals a dangerous gap: 88% report AI agent security incidents, yet only 47% of deployed agents are actively monitored.

Agentic Solution Patterns: From Chatbots to Multi-Agent Systems

Mon, 23 Feb 2026 00:00:00 +0000

Four enterprise agentic patterns — from chatbots to multi-agent systems. The real unlock is combining deterministic and agentic processing.

AAuth: A New Authentication Standard Built for the Age of AI Agents

Wed, 18 Feb 2026 00:00:00 +0000

Dick Hardt, the creator of OAuth, has proposed AAuth—a protocol designed from scratch for agent-to-resource authentication. Here’s what it changes and why it matters.

Agent Identity and Authentication: Why OAuth Alone Isn't Enough

Tue, 17 Feb 2026 00:00:00 +0000

AI agents can’t click consent screens. How to build identity systems that handle delegation, credential scoping, and trust chains for autonomous software.

Agent Lifecycle Management: From Development to Decommission

Tue, 17 Feb 2026 00:00:00 +0000

Building an agent is the easy part. Managing it through development, testing, deployment, monitoring, updating, and eventual retirement is where enterprise maturity is measured.

MCP Registry: How Agents Discover and Connect to Tools

Tue, 17 Feb 2026 00:00:00 +0000

MCP standardizes agent-to-tool connections. The MCP Registry standardizes discovery. What it provides, how namespace verification works, and what to build around it.

Security Boundaries for Agentic Systems

Tue, 17 Feb 2026 00:00:00 +0000

Agents cross trust boundaries that traditional software never touches. How to design security perimeters that contain failures and limit blast radius.

A2A Deep Dive: What the Agent-to-Agent Protocol Actually Does

Mon, 16 Feb 2026 00:00:00 +0000

Google’s A2A protocol enables collaboration between opaque AI agents. What it provides, how it compares to MCP, and where you’ll need to build beyond the spec.

API Gateway Patterns for Agentic Workloads

Mon, 16 Feb 2026 00:00:00 +0000

Traditional API gateways weren’t built for agents that chain tool calls and consume tokens unpredictably. How gateway patterns are evolving.

Benchmarking Agent Reliability

Mon, 16 Feb 2026 00:00:00 +0000

SWE-bench, GAIA, AgentBench—agent benchmarks are proliferating. Here’s what they actually measure, what they miss, and what enterprise teams should track instead.

Observability for AI Agents: Beyond Traditional APM

Mon, 16 Feb 2026 00:00:00 +0000

Traditional APM breaks down when agents make autonomous decisions across multi-step tool chains. Here’s what observability looks like when your software has agency.

The Protocol Landscape for Agentic Systems

Mon, 16 Feb 2026 00:00:00 +0000

MCP, A2A, OpenAPI, AsyncAPI—the protocol landscape for agentic systems is taking shape. Here’s what each provides, where they overlap, and how they fit together.

AI Economics: Cost, Latency, and Model Selection

Fri, 13 Feb 2026 00:00:00 +0000

The pragmatic reality of running AI in production—model tiers, cost-latency tradeoffs, caching strategies, rate limits, and how operational constraints shape every architecture decision.

From Chat to Capabilities: Tool Use and Function Calling

Fri, 13 Feb 2026 00:00:00 +0000

How LLMs go from generating text to taking actions—the bridge from chatbot to agent building block through tool use, function calling, and structured outputs.

From LLM to Agent: The Architectural Leap

Fri, 13 Feb 2026 00:00:00 +0000

What makes an agent more than a prompted LLM—the combination of planning, tools, memory, and autonomy that transforms a language model into a system that acts in the world.

How LLMs Process Information: Tokens and Context Windows

Fri, 13 Feb 2026 00:00:00 +0000

The operational realities of LLMs that shape every agent architecture decision—from token economics to context window constraints to in-context learning.

Memory, State, and Learning: What LLMs Remember (and Don't)

Fri, 13 Feb 2026 00:00:00 +0000

Why LLMs are stateless by default, what that means for agent design, and the approaches to giving agents persistent memory—from conversation history to RAG to external memory systems.

Planning, Reasoning, and the Limits of AI Judgment

Fri, 13 Feb 2026 00:00:00 +0000

How LLMs think—chain-of-thought, multi-step reasoning, and decomposition. And equally important: where reasoning breaks down and why this drives the need for autonomy boundaries.

What Is a Large Language Model?

Fri, 13 Feb 2026 00:00:00 +0000

Mental models for enterprise practitioners. What LLMs actually do, how to think about them, their capabilities and inherent limitations—and why this matters for agent design.

What Are AI Agents? Definition, Architecture, and How They Work

Sat, 07 Feb 2026 00:00:00 +0000

AI agents are entities that perceive, reason, and act to accomplish goals. Learn how agents combine LLMs, tools, and instructions to work autonomously in enterprise systems.

What Are Dynamic Connections?

Sat, 07 Feb 2026 00:00:00 +0000

Dynamic connections use registries and catalogs to discover endpoints at runtime—enabling agentic systems that evolve without reconfiguration.

What Are Point-to-Point Connections?

Sat, 07 Feb 2026 00:00:00 +0000

Point-to-point connections are direct, explicit links between two specific components in an agentic system—the simplest and most predictable way to wire things together.

What Are Queued Connections?

Sat, 07 Feb 2026 00:00:00 +0000

Queued connections use message infrastructure to decouple senders and receivers in time—enabling resilient, scalable agentic systems that handle load and failure gracefully.

What Are Users?

Sat, 07 Feb 2026 00:00:00 +0000

Users are the human participants who interact with, oversee, and ultimately benefit from agentic systems—the actors whose needs give agents their purpose.

What Is Agentic Orchestration?

Sat, 07 Feb 2026 00:00:00 +0000

Agentic orchestration is dynamic, LLM-driven coordination where a central agent reasons about how to decompose, delegate, and adapt complex work in real time.

What Is Choreography?

Sat, 07 Feb 2026 00:00:00 +0000

Choreography is decentralized coordination where autonomous agents react to events and coordinate without a central controller—enabling resilient, scalable agentic systems.

What Is Conversation?

Sat, 07 Feb 2026 00:00:00 +0000

Conversation is the interaction pattern where actors engage in sustained, contextual exchange over multiple turns—the collaborative dialogue that enables complex problem-solving.

What Is Delegation?

Sat, 07 Feb 2026 00:00:00 +0000

Delegation is the interaction pattern where one actor instructs another to perform specific work—the command that sets agents in motion.

What Is Notification?

Sat, 07 Feb 2026 00:00:00 +0000

Notification is the interaction pattern where an actor announces that something happened—the event-driven signal that enables reactive agentic architectures.

What Is Retrieval?

Sat, 07 Feb 2026 00:00:00 +0000

Retrieval is the interaction pattern where one actor requests information from another without expecting any state change—the question that keeps agents informed.

What Is Workflow Orchestration?

Sat, 07 Feb 2026 00:00:00 +0000

Workflow orchestration is deterministic, centralized coordination that executes predefined sequences of steps—the reliable backbone of enterprise agentic processes.

AI Agent Autonomy Borders: When to Escalate to Humans

Fri, 06 Feb 2026 00:00:00 +0000

Every AI agent operates within boundaries. Success depends on whether the agent recognizes its limits and escalates correctly. A practical guide to designing autonomy borders.

What Are Action Tools?

Fri, 06 Feb 2026 00:00:00 +0000

Action tools enable AI agents to modify state in the outside world—creating records, sending messages, triggering processes, and executing transactions.

What Are Agent Instructions?

Fri, 06 Feb 2026 00:00:00 +0000

Agent instructions define an individual AI agent’s identity, expertise, and behavioral guidelines—the constitution that shapes every interaction.

What Are Knowledge Tools?

Fri, 06 Feb 2026 00:00:00 +0000

Knowledge tools are read-only interfaces that give AI agents access to information beyond their training data—the eyes and ears of agentic systems.

What Are System Instructions?

Fri, 06 Feb 2026 00:00:00 +0000

System instructions are platform-level rules, constraints, and objectives that govern all AI agents within an environment—the governance layer of agentic systems.

What Are Workflow Instructions?

Fri, 06 Feb 2026 00:00:00 +0000

Workflow instructions provide step-by-step procedures that guide AI agents through multi-step tasks—the runbooks and playbooks of the agentic world.

The Applied Autonomy Framework: Bridging Agent Design and Operations

Thu, 05 Feb 2026 00:00:00 +0000

The gap between what you design and what your organisation can operate is where most AI agent initiatives fail. The Applied Autonomy Framework makes this gap measurable and actionable.

The Four Dimensions of Agent Autonomy

Wed, 04 Feb 2026 00:00:00 +0000

Why ‘how autonomous is your agent?’ is the wrong question—and what to ask instead. A framework for understanding tool, task, plan, and collaboration autonomy.

Agentic Primitives: 6 Building Blocks Every AI Agent System Needs

Mon, 02 Feb 2026 00:00:00 +0000

The six fundamental building blocks of AI agent systems: actors, tools, instructions, coordination, interactions, and governance. A practical framework for enterprise agent design.

Agents Are Not Magic: Why Autonomous AI Hype Is Dangerous

Thu, 29 Jan 2026 00:00:00 +0000

The obsession with ‘autonomous agents’ sets enterprises up for failure. Agents need structure, constraints, and human judgment — not magical thinking.

Building Your First AI Agent: A Practical Introduction

Wed, 28 Jan 2026 00:00:00 +0000

Start your journey into agentic AI with a hands-on introduction to building a simple but functional AI agent. Learn the core concepts, architecture patterns, and practical implementation steps.

What is AsyncAPI? The Standard Your Event-Driven Architecture Needs

Tue, 13 Jan 2026 00:00:00 +0000

AsyncAPI brings the same contract-first discipline to event-driven systems that OpenAPI brought to REST. For enterprise teams building agentic AI architectures, it’s becoming essential infrastructure.

Tasks, Skills, and Tools: The Essential AI Agent Framework

Mon, 12 Jan 2026 00:00:00 +0000

Learn the three core components every production AI agent needs: tasks define what to do, skills define how, and tools connect to external systems.

API Governance for AI Agents: How to Avoid Agentic Technical Debt

Thu, 08 Jan 2026 00:00:00 +0000

When every team can deploy an agent, API governance becomes the difference between compounding value and compounding chaos. What enterprises get wrong and how to fix it.

What Is MCP? A Practitioner's Guide to Model Context Protocol

Mon, 05 Jan 2026 00:00:00 +0000

Model Context Protocol (MCP) is the standard for agent-to-tool communication. What it actually provides, how the spec evolved, and where you’ll need to build your own solutions.

AI Agent Orchestration Patterns: Single, Sequential, Parallel, and Hierarchical

Fri, 02 Jan 2026 00:00:00 +0000

Choosing the right orchestration pattern is one of the most consequential decisions in AI agent architecture. Compare single, sequential, parallel, and hierarchical approaches with real tradeoffs.

How to Design APIs for AI Agent Consumption

Sun, 28 Dec 2025 00:00:00 +0000

Your APIs were designed for human developers, but agents read them differently. A practical guide to making APIs truly agent-consumable with OpenAPI and MCP.

About

Mon, 01 Jan 0001 00:00:00 +0000

Agentic Academy

Enterprise AI doesn’t fail because of models. It fails because of missing contracts, unclear governance, and APIs that were never designed to be consumed by agents.

Agentic Academy exists to close that gap.

This is where enterprise architects, AI practitioners, and system builders come to learn the craft of building agents that work—in production environments with real constraints. No hype cycles. No breathless predictions. Just rigorous analysis, battle-tested patterns, and the hard-won lessons that separate production-ready AI agents from expensive experiments.

Apply

Mon, 01 Jan 0001 00:00:00 +0000

Apply Your Knowledge

Coming soon: Hands-on projects, case studies, and practical guides for implementing AI agents in production environments.

Stay tuned for:

Real-world implementation case studies
Hands-on project templates
Best practices from production deployments
Common pitfalls and how to avoid them
Enterprise integration patterns

Authors

Mon, 01 Jan 0001 00:00:00 +0000

Frameworks

Mon, 01 Jan 0001 00:00:00 +0000

Agentic Academy’s original frameworks provide a shared vocabulary for designing, building, and governing AI agents in enterprise environments. Each framework is grounded in production experience and designed to be immediately applicable.

These frameworks are free to use, cite, and build upon. If they help clarify your thinking or improve your team’s conversations, we’ve done our job.

Imprint

Mon, 01 Jan 0001 00:00:00 +0000

Provider

Markus Müller

Rönner Weg 30 24146 Kiel

Represented by: Markus Müller

Contact us

E-mail: info@agentic-academy.ai

Sales tax ID

DE312182982

Information on audiovisual media services

Country of domicile: Germany

Regulatory and supervisory authority:

Disclaimer

We are responsible for the content of our website in accordance with the provisions of general law. All content is created with due care and to the best of our knowledge. Insofar as we refer to third-party websites on our Internet pages by means of hyperlinks, we cannot assume any liability for the continued topicality, correctness and completeness of the linked content, as this content is outside our area of responsibility and we have no influence on its future design. Should you consider any content to be in breach of applicable law or inappropriate, please let us know.

Learning Paths

Mon, 01 Jan 0001 00:00:00 +0000

A structured path from LLM fundamentals to production-ready agent systems. Each module builds on the previous one — start at Module 0 and work your way through.

Resources

Mon, 01 Jan 0001 00:00:00 +0000

Services

Mon, 01 Jan 0001 00:00:00 +0000

Services

Coming soon: Professional services to help you build, deploy, and scale AI agents in your organization.

Stay tuned for:

Strategy consulting for agentic AI initiatives
Architecture design and review
Training and enablement programs
Implementation support
Production readiness assessments

Start Here

Mon, 01 Jan 0001 00:00:00 +0000

Whether you’re writing agent code, designing agentic architectures, or shaping AI strategy — we’ve curated a reading path for you. Pick your track below and follow it in order.