Code Modernization Using Agentic AI
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Code Modernization Using Agentic AI
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Transform your legacy code into modern, maintainable, and efficient code, requirements, and tests using of Agentic AI.
Description
Legacy code is often a challenge: it requires heavy maintenance, slows down development, and can reduce team motivation. In this training, you’ll learn step by step how to modernize a legacy codebase using Agentic AI and a structured DevOps approach.
You will learn how to:
- transform legacy code into modern, maintainable solutions,
- automatically generate tests, requirements, and backlog items,
- improve code quality through validation and advanced prompt engineering.
During the training, you will gain hands-on experience with Agentic AI by tackling a concrete chal…
Veelgestelde vragen
Er zijn nog geen veelgestelde vragen over dit product. Als je een vraag hebt, neem dan contact op met onze klantenservice.
Meer weten over de onderwerpen die aan bod komen en de vereiste voorkennis? Neem vrijblijvend contact met ons op.
Transform your legacy code into modern, maintainable, and efficient code, requirements, and tests using of Agentic AI.
Description
Legacy code is often a challenge: it requires heavy maintenance, slows down development, and can reduce team motivation. In this training, you’ll learn step by step how to modernize a legacy codebase using Agentic AI and a structured DevOps approach.
You will learn how to:
- transform legacy code into modern, maintainable solutions,
- automatically generate tests, requirements, and backlog items,
- improve code quality through validation and advanced prompt engineering.
During the training, you will gain hands-on experience with Agentic AI by tackling a concrete challenge: migrating an existing Ruby codebase. You’ll explore different migration strategies, learn how to engage business stakeholders effectively, and apply context engineering to achieve consistent, high-quality results.
Note: This training focuses modernizing existing code bases. For starting with new projects see our AI Native Engineering Workflow training instead.
Learning Goals
- Understand when and how to use agentic AI in your code modernization loop [Understand]
- Explain the structured DevOps approach to code modernization including instructions files, requirements, and backlog items [Understand]
- Compare different migration strategies (entire project, feature-by-feature, file-by-file) and select appropriate approaches [Understand]
- Generate modern code, tests, requirements, and backlog items using Agentic AI [Create]
- Apply context engineering and advanced prompt engineering practices to improve output quality [Apply]
- Validate generated code and tests using multiple review techniques and tools [Evaluate]
- Evaluate the output of a code modernization loop and formulate improvements [Evaluate]
Subjects
- Apply a structured DevOps approach to code modernization
- Create requirements and backlog items using Agentic AI
- Choose and implement appropriate migration strategies (entire project, feature-by-feature, or file-by-file)
- Migrate features from legacy code to modern code with tests
- Validate generated code and tests using multiple review techniques
- Apply modern prompt engineering practices (context engineering) to improve output quality
- Integrate business stakeholders into the modernization process
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Deel je ervaring
Heb je ervaring met deze cursus? Deel je ervaring en help anderen kiezen. Als dank voor de moeite doneert Springest € 1,- aan Stichting Edukans.Er zijn nog geen veelgestelde vragen over dit product. Als je een vraag hebt, neem dan contact op met onze klantenservice.