AI Agent Development · Kaiserslautern

AI Agent Development training in Kaiserslautern

Build AI agents professionally: architectures, tool use, agent SDKs, LangGraph, memory, evals, guardrails and deployment.

All 30 AI Agent Development courses are also available in Kaiserslautern – in a centrally located training room or at your premises on request.

AI agents go beyond conventional chatbots: they break tasks down, call tools and APIs, evaluate the results and keep iterating until a goal is met. In this two-day course you learn to build such systems so that they work reliably, transparently and safely in day-to-day business. You compare architectural patterns ranging from simple workflows through the agent loop to multi-agent systems, and you implement them hands-on with the Claude Agent SDK, the OpenAI Agents SDK and LangGraph.

Kaiserslautern is a renowned centre for computer science and AI research with a university and research institutes. Our training room gives teams from the Palatinate, Saarland and the Rhine-Neckar region easy access to hands-on AI training.

Suggested dates – Kaiserslautern

All dates are suggestions – your preferred date is always possible.

  • Wed, 25 November 2026 – Thu, 26 November 2026 Kaiserslautern Request
  • Mon, 7 December 2026 – Tue, 8 December 2026 Kaiserslautern Request
  • Wed, 20 January 2027 – Thu, 21 January 2027 Kaiserslautern Request
  • Mon, 1 February 2027 – Tue, 2 February 2027 Kaiserslautern Request
  • Tue, 16 February 2027 – Wed, 17 February 2027 Kaiserslautern Request
  • Mon, 22 February 2027 – Tue, 23 February 2027 Kaiserslautern Request

Core content of every AI Agent Development course

Module 1 Agent architectures and design patterns
  • Workflows versus agents: prompt chaining, routing, parallelisation, orchestrator-worker
  • The agent loop: plan, act, observe, reflect
  • Multi-agent systems, subagents and handoffs between agents
  • Criteria for choosing model, framework and level of autonomy
Module 2 Tool use and context engineering
  • Function calling and structured outputs with JSON Schema
  • Designing good tools: granularity, naming, error messages, idempotency
  • Connecting and reusing tools via MCP servers
  • Managing the context window: summarisation, compaction, retrieval and prompt caching
Module 3 Frameworks in practice
  • Claude Agent SDK: agent loop, tools, subagents, permissions and hooks
  • OpenAI Agents SDK: agents, handoffs, guardrails and tracing
  • LangGraph: stateful graphs, checkpointing and human-in-the-loop
  • Side-by-side comparison on the same task and criteria for choosing a framework
Module 4 Memory, evals and observability
  • Short-term and long-term memory, storage strategies and forgetting
  • Evaluation datasets, LLM-as-a-judge and task-based success metrics
  • Tracing tool calls, token usage and latency
  • Regression testing when prompts, models or tools change
Module 5 Guardrails, security and deployment
  • Protecting against prompt injection, data exfiltration and over-privileged tools
  • Input and output checks, approval steps and sandboxing
  • Deploying as a service, asynchronous execution, retries and cost limits
  • Governance, audit logging and requirements under GDPR and the EU AI Act

AI Agent Development courses in Kaiserslautern

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Request without obligation

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Total €949 plus VAT