Back to Basics: Cutting Through the AI-Generated Code Noise
Thursday, May 29
16:15 - 17:00
AI tools promise instant code generation but often deliver superficial solutions that fail in practice. Through building a book location mapper, I’ll show why understanding programming fundamentals matters more than ever in our AI-assisted development workflow.
In an era where AI promises to revolutionize coding, we face a paradox: while tools like Claude and GPT can generate impressive-looking code instantly, developers are increasingly getting tangled in a web of superficial solutions that often fail in practice. Through my experience building a simple book location mapper, I’ll demonstrate why understanding fundamental programming concepts is more crucial than ever in our AI-assisted future.
Intended Audience:
- Intermediate Python developers
- Python educators and mentors
- Team leads evaluating AI in Python workflows
- Anyone who’s ever debug-googled “ModuleNotFoundError” at 2 AM
Archana Vaidheeswaran
A Program Manager at Apart Research building a safer future through AI. I serve on the Board of Directors at Women in Machine Learning and drive global AI safety initiatives through research, hackathons, and community building. I have been awarded Fellow by Python Software Foundation for my contributions to the Python community
My expertise spans AI/ML, developer relations, and product development – skills I use to bridge gaps between technology and diverse communities.