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AI Agent Development and Usage Training

Training Format: Live Online / In-Person Duration: 2 Days Download PDF

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Description

Agent Design, Frameworks, and No-Code Automation – 2-Day Program

The AI Agent Development and Usage Training is designed for corporate teams who want to learn how AI agents work, build code-based agent systems, and set up automation with no-code/low-code tools. The program covers agent architecture, n8n workflows, development frameworks, tool integrations, and security, combining theory with hands-on practice.

The goal of the training is for participants to understand the concept of an AI agent at both a technical and practical level so they can design systems that fit business needs. Participants examine how large language models (LLMs) work together with planning, memory, and tool-use components, and compare no-code automation with code-based development approaches.

By the end of the two-day program, participants are expected to gain basic practical skills in designing agent architectures, building automations with n8n, and developing agents with frameworks such as LangChain, CrewAI, Agno, and similar tools. Corporate use cases are also evaluated in terms of security, authorization, monitoring, and cost control.

Training Outcomes

  • Understanding the AI agent concept, its relationship to LLMs, and its core architectural components at a technical level.
  • Applying agent development approaches with no-code/low-code tools and code-based frameworks.
  • Building workflows in n8n that include LLM and API connections.
  • Evaluating planning, tool selection, memory, and feedback mechanisms in an agent scenario.
  • Designing enterprise agent architectures and multi-agent use cases.
  • Recognizing agent security risks and evaluating appropriate control methods.
  • Strategically identifying agent use cases and automation opportunities in business processes.

Who Is the AI Agent Training For?

The technical scope of the training suits software developers, automation specialists, solution architects, and corporate technology teams who want to build AI-powered applications. Technical business analysts and digital transformation teams who are evaluating the use of agents in business processes can also benefit from the program’s architecture and use case sections.

Hands-On Agent Development and Corporate Use

The n8n exercise in the program covers analyzing a user request, interpreting it with an LLM, making an API call, generating a report, and delivering the result through Slack or email. The final project works on an agent scenario that covers tool integration, memory, multi-agent coordination, and security control.

Teams that want to focus on connecting agent systems to external tools and data sources can also review the Model Context Protocol (MCP) Training. For complementary programs for the different teams in your organization, see the corporate AI training category.

Outline

Day 1 – AI Agent Fundamentals and No-Code Automations

What Is an AI Agent?

  • The AI agent concept and core operating principles.
  • Differences between agents and large language models (LLMs).
  • Reactive and autonomous agent approaches.
  • The concept of a tool-using agent.
  • Memory and planning mechanisms.
  • The agent lifecycle.

Agent Architecture

  • Receiving and evaluating input.
  • Planning task steps (planning).
  • Selecting the right tool for the need (tool selection).
  • Carrying out the operations (execution).
  • Updating memory (memory update).
  • Evaluating results through a feedback loop.

No-Code Agent Systems

  • How n8n works and its workflow structure.
  • Trigger → action → tool chain.
  • Connecting to an LLM via webhooks.
  • Connecting to external systems through API integrations.
  • Comparing the Zapier and n8n approaches.

Hands-On – n8n Agent Workflow

  • Analyzing the request received from the user.
  • Interpreting the request with an LLM.
  • Making an API call for the relevant operation.
  • Generating a report from the information obtained.
  • Sending the result via Slack or email.
Day 2 – Agent Frameworks and Code-Based Development

Introduction to Agent Frameworks

  • LangChain: The agent executor approach, tool binding, memory, and chains.
  • CrewAI: A role-based multi-agent approach and a planner/worker structure.
  • Agno: A lightweight agent development approach.
  • Upsonic: Enterprise agent architecture and lifecycle management.

Agent Development Techniques

  • The plan-first agent approach.
  • Multi-agent coordination.
  • Tool abstraction.
  • Memory persistence.
  • Retrieval-augmented generation (RAG) integration.
  • Model Context Protocol (MCP) integration.

Agent Security

  • Prompt injection risks.
  • Tool misuse and permission scoping.
  • Output validation.
  • Token usage and cost control.

Enterprise Agent Architecture

  • A central orchestrator component.
  • Domain-based agent structures.
  • Monitoring and logging.
  • Audit and governance model.

Final Project

  • Designing a simple agent.
  • Integrating tools into the agent system.
  • Connecting the memory component.
  • Setting up a multi-agent scenario.
  • Applying a security check.

Frequently Asked Questions About AI Agent Training

What does the AI Agent Development and Usage Training cover?

The training covers AI agent fundamentals, agent architecture, no-code automations with n8n, development frameworks, and code-based applications. Planning, memory, tool use, RAG and MCP integrations, multi-agent coordination, and enterprise security are covered together.

How many days does the AI agent training last?

The program lasts 2 days. Day one focuses on AI agent fundamentals, architectural components, and no-code automations with n8n. Day two covers agent frameworks, code-based development, security, enterprise architecture, and the final project.

Does the training cover building agents without writing code?

Yes. On the first day of the program, no-code/low-code agent workflows are covered with n8n. The work focuses on the trigger, action, and tool chain, connecting to an LLM via webhooks, and API integration. The second day also covers code-based development approaches.

Which agent frameworks are covered?

The training covers LangChain, CrewAI, Agno, and Upsonic. Different approaches are examined, such as tool binding, memory, role-based multi-agent structures, lightweight agent development, and enterprise lifecycle management.

What hands-on exercises are included?

The n8n exercise covers analyzing a user request, interpreting it with an LLM, making an API call, generating a report, and sending the result via Slack or email. In the final project, a simple agent is designed, and the work focuses on tool integration, memory, a multi-agent scenario, and security control.

Are RAG and MCP integrations part of the training?

Yes. RAG and MCP integrations are included in the agent development techniques section. These topics are evaluated together with planning, tool abstraction, memory persistence, and multi-agent coordination.

How is enterprise agent security addressed?

The program examines prompt injection risks, tool misuse, permission scoping, and output validation. Token and cost control, as well as monitoring, logging, audit, and governance, are also covered from a corporate usage perspective.

How can we get a price quote for AI agent training?

To get pricing and scheduling information for corporate training, you can fill out the contact form on the page. In your request, you can share your team’s current technical level and training goals to communicate your needs.