About
Pablo Restrepo is a Colombian software and ML engineer with over 11 years of experience building AI and software systems across Colombia, Germany, the UK, and the US. He is currently Machine Learning Lead at Loka, where he designs and deploys end-to-end GenAI solutions for global clients. He holds a Master's in Informatics from the Technical University of Munich and a BSc in Computer Science from Universidad EAFIT. He is also a published researcher in NLP and has spoken at conferences across Germany, Sweden, Norway, and the US.
Talk
Clean Code in the Era of LLMs: Do Good Practices Still Matter?
Instead, research from METR, CodeRabbit, and GitClear is converging on an uncomfortable truth: code duplication has quadrupled, copy-pasted code now exceeds moved code, bugs have risen 70%, and security issues have nearly tripled. AI didn't break our codebases. It amplified what was already broken. So what do we actually do about it? This talk makes the case that clean code, SOLID, DDD, TDD, and design patterns matter more than ever when LLMs write half the code. Your codebase is now a prompt: clean code leads to better AI suggestions, which make it easier to stay clean. We'll walk through which practices now matter more, which ones have quietly turned against you, and how to collaborate with an LLM without becoming a rubber stamp for its output. You'll leave with a concrete framework, Adversarial Collaboration: generate, critique, refactor, verify. Not vibe coding. Real engineering, just faster.
- Country
- Colombia
- Language
- Spanish / Español
- Level
- Intermediate / Intermedio
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