#243 - The 70% Problem: When AI Coding Falls Short

What happens when software engineers rely too heavily on AI-assisted coding tools? Brian and Zubin (an ex-Google engineer) dive deep into what they call "The 70% Problem" – the phenomenon where AI coding tools excel at initial scaffolding but falter when tackling the crucial final 30% of engineering work.Drawing from Addy Osmani's insightful article, these experienced developers share their firsthand experiences with tools like Cursor, ChatGPT, and GitHub Copilot. They explore how AI-assisted coding creates a dangerous illusion of competence while potentially masking fundamental knowledge gaps. As Zubin aptly puts it, giving powerful AI coding tools to inexperienced developers is like "giving a Formula One car to someone who's only driven on city streets."Visit parsity.io to learn how Brian and Zubin are training the next generation of engineers to excel in this new paradigm.Addy Osmani's ArticleVS Code Cheat SheetSend us a textShameless Plugs 🧑‍💻 Free 5 day email course to go from HTML to AI 🤔 Got a question you want answered on the pod? Drop it here Apply for 1 of 12 spots at Parsity - Learn to build complex software with AI integrations. AI Bootcamp - for software developers who want to be the expert on their team when it comes to AI