AI-Assisted Clean Code Workshop
Work hands-on with coding agents in a real codebase: uncover hidden risks, create behaviour-focused tests, refactor safely, establish repository guardrails, and coordinate multiple agents while preserving one coherent design.
AI coding tools can generate implementations, tests, and refactorings within minutes. The harder question is whether those changes are correct, understandable, appropriately structured, and safe to keep.
Generated code can compile, pass its tests, and still be wrong. It may rely on an unsupported API, silently change behaviour during a refactoring, copy a legacy workaround as if it were the preferred design, omit important failure or authorization paths, or produce an impressive test suite that protects implementation details instead of the behaviour that matters.
This hands-on workshop turns Clean Code judgement into a practical AI-assisted development workflow. Participants work with a provided application, inspect real generated diffs, improve tests, refactor code in small controlled steps, make deliberate domain and architecture decisions, and convert repeated review findings into reusable repository guardrails.
The focus is on the quality of an individual AI-assisted change. Participants begin with an unguided agent implementation and progressively make it safer, clearer, better tested, and more consistent with the intended direction of the codebase. Clean Code practices, code smells, test design, domain modelling, and architecture patterns are used as practical decision tools rather than as abstract catalogues.
The workshop is deliberately tool-agnostic. Participants may use Codex, Claude Code, Cursor, GitHub Copilot coding agents, or equivalent repository-level tools. The focus is not on collecting prompts or maximizing the number of agents. The focus is on making engineering judgement explicit, verifiable, and reusable so that AI assistance improves the codebase instead of accelerating technical debt.
Oliver Zihler is a dedicated Software Crafter specialising in Domain-Driven Design, Event Sourcing, collaborative modelling, and effective software development. His current focus lies in leveraging software architecture and business semantics to improve AI reasoning and AI-assisted development. Oliver actively organises Tech Excellence meetups and conferences, fostering community learning and innovation. At Codeartify, he serves as a technical trainer, software engineer, and architect, guiding teams to deliver robust software solutions.
Alina Liburkina is Software Craftress and CEO of Codeartify GmbH. She is a technical trainer, software engineer and architect, and (IT) event organizer passionate about DDD, Refactoring, Hexagonal and Clean Architecture. She is a co-organizer of an international conference and meetups TechExcellence. Moreover, she promotes and introduces XP techniques in the teams she works with. She loves to gather and share her knowledge with others through pair or mob programming, presentations or hands-on workshops.