Agentic coding: workflow automation through AI agents
Software development is undergoing a radical transformation. While traditional code completion tools merely offer reactive suggestions, agentic coding tools are ushering in a new era: they operate autonomously, plan complex tasks, and coordinate entire workflows. In a market environment that demands ever-faster development cycles, the ability to deploy AI agents as “digital co-developers” is becoming a critical factor in productivity. Those who ignore these autonomous assistants will fall behind in modern, highly efficient development processes.
In this hands-on workshop, you’ll learn how to use Large Language Models (LLMs) and specialized agent systems specifically for code generation, error analysis, and system integration. We’ll show you how agents can independently fix build errors, resolve merge conflicts (version conflicts), and perform automated code reviews. The focus here is on making the leap from mere text generation to a fully integrated, intelligent assistant that actively works in the background of your projects.
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- Autonomous workflow support: you’ll understand the difference between simple code completion and agentic coding, where AI independently plans tasks and solves complex problems such as incompatible library versions.
- Targeted code generation: you’ll learn how to use LLMs to efficiently create functional, application-specific code for scripts, data analysis, or web prototypes.
- Hands-on implementation: in the interactive session, we’ll set up the necessary software together so you can immediately test what you’ve learned on your own use cases or business examples.
- Improving code quality: you’ll learn how AI agents perform automated reviews to identify bugs and performance issues early on and enhance the security of your software.
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The workshop is designed for technical professionals in software development and industrial development environments.
- Software developers and systems developers
- AI engineers and software engineers in the AI field
- DevOps and platform engineers
- IT architects and technical project managers
- Developers in industrial sectors such as energy, manufacturing, automotive, and defense
- Teams looking to implement modern AI-driven development processes
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- Format: workshop / training
- Duration: flexible
- Delivery: online or in-person
- Practical component: high, with examples and specific application scenarios
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The format can be customized to suit your organization’s specific needs—for example, by:
- Incorporating your specific use cases
- Adapting to your industry or project type
- Delving deeper into specific methods or tools
