AI Coding for Makers and Solopreneurs – Tech Explorations

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.

Course Content

Module 0 — Orientation and Setup 5 Lectures | 2 Quizzes

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L0.1 — Why I Built This Course

L0.3 — What AI Can (and Can’t) Do

L0.4 — AI Tools and LLM Landscape

L0.4 — AI Tools and LLM Landscape

L0.4.1 — Frontier Models and the Rest (bonus)

L0.4.1 — Frontier Models and the Rest (bonus)

L0.5 — Install the Default Stack

Module 1 — Foundations 7 Lectures | 3 Quizzes

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L1.1 — What AI-Assisted Coding Actually Is

L1.2 — The Five Levels

L1.2 — The Five Levels

L1.3 — Framing a Problem for an AI

L1.3 — Framing a Problem for an AI

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

L1.4 — Known Failure Modes

L1.4 — Known Failure Modes

Project 1: RC Filter Analyser Briefing

Project 1: RC Filter analyser implementation

Module 2 — Tools Landscape 6 Lectures | 2 Quizzes

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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

L2.4 — LLMs as a Separate Concern

L2.5 — Choosing Data Sources

L2.5 — Choosing Data Sources

L2.6 — Local vs Cloud

Module 3 — The Workflow 17 Lectures | 4 Quizzes

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L3.1 — Brainstorming and Idea Validation with AI

L3.1 — Brainstorming and Idea Validation with AI

A3.1 — Demo: Brainstorming (Serial Plotter)

L3.2 — Planning and Specification

A3.2 — Demo: Planning (Serial Plotter)

L3.3 — Implementation Patterns

L3.3 — Implementation Patterns

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

L3.4 — Testing

A3.4 — Demo: Testing (Flask + SSE)

L3.5 — Iteration and Refactoring

L3.5 — Iteration and Refactoring

A3.5 — Demo: Iteration (Frontend)

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Module 4 — AI Inside Your Tools 11 Lectures | 5 Quizzes

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L4.1 — When to Put an LLM at Runtime

L4.1 — When to Put an LLM at Runtime

A4.1 — Demo: Planning the Q&A Tool

L4.2 — API Basics

L4.2 — API Basics

A4.2 — Demo: API Integration

L4.3 Retrieval-Augmented Generation (RAG)

A4.3 RAG implementation Part 1

A4.3 RAG implementation Part 3

L4.4 — Preparing Documents for LLM Ingestion

L4.4 — Preparing Documents for LLM Ingestion

A4.4 — Demo: PDF Preprocessing

L4.5 — Cost, Latency, and Graceful Failure

L4.5 — Cost, Latency, and Graceful Failure

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Module 5 — Capstone 33 Lectures | 6 Quizzes

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L5.1 — Capstone Orientation: What We’re Building

L5.2 — Multi-User Application Design

L5.2 — Multi-User Application Design

L5.3 — Database Design and the ORM

L5.3 — Database Design and the ORM

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

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

L5.5 — External APIs and Background Jobs

L5.5 — External APIs and Background Jobs

L5.6 — Finishing and Shipping the Capstone

L5.6 — Finishing and Shipping the Capstone

L5.7 — Designing for Multiple Users

L5.7 — Designing for Multiple Users

L5.8 — The Solopreneur Roadmap (bonus)

A5.1 — Demo: Brainstorming

A5.2 — Demo: Specification

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Conclusion 1 Lecture

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