Agentic Software Engineering Training – Structuring and Scaling Software Development with AI Agents
Upon request
1–2 days
Online, in Munich, or in-house
Upon request
German or English
Digital Certificate of Participation
From product concept to operation: Agentic AI for robust architecture, efficient development, and secure software processes. Software development is increasingly supported by AI agents. These agents analyze requirements, develop proposed solutions, generate code, run tests, and can independently handle tasks in development and operations processes. However, turning this into production-ready software requires more than just individual AI prompts: Clear contexts, transparent workflows, technical oversight, and robust governance are crucial.
Our Agentic Software Engineering Training teaches how companies and teams can deploy AI agents throughout the entire software lifecycle—from product development and architecture through implementation and testing to CI/CD and operations. You’ll learn how to structure agentic development processes effectively, build multi-agent workflows, and distinguish experimental “vibe coding” from professional software engineering.
Content and Schedule of the Agentic Software Engineering Training Course
This training program combines the fundamentals of agentic AI with practical methods for product development, software engineering, quality assurance, and secure production operations. All modules can be combined freely.
- Introduction to Foundation Models and Large Language Models (LLM)
- Key concepts such as tokens, context, memory, prompts, tools, and the Model Context Protocol
- Differences Between AI Assistants and AI Agents:
- Observe
- Decide
- Trade
- Change System States
- Overview of Agent Toolchains, Agent Harnesses, and Related Tools
- AI Support for Glossaries, Proto-Personas, User Journeys, Epics, and User Stories
- Structuring and maintaining consistent backlogs based on product and project documentation
- Agent-based prototypes for rapid validation of product ideas
Result
A solid understanding of agent-based software development, as well as structured product and requirements frameworks.
- Derive quality requirements and quality scenarios from requirements and stakeholder needs
- Supporting Architectural Designs, System Contexts, and Component Views with AI
- Identify contradictions, inconsistencies, and deviations from a common technical language
- Identify, Assess, and Document Technical Debt
- Maintaining Architectural and Project Documentation with AI Agents
- Critically Evaluate Agent-Generated Architectural Proposals
Result
Transparent architectural decisions and robust technical documentation.
- Context Engineering as the Foundation for Reliable Development Tasks
- Setting Up Memory, Rules, Commands, Skills, and Subagents
- Use Specification-Driven Development, Planning Mode, Task Breakdown, and reviewable implementation units
- Using AI for Code Generation, Code Completion, API Integration, and Library Usage
- Use agents for features, refactoring, debugging, legacy modernization, and Git workflows
- Creating Traceable Commits, Pull Requests, and Review Templates
- Parallelizing Development Tasks Using Separate Agents and Work Contexts
Result
Structured and production-oriented implementation using AI agents and multi-agent workflows.
- Develop and Improve Unit, Integration, and End-to-End Tests
- Retrofit Test Suites for Existing Applications
- Generate Synthetic Test Data and Identify Edge Cases
- Using UI interpretation and browser automation for realistic test scenarios
- Implementing Test-Driven Agentic Development and Iterative Quality Assurance
- Conduct agent-assisted code, merge request, and architecture reviews
- Verify code quality, security, requirements, and compliance
- Evaluate agent-generated changes and systematically address review findings
Result
Higher code quality, better test coverage, and transparent control mechanisms.
- Developing and Optimizing CI/CD Pipelines with AI Agents
- Automate builds, tests, reporting, containerization, and releases
- Create Release Notes, Changelogs, and Repeatable Pipeline Steps
- Use agents for logging, metrics, dashboards, alerts, and observability queries
- Support root-cause analyses, bug fix suggestions, and ticket management
- Fundamentals of Self-Healing Pipelines and Automated Troubleshooting
- Ensure guardrails, approvals, permissions, rollbacks, and human oversight
Result
AI-powered automation and safe operation with clear control and approval points.
What You Can Put into Practice Right Away After Completing the Agentic Software Engineering Training
After the training, you will be able to deploy AI agents in a targeted manner in software development and operations.
- Classifying Agentic AI Architectures and Appropriate Toolchains
- Structuring Requirements, Backlogs, and Product Ideas with AI
- Use AI agents for coding, refactoring, debugging, and legacy system modernization
- Developing Multi-Agent Workflows for Complex Development Tasks
- Supporting Tests, Code Reviews, and Quality Assurance with Agents
- Analyze Logs, Traces, and Error Messages More Efficiently
- Critically review agent-generated results and approve them with confidence
- Establishing Checkpoints, Authorizations, and Human Oversight in the Development Process
Who is the Agentic Software Engineering Training course designed for?
This training is intended for:
- Software Developers and Engineering Teams
- Software Architects and Technical Leads
- DevOps, Platform, and SRE Teams
- Product Owners and Technical Project Managers
- Manager of Software and Product Development
- Companies that want to integrate AI agents into their engineering processes
A basic understanding of technology and experience with software development processes are helpful.
Eligibility Requirements for the Agentic Software Engineering Training
Basic knowledge of software development, architecture, or DevOps is recommended. Experience with AI tools is helpful but not required.
Customized Agentic Software Engineering Training Courses
- Customized Training for Development and Engineering Teams
- Integration of custom programming languages, IDEs, repositories, and toolchains
- Working with real-world architecture, code, and deployment scenarios
- Development of Custom Agent Workflows and Engineering Standards
- Offered as a seminar, workshop, or in-house training session
About Us as a Training Provider
We are an experienced management consulting firm with over 20 years of expertise in digital transformation, software development, and new technologies, such as artificial intelligence. Our training programs combine modern agentic AI concepts with specific requirements from product development, engineering, and operations.
We help companies safely integrate AI agents into existing development processes, tap into new automation potential, and develop production-ready software solutions. In doing so, we consider the entire lifecycle—from the initial idea through architecture and code to testing, deployment, and operations.
01
02
03
04
05
06
Expertise in Agentic Software Engineering – Your Trainer
Jonas Kuhlmann helps companies implement modern AI technologies and agentic development processes. He explains complex topics such as context engineering, multi-agent workflows, vibe coding, and agentic coding in an accessible way, drawing direct parallels to real-world engineering tasks.
His focus is on integrating product development, software architecture, implementation, and secure operations. In doing so, he demonstrates how AI agents can make development teams more productive without compromising quality, traceability, or technical accountability.
Request a no-obligation
appointment now
- Using Agentic AI Specifically for Software Development and Engineering
- Customized Training for Developers, Architects, and Technical Teams
- Proven expertise in AI agents, development processes, and system architecture
- Ready-to-use methods for coding, testing, automation, and secure operation
TISAX and ISO certification apply only to the Munich location
Your Message
TISAX and ISO certification apply only to the Munich location
Discover more continuing education programs, seminars, and training courses
ChatGPT Training: Using AI Professionally in Your Daily Work
Less effort, more impact: By using ChatGPT strategically, you can turn daily routines into real value creation.
ChatGPT and Copilot Training: Save Time in Your Daily Life with AI and Effective Prompt Engineering
In this training session, learn how to use ChatGPT, Copilot, and targeted prompt engineering to efficiently integrate artificial intelligence into your daily work—for greater innovation, value creation, and productivity.
Product Owner Training: Your Guide to Successful Scrum Teams
In this training course, you’ll learn how to fulfill your role as a Product Owner strategically and effectively—for greater clarity, focus, and sustainable success in day-to-day agile project work.
Resilience Seminar for Executives
In this resilience seminar for leaders, learn how to use proven methods and effective routines to strengthen your own resilience and that of your team—for greater confidence, clarity, and stability in challenging leadership situations.
Release Manager Training
In this training, learn how to establish and optimize structured and agile release management processes to ensure faster and more reliable service delivery in your organization.
Requirements Engineering Training: The Key to Successful Projects
In this training course, you’ll learn how to create clearly defined requirements and, as a result, make your projects more efficient, more customer-focused, and less risky—for demonstrable success right from the start.
Resilience Training for Executives, Teams, and Employees: Targeted Strengthening of Resilience
Training: How to Attract, Lead, and Retain Generation Z
Find out here how to apply modern leadership approaches to successfully inspire, attract, and retain young Generation Z talent in your company.
Scrum Basics Training – Agile Fundamentals for Sustainable Business Success
In this course, you’ll learn the basics of agile work using Scrum. You’ll gain practical insights and learn how to effectively use modern project management methods and apply them directly.
FAQ – Frequently Asked Questions About Agentic Software Engineering Training
Traditional AI assistants typically support individual tasks on demand, such as code generation or code explanation. AI agents, on the other hand, can plan multi-step tasks, use tools, process information, and carry out follow-up actions. In this training, you’ll learn how to design such agent-based processes and use them in a controlled manner.
Yes, a basic technical understanding is recommended, as much of the content relates to code, architecture, testing, and CI/CD. However, you do not need to be a specialist in AI development. The training covers agent-based concepts and demonstrates how existing engineering skills can be enhanced through AI.
Among other things, agents can structure requirements, generate code, develop tests, analyze errors, create documentation, and prepare pull requests. They can also support architectural decisions, refactoring, legacy modernization, and pipeline tasks. The specific level of automation depends on the system, context, and defined checkpoints.
Vibe Coding is often used to describe the rapid development of prototypes using natural-language instructions. Agentic Software Engineering goes a step further and encompasses structured processes for architecture, implementation, testing, quality assurance, and operations. In this training, you’ll learn when a quick prototype is sufficient and when robust engineering standards are required.
Yes. You will learn how multiple specialized agents can handle tasks in parallel or by dividing the work among themselves. Examples include separate agents for planning, research, implementation, testing, or review. The course also covers responsibilities, handoffs, shared contexts, and control mechanisms.
Code generated by agents must be tested, reviewed, and evaluated from a technical perspective. The training covers, among other topics, unit, integration, and end-to-end testing, code reviews, security checks, and human approvals. The goal is a controlled process that balances speed with quality and technical accountability.
Yes. For in-house training, existing IDEs, repositories, CI/CD pipelines, and toolchains can be incorporated. Participants’ own architecture, code, or deployment examples can also be included in the exercises. Confidential information should only be used in approved environments.
Security and governance are central components of the training. Topics covered include permissions, guardrails, approvals, rollbacks, data protection, and human oversight. This enables teams to learn how to operate agent-based systems in a way that is not only efficient but also controllable and secure.