Imagine a virtual tutor that can offer personalized feedback, guiding students toward coding mastery. That's the promise of feedback ladders, a novel approach to teaching programming using AI. Researchers are exploring how Large Language Models (LLMs) like GPT-4 can generate these ladders, offering multiple levels of hints for a single coding problem. A student struggling with a basic error might receive a simple 'yes/no' verdict (Level 0) or a failing test case (Level 1). As they progress, the AI can offer high-level explanations of the error (Level 2), pinpoint the problematic code section (Level 3), or even suggest specific edits (Level 4). This personalized approach aims to give each student the right amount of support at the right time. A recent study tested this approach, asking students, instructors, and researchers to evaluate the AI-generated feedback. The results were promising, especially for lower-level feedback. The AI excelled at providing relevant 'yes/no' verdicts and test cases. However, the higher rungs of the ladder proved more challenging. The AI sometimes struggled to give clear, helpful explanations or suggest appropriate edits, especially for code that was *almost* correct. These higher-level hints often strayed from the intended format, sometimes even offering a completely new solution instead of guiding the student to find their own fix. This suggests that while AI can effectively identify simple errors, it still needs refinement to provide the nuanced guidance required for more complex problems. The study also revealed that the AI tutors were better at helping students with low-scoring submissions than those with high-scoring ones. This makes sense – it's easier to spot major flaws than subtle errors. Even human experts can struggle to find those last few bugs in nearly perfect code. While there's still work to be done, AI-powered feedback ladders hold exciting potential for personalized coding education. Future research could involve real-classroom testing to measure actual learning gains and developing AI models that can automatically choose the right feedback level for each student. Imagine a future where every student has a personalized AI tutor, ready to guide them up the feedback ladder to coding success.