Once I began engaged on the brand new version of Head First C# again in 2023, AI instruments like ChatGPT and Copilot had been already altering how builders write and study code. It was clear that I wanted to cowl them. However that raised an attention-grabbing problem: How do you train new and intermediate builders to make use of AI successfully?
Virtually the entire materials that I discovered was aimed toward senior builders—individuals who can acknowledge patterns in code, spot the refined errors usually present in AI-generated code, and refine and refactor AI output. However the viewers for the e book—a developer studying C# as their first, second, or third language—doesn’t but have these expertise. It grew to become more and more clear that they would wish a brand new technique.
Designing an efficient AI studying path that labored with the Head First methodology—which engages readers by way of energetic studying and interactive puzzles, workouts, and different parts—took months of intense analysis and experimentation. The consequence was Sens-AI, a brand new collection of hands-on parts that I designed to show builders the way to study with AI, not simply generate code. The title is a play on “sensei,” reflecting the function of AI as a trainer or teacher quite than only a software.
The important thing realization was that there’s an enormous distinction between utilizing AI as a code era software and utilizing it as a studying software. That distinction is a important a part of the training path, and it took time to totally perceive. Sens-AI guides learners by way of a collection of incremental studying parts that get them working with AI instantly, making a satisfying expertise from the beginning whereas they progressively study the prompting expertise they’ll lean on as their growth expertise develop.
The Problem of Constructing an AI Studying Path That Works
I developed Sens-AI for the fifth version of Head First C#. After greater than 20 years of writing and educating for O’Reilly, I’ve realized rather a lot about how new and intermediate builders study—and simply as importantly, what journeys them up. In some methods AI-assisted coding is simply one other ability to study, but it surely comes with its personal challenges that make it uniquely tough for brand spanking new and intermediate learners to select up. My objective was to discover a technique to combine AI into the training path with out letting it short-circuit the training course of.
Step 1: Present Learners Why They Can’t Simply Belief AI
One of many largest challenges for brand spanking new and intermediate builders attempting to combine AI into their studying is that an overreliance on AI-generated code can really stop them from studying. Coding is a ability, and like all expertise it takes apply, which is why Head First C# has dozens of hands-on coding workouts designed to show particular ideas and methods. A learner who makes use of AI to do the workouts will battle to construct these expertise.
The important thing to utilizing AI safely is belief however confirm—AI-generated explanations and code might look right, however they usually comprise refined errors. Studying to identify these errors is important for utilizing AI successfully, and creating that ability is a vital stepping stone on the trail to changing into a senior developer. Step one in Sens-AI was to make this lesson clear instantly. I designed an early Sens-AI train to display how AI could be confidently mistaken.
Right here’s the way it works:
- Early within the e book, learners full a pencil-and-paper train the place they analyze a easy loop and decide what number of occasions it executes.
- Most readers get the proper reply, however after they feed the identical query into an AI chatbot, the AI virtually by no means will get it proper.
- The AI usually explains the logic of the loop nicely—however its remaining reply is virtually at all times mistaken, as a result of LLM-based AIs don’t execute code.
- This reinforces an essential lesson: AI could be mistaken—and typically, you might be higher at fixing issues than AI. By seeing AI make a mistake on an issue they already solved appropriately, learners instantly perceive that they’ll’t simply assume AI is true.
Step 2: Present Learners That AI Nonetheless Requires Effort
The following problem was educating learners to see AI as a software, not a crutch. AI can remedy virtually the entire workouts within the e book, however a reader who lets AI try this received’t really study the talents they got here to the e book to study.
This led to an essential realization: Writing a coding train for an individual is strictly the identical as writing a immediate for an AI.
In truth, I spotted that I might take a look at my workouts by pasting them verbatim into an AI. If the AI was capable of generate an accurate resolution, that meant my train contained all the data a human learner wanted to resolve it too.
This was one other key Sens-AI train:
- Learners full a full-page coding train by following step-by-step directions.
- After fixing it themselves, they paste your entire train into an AI chatbot to see the way it solves the identical drawback.
- The AI virtually at all times generates the proper reply, and it usually generates precisely the identical resolution they wrote.
This reinforces one other important lesson: Telling an AI what to do is simply as tough as telling an individual what to do. Many new builders assume that immediate engineering is simply writing a fast instruction—however Sens-AI demonstrates {that a} good AI immediate is as detailed and structured as a coding train. This offers learners an instantaneous hands-on expertise with AI whereas educating them that writing efficient prompts requires actual effort.
By first having the learner see that AIs could make errors, after which having them generate code for an issue they solved and evaluate it to their very own resolution—and even use the AI’s code supply of concepts for refactoring—they acquire a deeper understanding of the way to interact with AI critically. These two opening Sens-AI parts laid the groundwork for a profitable AI studying path.
The Sens-AI Strategy—Making AI a Studying Device
The ultimate problem in creating the Sens-AI method was discovering a manner to assist learners develop a behavior of partaking with AI in a constructive manner. Fixing that drawback required me to develop a collection of sensible workouts, every of which supplies the learner a selected software that they’ll use instantly but in addition reinforces a constructive lesson about the way to use AI successfully.
Considered one of AI’s strongest options for builders is its capacity to elucidate code. I constructed the following Sens-AI factor round this by having learners ask AI so as to add feedback to code they only wrote. Since they already perceive their very own code, they’ll consider the AI’s feedback—checking whether or not the AI understood their logic, recognizing the place it went mistaken, and figuring out gaps in its explanations. This gives hands-on coaching in prompting AI whereas reinforcing a key lesson: AI doesn’t at all times get it proper, and reviewing its output critically is crucial.
The following step within the Sens-AI studying path focuses on utilizing AI as a analysis software, serving to learners discover C# subjects successfully by way of immediate engineering methods. Learners experiment with completely different AI personas and response kinds—informal versus exact explanations, bullet factors versus lengthy solutions—to see what works finest for them. They’re additionally inspired to ask follow-up questions, request reworded explanations, and ask for concrete examples that they’ll use to refine their understanding. To place this into apply, learners analysis a brand new C# matter that wasn’t lined earlier within the e book. This reinforces the concept AI is a helpful analysis software, however provided that you information it successfully.
Sens-AI focuses on understanding code first, producing code second. That’s why the training path solely returns to AI-generated code after reinforcing good AI habits. Even then, I needed to rigorously design workouts to make sure AI was an help to studying, not a substitute for it. After experimenting with completely different approaches, I discovered that producing unit assessments was an efficient subsequent step.
Unit assessments work nicely as a result of their logic is straightforward and straightforward to confirm, making them a protected technique to apply AI-assisted coding. Extra importantly, writing an excellent immediate for a unit take a look at forces the learner to explain the code they’re testing—together with its conduct, arguments, and return sort. This naturally builds robust prompting expertise and constructive AI habits, encouraging builders to consider carefully about their design earlier than asking AI to generate something.
Studying with AI, Not Simply Utilizing It
AI is a strong software for builders, however utilizing it successfully requires extra than simply figuring out the way to generate code. The most important mistake new builders could make with AI is utilizing it as a crutch for producing code, as a result of that retains them from studying the coding expertise they should critically consider the entire code that AI generates. By giving learners a step-by-step method that reinforces protected use of AI and nice AI habits, and reinforcing it with examples and apply, Sens-AI offers new and intermediate learners an efficient AI studying path that works for them.
AI-assisted coding isn’t about shortcuts. It’s about studying the way to assume critically, and about utilizing AI as a constructive software to assist us construct and study. Builders who interact critically with AI, refine their prompts, query AI-generated output, and develop efficient AI studying habits would be the ones who profit essentially the most. By serving to builders embrace AI as part of their skillset from the beginning, Sens-AI ensures that they don’t simply use AI to generate code—they learn to assume, problem-solve, and enhance as builders within the course of.
On April 24, O’Reilly Media will likely be internet hosting Coding with AI: The Finish of Software program Improvement as We Know It—a reside digital tech convention spotlighting how AI is already supercharging builders, boosting productiveness, and offering actual worth to their organizations. In the event you’re within the trenches constructing tomorrow’s growth practices right now and thinking about talking on the occasion, we’d love to listen to from you by March 5. You will discover extra info and our name for shows right here.
