The Maker’s Guide to AI Coding: Build More With AI

You have an idea for a useful tool, but there is a problem: building it means learning a new programming language, framework, or software stack. What if you could explain what you want to build and let AI handle much of the coding?

That is the idea behind The Maker’s Guide to AI Coding, a new Elektor book by engineer and educator Peter Dalmaris. Rather than teaching programming language by language, the book focuses on how makers can work with AI coding assistants to turn their ideas into working software, while still understanding and controlling what is being built.

AI Can Write the Code, But Can You Trust It?

Getting code from an AI assistant is easy. Knowing whether that code is actually correct is a different matter.

Dalmaris approaches AI coding as a collaboration rather than a way to hand over the entire development process. The book introduces five levels of delegation, ranging from asking AI a focused question to allowing an autonomous coding agent to work across a project. Readers learn when it makes sense to delegate, when they need to verify the result, and when they should keep control of the work themselves. 

This is where makers have an interesting advantage. Electronics provides plenty of real-world reference points for checking AI-generated software. A filter has a known response, a sensor reading has a plausible range, and a datasheet tells you how a component should behave. The goal is not simply to get code that runs, but to understand it well enough to know that it is doing the right thing. 

The first project makes that idea concrete. Using only a browser and a chat-based AI assistant, readers create an interactive RC low-pass filter analyzer. Enter the resistance and capacitance, and the resulting tool calculates the cutoff frequency and plots the magnitude response. 
 

From an Arduino Plotter to Your Own Datasheet Assistant

From there, the projects become progressively more ambitious. The second build is particularly familiar territory for anyone who works with microcontrollers: a live serial data plotter. An Arduino sends temperature, humidity, and light readings over USB serial, while a Python server and browser interface turn the incoming values into live charts. 

The project is also used to introduce a complete AI-assisted development workflow. Instead of jumping straight into generated code, readers work through brainstorming, specification, implementation, testing, iteration, documentation, deployment, and maintenance.
 

The third project takes AI beyond the role of coding assistant and puts a language model inside the finished application. Readers build a datasheet Q&A tool using retrieval-augmented generation (RAG). Load a component datasheet, ask questions such as its maximum supply voltage or how to configure an interface, and the application finds the relevant information and identifies where it came from so the answer can be checked. 

From an Idea to a Complete Application

For the final project, the scale changes again. Readers develop a multi-user resource booking system for a shared workshop, makerspace, or electronics lab. Members can sign in, browse resources and reserve equipment or facilities, while the application handles areas such as authentication, databases, external services, background tasks, conflict detection, and multiple organizations. 

The progression is deliberate. Each project hands more responsibility to the AI while asking the reader to make increasingly important decisions about specifications, testing, architecture, and verification.

You don't need an advanced programming background to get started. The book introduces the process from the beginning, and the projects use Python and JavaScript as practical tools rather than assuming fluency in either language. No specialized hardware or expensive software licenses are required either. 

The Maker’s Guide to AI Coding is ultimately less about learning how to prompt an AI and more about learning how to build with one. If you have an idea for a tool but programming has been the barrier between the idea and a working project, this book offers a practical place to start.

The Maker’s Guide to AI Coding is available from the Elektor Store.