Applying prompts to GenAI/LLMs

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? Between the long lists of citations and dense technical titles, "connecting the dots" of a decade-long career is a massive cognitive lift. Whether you are a student hunting for a dissertation topic or a professional scouting for a collaborator, understanding the trajectory of research is harder than reading the papers themselves. In my latest experiment, I used Google Gemini to see if it could bridge this gap. I gave it a specific challenge: Analyze my own research profile and design 10 compelling project ideas for a final-year Computer Science student. The Prompt: Turning Data into Direction The secret to a good AI output is giving it a clear "anchor." By providing a URL to a live dataset (my Scholar profile), I bypassed the need to copy-paste thousands of words....

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 One of the most significant cognitive hurdles for students is the transition from a high-level area of interest to a rigorously defined project specification. This "blank page" problem often leads to poorly scoped projects or a lack of alignment with current academic literature. Building on my previous experiments in prompt-mediated productivity, this post examines a structured workflow for using Large Language Models (LLMs)—specifically GPT-4o—to scaffold the development of a BSc Software Engineering project proposal. The Methodology: Multi-Stage Prompt Scaffolding Rather than requesting a single output, the workflow utilizes a recursive prompting strategy. This mirrors the iterative refinement pr...

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...

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 text interface for ChatGPT prompts and responses. It feels more like using a featured text editor.  At the moment OpenAI are rolling out canvas to ChatGPT Plus and Team users, then   Enterprise and Edu users will get access next week; with the plan to  make canvas available to all ChatGPT Free users after the beta stage. So to have a bit of a play I put an old document through it (selected the ChatGPT 4o with canvas option from the  ChatGPT Plus drop-down menu), a skeing it to use that document as a starting point for a report. One of the difference is both windows are editable for prompts. So using the lefthand side you can put in a prompt as normal  in ChatGPT but in the right-hand wind you highlight the text and ask  ChatGPT  do action that bit .  You can...

Image created using DALL-E - love the bad spelling I want to explore using Generative AI to explore and compare websites. So I used using Google Gemini because of it its ability to work easily with websites.I choose UK three political party websites purely to compare like with like. Prompt 1: Analyse the following webpages website 1 https://www.conservatives.com/ , website 2 https://www.libdems.org.uk/  and website 3 https://labour.org.uk/ from a web user's perspective. For each website produce a report containing 2 tables. The first Table list issues with the site; for each issues provide at least three examples and then provide a list of potential solutions. Table 2 strengths of the site with each strength provide at least three examples. Add in any commentary Results It produced two tables per website and provided a summary comparing them at the end. Direct political statements were not produce. Now trying out personas and testing the website the politics side not filtered out ...

Using ChatGPT4o to produce the start of a literature review with a comparison table and references.  Prompt 1: You will generate a search and produce a summary table of published papers on the following topic " VR in Higher Education "   Iterate 5 times the following Step 1,;Step 2.; Step 3.; and Step 4.,   Step 1. Search for 3 new papers relating to the topic and add to the list of papers stored;   Step 2, Identifying a Common Features to at least three papers not included in the previous interaction. Each iteration all Common Features are maintained but can be revised;   Step 3. On each iteration from the papers stored revised the following table. The table will have four parts: Common Features , summary the of the Common Feature, identified and included all papers that have Common Feature, all papers that don't match the Common Feature;   Step 4. Add the full reference to all the paper to a Harvard styled reference list ....