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AI Engineering Workshop

This IT project is part of our digitalization and optimization of our customers’ IT landscape. Through targeted measures, we promote technological progress, optimize cross-system processes and create a sustainable basis for future developments. Our IT reference projects serve as a basis for orientation. They support the reusability of tried and tested concepts as part of project implementation.

Project duration: 2 days

Brief description

The client primarily has its in-house software development carried out by external service providers. The workshop equips architects, developers, business analysts, and process managers to deploy AI coding agents themselves, evaluate their results, and define their own architecture and governance requirements in such a way that these are also applied in third-party development. The PTA clarifies the requirements, creates the concept, coordinates the agenda, researches and prepares the content, and conducts the three-day on-site workshop – featuring presentations, guided hands-on exercises, teamwork in four teams, reflection sessions, slide decks, and handouts. Technically, the focus is on a coding agent and its components: project rules, agent skills, hooks, subagents, and MCP, as well as context engineering and spec-driven development. Participants will practice using a Java web application with Maven, Servlet, Tomcat, and PostgreSQL.

Supplement

Each team works on a laptop with a local setup consisting of an IDE, Maven, Tomcat, and PostgreSQL, as well as a preconfigured repository with a directory structure and a Hello-World-servlet. The coding agent Claude Code runs using the client's credentials. Topics covered include plan and authorization modes, project rules as an instruction file, agent skills, hooks as automatic checkpoints, subagents for specific subtasks, and MCP servers for connecting to existing systems.

Subject description

The benefit lies in the fact that domain rules, nomenclature, and architectural specifications are available to the agent as context, rather than existing solely in people's minds. The client retains the ability to evaluate the work, even when external parties are developing with agents. Agentic Engineering refers to development using AI agents within a structured process. Context Engineering controls which information is made available to an agent. Spec-Driven Development establishes a verifiable specification prior to implementation. MCP integrates existing systems with the agent.

IT project data

Project period08.09.2026 - 10.09.2026

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