AI Coding for makers & solopreneurs

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AI coding assistants have collapsed the distance between an idea and a working tool. The thing that used to stop you, the months of learning a framework, the unfamiliar tooling, the deployment you never got around to, is no longer the barrier it was. If you can describe what you want clearly, and judge whether what comes back is right, you can build it. This course teaches that workflow, end to end, for people who build things.

It is built for makers. Every concept, project, and example connects to electronics, embedded systems, and the kind of work you already do. You start by building an interactive RC filter analyser in your browser, then a command-line tool that reads real file formats, a GUI serial plotter that charts live data from an Arduino, a datasheet question-and-answer tool with a language model at its core, and finally a complete multi-user Resource Booking System as the capstone. Five working projects, each one a little more capable than the last.

You do not wait until the end to build something. You ship your first tool in Module 1. The early lectures are short and conceptual because they earn their place by setting up the next thing you build, not because theory is the point. Along the way you learn the part most tutorials skip: how to frame a problem so an AI gets it right the first time, how to recognise when generated code is confidently wrong, and how to keep a project under control as it grows.

The course also covers the path from a personal maker itch to a product other people can use. The later modules extend the capstone with multi-user design and the judgement a solopreneur needs to take a working tool and turn it into something shippable. Whether you want to scratch your own itch or test a real product idea, you will finish with the workflow, the habits, and the confidence to keep building on your own.

Who is this course for?

This course is for technically capable people who are not professional software developers, but who want to build real software with AI assistance.

This course is ideal for:

Hardware and electronics DIYers and makers who want to build their own tools.
Solopreneurs who want to test a product idea quickly and cheaply, without committing months to learning to code.
People comfortable with Python basics, microcontrollers, or PCB design, but new to application architecture, deployment, and AI tooling.
Anyone who has watched an AI write code and wants the workflow and judgement to use that capability safely and productively.

This course is not a fit if you are a professional software engineer looking for deep computer-science theory, or if you want a tour of AI tools without building anything. Here, you build.

Learning objectives

By the end of this course you will be able to take an idea from a sentence in your head to a working, deployed tool, using an AI coding assistant as your collaborator.

You will be able to:

Explain the Five Levels of AI-assisted coding and locate your own practice on that scale.
Use a coding assistant such as Cline or Claude Code to take a project from idea to deployed tool.
Write specifications clear enough for an AI to act on without constant redirection.
Recognise and manage the common failure modes of AI-generated code, including hallucination, context drift, and code that runs but is wrong.
Build five working projects: a browser tool, a command-line tool, a GUI app, a tool with a language model at runtime, and a full capstone application.
Extend a working tool into a shippable product with multi-user design and deployment.

Knowledge prerequisites

You need broad technical confidence, not a programming background. If you are comfortable around a microcontroller and a datasheet, you are ready.

What you should already have:

Comfort running a Python script and editing text files
Basic command-line familiarity, or the willingness to learn it (Module 0 walks you through the setup)
A working understanding of your own hardware or electronics domain, which is exactly the context an AI needs from you
Curiosity and a project you would like to build

What you do not need:

You do not need to be a professional programmer
No prior experience with AI tools, web frameworks, databases, or deployment is required. The course builds all of it from the ground up.

Hardware & Software

Everything you need is free or low-cost, and Module 0 walks you through installing it before you build anything.

Software

VS Code, the free code editor used throughout the course
An AI coding assistant: Cline and/or Claude Code (both shown)
Python 3
A modern web browser
Access to a language model API. The course shows you the free and low-cost options and how to choose between them.

Hardware

None required. All project files and resources are provided as course downloads.
Optional: if you want to follow the serial plotter demo on real hardware, any Arduino-compatible board will do. This is entirely optional and not needed to complete the course.

This course does not require any hardware purchases. All design files, manufacturing outputs, and project resources are provided as course downloads.

Sample lectures from the course

Why I made this course

AI Code assistant capabilities

Capstone project completed

Here's what you're getting:

Video course

"AI Coding for Makers and Solopreneurs" video course.
80+ video lectures in 4K, 18 hours of video.
Each exploration lecture is supported by video, a slide deck, detailed notes, and a quiz.
Each hands-on lecture is supported by video, and detailed notes.
Dedicated community discussion space if you need interaction with the instructor (requires Community Tier purchase).
Lifetime access.

eBook

"AI Coding Assistant for Makers and Solopreneurs", the complete book companion to the video course.
29 chapters across four parts, plus appendices and a glossary.
Four complete hands-on build projects, from a single-file browser tool to a multi-user web application.
Instant PDF download, available immediately after purchase. Fully printable, no restrictions.
No DRM. Your copy is identified only by your email address, watermarked on each page.
Lifetime access. Download once, keep it forever.

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What's in this course?

Module 0 — Orientation and Setup

L0.1 Why I Built This Course

L0.2 What You'll Build

L0.3 What AI Can (and Can't) Do

L0.4 AI Tools and LLM Landscape

L0.4.1 Frontier Models and the Rest (bonus)

L0.5 Install the Default Stack

Module 1 — Foundations

L1.1 What AI-Assisted Coding Actually Is

L1.2 The Five Levels

L1.3 Framing a Problem for an AI

L1.3.1 Use AI to Create a Prompt (bonus)

L1.4 Known Failure Modes

Project 1: RC Filter Analyser

Module 2 — Tools Landscape

L2.1 VS Code as the Default

L2.2 Coding Assistants: Cline

L2.3 Coding Assistants: Claude Code

L2.4 LLMs as a Separate Concern

L2.5 Choosing Data Sources

L2.6 Local vs Cloud

Module 3 — The Workflow

L3.1 Brainstorming and Idea Validation with AI

L3.2 Planning and Specification

L3.3 Implementation Patterns

L3.4 Testing

L3.5 Iteration and Refactoring

L3.6 Documenting for Future-You

L3.7 Deploying for Makers

L3.8 AI for the Non-Code Business Layer

A3.1 Demo: Brainstorming (Serial Plotter)

A3.2 Demo: Planning (Serial Plotter)

A3.3 Demo: Implementation Part 1 (Serial Plotter)

A3.4 Demo: Testing (Flask + SSE)

A3.5 Demo: Iteration (Frontend)

A3.6 Demo: Documenting

A3.7 Demo: Deploying

Module 4 — AI Inside Your Tools

L4.1 When to Put an LLM at Runtime

A4.1 Demo: Planning the Q&A Tool

L4.2 API Basics

A4.2 Demo: API Integration

L4.3 RAG

A4.3 Demo: RAG Implementation

L4.4 Preparing Documents for LLM Ingestion

A4.4 Demo: PDF Preprocessing

L4.5 Cost, Latency, and Graceful Failure

A4.5 Demo: Cost Controls and Resilience

Module 5 — Capstone

L5.1 Capstone Orientation: What We're Building

L5.2 Multi-User Application Design

L5.3 Database Design and the ORM

L5.4 Building a Multi-File Project with an Agent

L5.5 External APIs and Background Jobs

L5.6 Finishing and Shipping the Capstone

L5.7 Designing for Multiple Users

L5.8 The Solopreneur Roadmap (bonus)

A5 Demo Overview: Resource Booking System

A5.1 Demo: Brainstorming

A5.2 Demo: Specification

A5.3 Demo: Schema and Architecture

A5.4a Demo: First Implementation (Auth and Equipment)

A5.4b Demo: First Implementation (Bookings and Availability)

A5.5 Demo: Bonus Features

A5.6 Demo: Iteration, Testing, and Deployment

A5.7 Demo: Multi-User Support

What's in this eBook?

Table of Contents — AI Coding Assistant for Makers and Solopreneurs

Introduction

Part I — How AI-assisted coding works

Ch 1 What it is, and what it isn't
Ch 2 The five levels of delegation
Ch 3 Knowing your own level
Ch 4 Framing the problem
Ch 5 Failure modes and how to catch them
Ch 6 Build: a calculator in a browser

Interlude — The Toolscape

Part II — The development workflow

Ch 7 Brainstorming and idea validation
Ch 8 Planning and specification
Ch 9 The mock-first pattern
Ch 10 Testing
Ch 11 Iteration and refactoring
Ch 12 Documenting for future-you
Ch 13 Deploying for makers
Ch 14 AI for the business layer
Ch 15 Comprehension as a discipline
Ch 16 Build: the serial data plotter

Part III — A language model inside the tool

Ch 17 AI inside the tool
Ch 18 API basics: requests, streaming, and structured output
Ch 19 Retrieval-augmented generation
Ch 20 Preparing documents for ingestion
Ch 21 Cost, latency, and graceful failure
Ch 22 Build: the datasheet Q&A tool

Part IV — A multi-user application

Ch 23 Multi-user application design
Ch 24 Database design and the ORM
Ch 25 Building a multi-file project with an agent
Ch 26 External APIs and background jobs
Ch 27 Finishing and shipping
Ch 28 Designing for multiple organisations
Ch 29 Build: the resource booking system

Appendices & Reference

Appendix A RAG evolution and alternatives
Appendix B The Centaur Test
Glossary

The course instructor

The course instructor is Peter Dalmaris, PhD.

Peter is the founder of Tech Explorations, an electronics education company based in Sydney, Australia. He holds a PhD and has been creating and teaching electronics courses since 2014, with a catalogue covering Arduino, ESP32, Raspberry Pi, KiCad, and PCB design. His courses have reached students across Udemy and his own learning platform. Peter is a published technical author with Elektor, where he has written books on KiCad and Raspberry Pi. Peter brings both academic rigour and hands-on engineering practice to his teaching, with a focus on building real skills through real projects.

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