Applying prompts to GenAI/LLMs

The Problem: The "Generic App" and the "Time Sink" We’ve all been there: a student walks into a 1-to-1 with a vague desire to "do something with AI" or "build a fitness app." You spend 45 minutes trying to find a technical "hook" that justifies a Level 6 or Level 7 grade, only for the student to drift back into "CRUD app" territory by week three. The Philosophy: AI as a Mirror Instead of you doing the heavy lifting, this workflow uses AI as a Mirror . It reflects the student’s own skills and career goals back to them, but with the structural rigour of a virtual supervisory team. It’s not about the AI "giving" the idea; it’s about the AI forcing the student to defend and refine their own concepts until they hold water. The Framework: 3 Months of Rigour This prompt is specifically designed for intensive/conversion MSc or summer capstone projects . It assumes a tight 12-week implementation window. By forcing the AI to w...

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...

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...

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...

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...