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A Practical Guide to Building Lessons with AI (Real Savings, No Shortcuts)

There is no shortage of articles telling academics that Generative AI is going to transform education. It is, and it will continue to do so. However, many of these pieces are long on enthusiasm and short on detail. This is not one of those. What follows is a practical account of using ChatGPT to build a real teaching session. I’ll cover what I did, what worked, what failed, and how long it actually took. No hype—just the reality of how it saved me time and how it could possibly do the same for you. The Test Case My subject was a four-hour session on Pytest in Django , aimed at final-year BSc Software Engineering students. These students have a basic grasp of Django but possess solid overall coding skills. The session was split into a one-hour lecture and three hours of hands-on practical work in VS Code. The Strategy: Starting with the Prompt The key to getting useful output is being specific upfront. Rather than simply asking ChatGPT to "create a lesson on Pytest," I provide...
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From Boring to Beautiful: How I Used Claude to Transform a Dash App in Minutes

I've been learning Python data visualisation, working through Murat Durmus's Hands-On Introduction to Essential Python Libraries and Frameworks alongside the official Dash tutorial . The resulting code was functional — a basic bar chart comparing data for San Francisco and Montréal — but it looked like exactly what it was: a beginner's first attempt. Plain white background, default colours, numbered axes, and a title that just said "Data Viz." So I decided to run an experiment. Could Claude AI turn a scrappy 20-line script into something genuinely worth showing people? Before running the prompt The First Prompt I pasted the code into Claude.ai with a simple instruction: "Rewrite this following code to be graphically more interesting." The result was striking. Claude switched to a dark "neon terminal" aesthetic — deep navy background, electric teal and magenta accents, and a stylish monospaced font. The bars got proper labels, the axe...

From Blank Page to Proposal: Mastering GenAI for Academic and Professional Projects

For many professionals, one of the hardest parts of any project isn’t the work itself—it’s the "blank page" problem. Whether you are drafting a project proposal, conducting a literature review , or  brainstorming  innovative solutions, getting started can be a significant mental hurdle. Generative AI (GenAI) tools like ChatGPT, Claude, and Copilot are often described as "content creators," but their true value for professionals lies in enhancing productivity. By applying specific prompting techniques, you can transform a vague idea into a well-structured, reference-supported document in a fraction of the time. Here is a three-step workflow to turn GenAI into your ultimate research and planning partner. 1. Brainstorming with "Personas" and "Templates" Don't just ask the AI for "ideas." To get professional results, you must give the AI a Persona (who it is acting as) and a Template (how you want the output to look). In our recent ex...

#Onions and Prompts

I recently came across a genuinely useful idea on Tom's Guide about using an “onion prompt” with AI to organise your schedule when you’re overwhelmed. If you haven’t seen it, I’d strongly recommend reading the original article — it explains the thinking behind the method and the psychological principles that make it effective: https://www.tomsguide.com/ai/i-use-the-onion-prompt-with-chatgpt-when-im-buried-in-tasks-it-cuts-through-clutter-in-seconds How I’ve adapted it I’m using Google Gemini rather than ChatGPT, and I used my task list from Google Keep instead of viewing my desktop. The tools are little different (but not too much), but the central ideas are the same: strip away the layers hiding your real priorities and let AI “peel back” your to-do list until only what truly matters remains. To make it easier, I copied my Google Keep list into a Google Doc and pasted it into the prompt. Prompt 1: Prioritising with the “Onion” Method Here’s the version I’m using (slightly adapt...

Reverse engineering a specification from a solution using GenAI: Part 1

Imagine buying complex furniture, but the instructions are a chaotic pile of sticky notes. That is exactly how programmers feel when trying to connect different web services (like weather apps or payment processors). They usually have to dig through messy documentation just to make two programs talk to each other. The OpenAPI Specification (OAS) fixes this by acting as a universal, standardised "Instruction Manual." Why It Matters OpenAPI acts as a perfect bridge between humans and machines: For Humans: It provides a clear map of what a service does, what information it needs, and what it returns. For Computers: Because the rules are strict and predictable, software can "read" the manual and automatically connect to the service. What Can You Do With It? With an OpenAPI blueprint, developers can plug into tools that do the heavy lifting for them: Create Visual Guides: Turn complex code into sleek, interactive websites where users can test the service with the cli...

Ideas to project proposal ideas from Google Scholar - the video

GenAI Productivity: Ideas to project proposal ideas from Google Scholar

From Google Scholar to Project Ideas or Using AI to Map the Future of Your Research Generated as well by Google Gemini Have you ever looked at a researcher's Google Scholar profile and felt overwhelmed by the lists of citations and technical titles? Whether you are a student looking for a dissertation topic or a professional trying to understand a collaborator's expertise, "connecting the dots" can be a challenge. In my latest experiment, I decided to see if Google Gemini could bridge that gap. I gave it a challenge: Look at my own research profile and design 10 compelling project ideas for a final-year student. Prompt used :  " Using this as a starting point https://scholar.google.com/citations?user=ghQedZAAAAAJ&hl=en from the research here provide 10 project ideas suitable for a final year Computer Science student project with this supervisor. For each provide title, 100 word summary, possible outcome s " The "Ego Ride" with Unexpected Res...