Saad Ullah
⬤ Anthropic just dropped new research on January 29, 2026, looking at how AI assistance actually affects coding skills over time. Here's the interesting part: AI tools are pretty much the same for everyone, but the results people get vary wildly. Why? It all comes down to how you engage with them. The research focuses on three key factors—curiosity, willingness to experiment, and how you handle failure when working alongside AI systems.
⬤ The bottom line is that AI assistance is neutral when it comes to skill development. What really matters is whether you're trying to understand the solution or just copying and pasting. Developers who question the AI's answers, try different approaches, and actually think about their mistakes end up with much stronger skills. On the flip side, if you're just grabbing quick answers without digging deeper, you might get stuff done faster today but you won't be learning much for tomorrow.
⬤ One surprising finding: getting stuck and failing are still crucial for learning, even with AI help. AI doesn't eliminate the hard parts—it just changes how you run into them. The research argues that staying curious about how things actually work and being okay with uncertainty helps turn AI from a crutch into a real learning tool. It's about building long-term capability, not just getting quick fixes.
⬤ This matters because AI coding assistants are everywhere now—in schools, bootcamps, and professional work. Anthropic's research suggests that how sophisticated the AI is doesn't matter nearly as much as how you use it. As these tools become standard in software development, the gap between developers might not be about who has access to the best AI, but who knows how to learn with it. Your mindset and learning habits could become the biggest factors in your technical growth.
Saad Ullah
