This post isn’t meant to wag fingers or shame anyone. We just want learners to be smart about the way they use new technology \u2013 especially one as impactful on the learning process as LLMs. Indeed, sometimes getting the best learning experience may mean not using AI, but sometimes it just means using it slightly differently.<\/p>\n\n\n\n
This is part three in our series How to Learn to Code in an AI World<\/em>. Don\u2019t miss the first, Is it Still Worth Learning to Code?<\/em><\/a>, and second, Learning to Think in an AI World: 5 Lessons for Novice Programmers<\/em><\/a>.<\/em><\/p>\n\n\n\n Let\u2019s get right to it: Should you use AI when learning to program?<\/p>\n\n\n\n Our answer is best expressed as a graph:<\/p>\n\n\n\n In short, the more of a beginner you are, the less you should use AI to generate code for you. <\/p>\n\n\n\n There are a lot of reasons for this, namely:<\/p>\n\n\n\n This doesn\u2019t mean you can\u2019t use AI to help you follow your curiosity and increase<\/em> your motivation to learn things yourself. You can ask it to generate metaphors for challenging abstract concepts, ask questions if no human teacher is available, clarify terms that confuse you, and even get advice on a personal project that is slightly out of your depth.<\/p>\n\n\n\n Still, we would generally advise caution when interacting with LLMs that aren\u2019t specifically tailored for education. Research shows people are very bad at realizing when AI is replacing their thinking rather than augmenting it<\/a>.<\/p>\n\n\n\n Choosing between no AI, an AI made for learning, or going all in is difficult. In the next part, we’ll go a bit deeper into the pros and cons of each of these options.<\/p>\n\n\n\n Inconvenient, but better for knowledge retention and accuracy<\/em><\/p>\n\n\n\n Non-AI materials require us to commit to the active process of digging through books, documentation, and forums to find answers. It can take much longer compared to prompting an LLM, but the benefit is that it fully engages us in our own learning (as long as it doesn\u2019t ruin our motivation by being too boring). Our brains interpret the additional time as a sign of importance, which in turn enhances our memory of what we learned. Moreover, we might stumble upon unexpected gems in a way that\u2019s difficult with AI-generated answers.<\/p>\n\n\n\n Let\u2019s also not overlook the human element here: a skilled teacher can offer a personal perspective that significantly outweighs the convenience of AI. Through good teachers we learn to love a subject and believe in ourselves, profoundly impacting the experience of learning and our long-term motivation.<\/p>\n\n\n\n Extremely convenient but hard to get right in practice<\/em><\/p>\n\n\n\n Usually, when we interact with AI, we\u2019re looking for a quick and easy answer. Even when it\u2019s engineered to prompt us to do some thinking on our own, we tend to unconsciously skip over those questions and shortcut to the solution<\/a>. It requires a lot of willpower to slow down and truly digest the information AI gives us, not to mention reflect and relate it to previous things we\u2019ve learned, and finally, understand how to apply it in practice.<\/p>\n\n\n\n If you\u2019re good at making yourself slow down and think, then tutor away! But, if you find yourself spending most of your time prompting, skimming, and rushing toward output \u2013 skipping the high-level thinking<\/em> parts of coding \u2013 then we\u2019d recommend you take a break from AI and find ways to allow for more thoughtful reflection into your practice.<\/p>\n\n\n\n AI assistants<\/strong><\/p>\n\n\n\n Great for doing things, less great for learning things; to use them wisely requires a strong foundation<\/em><\/p>\n\n\n\n There are as many opinions on the best way to use an AI assistant as there are software developers. Some use it every time they code and some prefer a whiteboard and a rubber duck. Over time you\u2019ll learn your preference and style. The important thing is for you to figure out how to write quality code quickly and in a way that feels good.<\/p>\n\n\n\n If you do use it, we definitely recommend spending some focused time learning best practices \u2013 like any technology, it takes some intention to learn to use it well. See our course catalog<\/a> for free courses like Coding with AI assistant<\/em><\/a> or Prompting to debug and fix AI-generated code<\/em><\/a>.<\/p>\n\n\n\n In summary, while AI tools are incredibly convenient, it’s crucial for beginners to exercise caution. Overreliance on AI for code generation can hinder foundational understanding, knowledge retention, and intrinsic motivation.<\/p>\n\n\n\n The best approach involves balancing AI assistance with traditional learning methods, fostering <\/strong>computational thinking<\/a>, and staying smart about when you use it. Ultimately, the effectiveness of AI in your coding journey depends on your learning style, current skill level, and how thoughtfully you integrate these powerful tools.<\/p>\n\n\n ![\"\"](\"https:\/\/blog.jetbrains.com\/wp-content\/uploads\/2025\/07\/DSGN-22785_Banners_for_AI_world_blog_post_series_part_3_21.jpg\")
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Non-AI materials and tutors<\/strong><\/h3>\n\n\n\n
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