Applying prompts to GenAI/LLMs

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...

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...

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...

Produced using Google Gemini In two previous posts I looked at using Generative AI to start producing  project ideas and refining one to be the start of the proposal, Previous blog posts GenAI Productivity: Ideas to project proposal 1 GenAI Productivity: Ideas to project proposal 2 This post is really a slightly different variation on those. Playing with adding a few things in. The example can be repurposed for non-computing student but the example came from a discussion with a BSc Software Engineering student, thinking about project ideas Example starting prompt in ChatGPT4o " P roduce 5 project ideas suitable for a BSc Software Engineering students for the following topic: " Ambient Assisted Living " The project must suit someone with a strong interest in programming.  For each idea produce a 100 word description; justification in 200 words why this is a worthwhile project; a set of goals; sources of potential data; physical resources neede d " It does produce 5 p...

OpenAI has just announced canvas ( https://openai.com/index/introducing-canvas/  ) with ChatGPT as a beta in  ChatGPT Plus . Canvas is an extra interface along with the standard prompt interface which we have got used to.  In an earlier post, I started discussing using Canvas for  reports,  but what about coding? People have been using generative AIs for coding, including code generation from prompts, but what does it do when we use canvas. So let's play. The new interface for canvas does support coding (as does ChatGPT) - could it be a programmer's friend/assistant?  In the example below ChatGPT was asked via an initial prompt to produce a pseudo-code for the start of a murder-mystery style game, but to also use canvas.  What it produces is a form pseudo-code in the style of Python; not a great surprise there, as ChatGPT is not bad at generating Python code. So, can it convert the pseudo-code to something other than Python? The two examples below sho...