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Avoiding a Howler of a Performance Review Sometimes it feels like you’ve only just closed out one performance cycle before another one rolls in. Endless requests, forms to fill, and the occasional awkward self-assessment. There’s no denying performance reviews and regular feedback are essential to our professional development. Whether it’s understanding how we’re showing up, growing in knowledge and capability, or identifying where we need to level up. But with back-to-back meetings, deadlines, and never-ending to-do lists, traditional performance management can often feel more like a chore than a chance for reflection or a kick-starter for growth, What if we could turn feedback into something magical? Cue the Sorting Hat. In the midst of delivering a comprehensive Microsoft 365 Copilot learning programme, and just ahead of a performance review cycle, a colleague shared a prompt that completely changed how I approached self-reflection. It created what I shall now call "a Remembrall  moment". The prompt was clever, creative, and if I’m completely honest, b****y brilliant! It went something like this: “You are the Sorting Hat from Hogwarts. Using my recent activity across Teams, Outlook, and Copilot over the past two weeks, analyse my communication style, decision-making patterns, collaboration habits, and leadership traits. Based on this, assign me a character from Harry Potter and assign me to one of the four Hogwarts houses—Gryffindor, Hufflepuff, Ravenclaw, or Slytherin. Justify your choice with specific behavioural insights and include a quote from and in the style of the Sorting Hat to support your conclusion.” As prompts go, this one hit a sweet spot. With Copilot seamlessly embedded across my everyday apps (Teams, Outlook, Word, and more), it painted a cracking portrait of how I show up and the strengths I display. My Magical Revelation According to the wise old hat, I’m most like Professor Remus Lupin, empathetic, quietly influential, and with a knack for guiding others through complexity. And my house? Ravenclaw. Apparently, my curiosity, creativity, and love of structured problem-solving gave me away. What I loved most was how Copilot structured its response, taking note of the expectations I'd set out in my prompt. Each observation came with references (direct examples from my recent work history) so I could see how it formed its conclusions. I could then challenge them, reflect on them, or simply nod along in agreement. The Prompt Chooses the Prompter Potter puns aside, if you’re dreading your next round of performance management or personal development planning, give this prompt a go. Ask Copilot to don the Sorting Hat and give you a magic mirror of your own to reflect your working self. It might just make the whole experience, well, enjoyable. And who knows, you could discover traits you hadn’t noticed or strengths that deserve more time in the spotlight. It would be great to see in the comments: What character did you get? Which house were you sorted into? And did it spark your own "Remembrall moment"? Because if we have  to do performance reviews, we might as well make them magical. Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat

Another week down and I’ve finally found a moment to pause and reflect. In the middle of running Microsoft 365 Copilot learning sessions recently, one question has kept popping up. And rightly so. Not “How do I get my week summarised to me in the style of a rap?” or “How do I actually get Copilot in PowerPoint to apply my brand guidelines?” (although that last one comes up more than I care to admit). Luckily, this time, it is something far more important. How environmentally friendly is it to use? Should I be using Google instead? It is a fair question and one that is always there in the background as I experiment and find the best ways of working with AI day to day. Should I be searching, prompting and what are the implications to the planet? Interestingly, some research suggests there is a generational shift in our search habits skewing us ever increasingly towards AI for search. Younger users are leading the shift in starting-point behaviour, with 28% of Gen Z beginning their searches on ChatGPT (Adobe, 2025) Gone may be the days of instinctively “googling it” when we want to find or understand something. With AI tools like Copilot and ChatGPT in the mix, we now have a choice, and those choices carry different environmental costs. Does prompting with AI cost more to run than search? Using Google for a simple search uses surprisingly little energy. You ask, it checks its vast index, and it sends back the answer in milliseconds. It is highly optimised and therefore highly efficient. AI works differently. Each time you prompt, it generates a new answer for you there and then. It is like making a meal from scratch when there is a pre-prepared one ready and waiting on the side. This requires far more computational energy and rapidly adds up. One study suggests that “a generative AI system might use around 33 times more energy than running task-specific software” (Kelion, 2025). With the growing user base and volume of daily prompts, that difference could become significant. But it's not that clear cut There is some nuance here. Depending on the task, there is a case for which tool to pull out of the box. If it is a simple question, like identifying the actor in a certain film, search is probably a greener choice. However, if you are looking to summarise a report, translate a document or ideate for a workshop, the use of AI could save you and your peers hours, potentially avoiding multiple searches, clicks and time spent churning through several documents. The recent challenge is that search engines themselves are getting more AI-driven. My recent Google searches have sometimes served me an AI-generated summary at the top of the results page. This is highly convenient, but it starts to blur the environmental line and the argument for using search or prompt. So what might be the solution? Some companies are showing their working, with firms calculating the cost of use. These figures do not make for light reading. Google's carbon emissions have soared by 51% since 2019 as artificial intelligence hampers the tech company's efforts to go green (Hern, 2025) Google has struggled to curb its emissions and is seeing its energy consumption increase each year as the demand for AI grows. In my work and observations with innovators through to sceptics, encouraging the use of AI tools in the day-to-day has largely hinged on finding high-value use cases that make work more enjoyable, efficient or of greater quality. In doing so, it sparks enthusiasm to find more, and using AI becomes second nature. The one area I am always encouraging is mindful use and critical thinking, ensuring outputs are reviewed and challenged appropriately. This is a skill we cannot afford to lose. I do wonder if we need something more visible to curb our enthusiasm to use AI as the default. Would making the environmental impact more visible before prompting encourage greater thought into whether AI is the right tool for the job? Could our own computational power be up to the task, or could we take the time to use different sources to get to a great result? I often find the process of crafting an excellent prompt provides greater clarity on the ask and whether AI is likely to handle it well or whether I would be better doing it solo. For now, how do I decide what to use and when? Here's the guidance that I try to apply to my daily life. Use search when: You're looking for a quick fact You're browsing options and ideas and have time to scan You're doing something straightforward and low effort Use AI when: You're looking to synthesise information from many sources You're tailoring some output in a particular style or context You're going to save hours of extra work and other energy use And no matter what you choose, you can reduce your footprint further by: Being specific in your prompts so you get to the desired result quickly, with the least amount of processing Choosing efficient tools, for example on-device AI, which can use less power than cloud-based models Batching your requests so you get what you need in as close to one go as possible Why does it matter? In the constant pursuit of instant gratification and never being more than a metre away from technology, it is easy to think our digital actions have no consequences. But behind the scenes, vast cooling systems are running 24/7, using millions of litres of water a year, and energy consumption is growing. We do not need to be perfect, but we can be more mindful. A little awareness and self-challenge can help us work smarter, use AI responsibly, and work a little greener. If there are ways you are encouraging mindful use that you would like to share, please let me know below. References Adobe.  (2025) ChatGPT as a search engine: Benefits, drawbacks, and how it compares . Available at: https://www.adobe.com/express/learn/blog/chatgpt-as-a-search-engine  (Accessed: 15 August 2025) Hern, A.  (2025) ‘Google’s emissions rise 48% in five years due to AI electricity demand’, The Guardian , 27 June. Available at: https://www.theguardian.com/technology/2025/jun/27/google-emissions-ai-electricity-demand-derail-efforts-green  (Accessed: 15 August 2025). Kelion, L.  (2025) ‘ChatGPT: Why we should all be more mindful about using AI’, BBC News , 14 August. Available at: https://www.bbc.co.uk/news/articles/cj5ll89dy2mo  (Accessed: 15 August 2025) Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 5 [Large language model].  https://chat.openai.com/chat Images: Midjourney (2025). V7 [Image generation model] https://www.midjourney.com/ / OpenAI. (2025).  ChatGPT 5 [Large language model].  https://chat.openai.com/chat

We often hear about the breakthroughs where Gen AI saves time, unlocks insight, and helps teams work smarter. I’ve often been that person on my soapbox, waxing lyrical about what I’ve been able to achieve with it. But what happens when it doesn’t go so swimmingly? Recently, I found myself deep in an Excel challenge, using Gen AI to build and debug something in PowerQuery. As with most of my endeavours, it started with a great deal of promise. I came armed with clear intentions, helpful prompts, and the confidence of someone who works with Gen AI daily. But gradually, I began running into snag after snag, and the route to success became muddy. I rephrased, reframed, and chain-prompted in a valiant effort not to concede. Eventually, the only thing that stopped me was running out of chat interactions altogether. Rob: 0, GenAi: 0. More frustrating than the tool itself was the sense of time wasted, and the creeping thought that I should’ve just solved it myself or asked a colleague. The Reality Behind the Gen AI Promise Gen AI is reshaping how we work. But amidst the excitement, it’s important to acknowledge a more grounded truth: Gen AI isn’t infallible. It’s not always accurate. And it’s certainly not always efficient - especially when time is tight. Having lived and breathed fast-paced environments, the expectation has always been to deliver effectively at speed. Yet even the most advanced tools can’t deliver without direction, clarity, and importantly, patience. That’s not a failure of the technology. It’s a reminder that how  we use Gen AI matters just as much as what  we use it for. That’s why I wanted to share some reflections and the mindset shifts I’ve adopted when facing challenges with the tech myself. Three Practical Mindset Shifts for Professionals Using Gen AI If you’ve ever found yourself in the same boat of being frustrated with a Gen AI assistant, you’re far from alone. Here are three of my takeaways to help you make the most of these tools (without hurling your device in the process): 1. Start with clarity, not just curiosity Gen AI performs best when it’s grounded in specifics. A vague prompt will lead to a vague response. A well-framed question or challenge that's complete with context, constraints, and a clear goal can save you multiple prompts and iterations. Think of it as briefing a team member: if you wouldn’t ask a colleague to “just fix this” without context, don’t ask Gen AI to. 2. Take a pause when progress stalls When the answers feel off or inconsistent, resist the urge to keep pushing. (Learn from my mistake here.) Instead, step away. Break the task down as if you were explaining it to a peer. Often, the clarity you need doesn’t come from more prompts, it comes from rethinking the problem. 3. Know when Gen AI isn’t the right tool Not every task is Gen AI-ready. Some problems are better solved through search, experience, or a five-minute chat with someone who has been there. This isn’t a weakness, it’s a strength. It’s what we did long before this technology became our go-to coach. The best professionals know when to change tack. Moving Forward: Human Insight Still Leads the Way The rise of Gen AI isn’t about replacing thought, it’s about enhancing it. And sharpening that skill will be essential as Gen AI becomes more embedded in the way we work. There will be moments when this technology accelerates your output, and moments when it slows you down. What matters is your ability to navigate both with intent and knowing when it’s time to adjust your approach. So if your next Gen AI session doesn’t yield results on the first try, don’t be discouraged. Invest a little more up front. Step away when needed. And remember: sometimes the best guidance still comes from human experience. Efficiency isn’t just about tools, it's about judgment. And judgement, no matter how advanced AI becomes, is still very much a human skill. Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat

Why I Hadn’t Made My Doll The AI-generated “boxed doll” trend really took off. You know the one: design yourself as a mini figure, accessories and all, like you just came off the shelf at a toy store. But while everyone else was posting theirs, I hesitated. Not because I don’t love a good internet trend (those who know me well, know I do), but because… where would I even start? As someone who sees themselves as a bit of a jack of all trades, narrowing down my “accessories” to just three or four items made me spiral immediately. Straight away, I was heading into expansion pack territory. Would I include a bass guitar? Running shoes? The 6kg or 9kg Hyrox wall ball I’m desperately trying not to drop on my head each week? The more I thought about it, the more it became less about defining myself and more about realising how many versions of “me” (and “us”) there really are. And that’s one lesson from this trend: we should stop boxing ourselves in and appreciate that we’re all multi-faceted, evolving, and beautiful in our own unique ways. Spoiler: I did create my doll but I had him break out... Then the AI-Skeptics Came Knocking From appreciating our differences to seeing a shift in narrative, what surprised me most was who  was making their boxes. Friends who had previously rolled their eyes when I’d gone full TED Talk about Gen AI were now sending me their creations: “LOOK what I made!” “Isn’t this so cool?” Suddenly, the story wasn’t about efficiency, productivity, or workflow automation. It was about play . Creativity. Pure, joyful self-expression that got the experimentation flowing and brought a whole new audience into the fold. There’s a reason ChatGPT just overtook TikTok and others as the most downloaded app in the Apple Store a few days ago. More people are seeing what's possible, and nobody wants to be left behind. From Free Fun to Paid Priority The real moment came when my partner ran out of her free credits and asked for help getting her doll across the finish line. This wasn’t just a fun little distraction anymore — it had shifted into something worth paying for (or at least worth borrowing a premium account for). Not because it saved time, but because it sparked joy. And that shift? That’s what real adoption looks like. It’s also how I, and many organisations, need to start thinking about driving meaningful AI use: What are those moments of joy we can spark that make users not want to turn their backs on this technology? We’ve Been Asking the Wrong Question For quite a while now, the north star in most Gen AI deployments has been: “How can this make work more efficient?” And while we all have a million and one things on our to-do lists, the focus on doing more, doing it differently, or (heaven forbid) doing less, has been largely anchored around personal and operational efficiency, not enjoyment. But here’s the thing: improved enjoyment leads to better adoption, better engagement, and ultimately, better outcomes. So maybe we’ve been looking at it wrong. Maybe the better question going forward is: “How can Gen AI make our work more fun?” Ease of use is important, sure. But this trend has proved something bigger: the real pull is fun. That moment of “oh wow, I made this” sparks curiosity and keeps people coming back. AI doesn’t just need to be useful. It needs to be enjoyable. A New Way to Show Who We Are Beyond driving adoption, these packaged dolls have more powerful use cases — especially in the workplace. How often have you joined a new organisation or team and had to do the standard “tell us about yourself” intro? What if, instead, your whole team brought their AI-generated doll boxes to the table? It’s a playful, creative way to spark conversation and deepen understanding. You get a sense of what drives someone, what excites them, and what makes them tick — both in and out of work. And that matters, especially in the more hybrid, less face-to-face way we work today. Has the Early Majority Arrived? Potentially. This isn’t just for the innovators and early adopters anymore. The early majority may have just walked in. And they came not because they had to, but because they wanted to. Now that they’re through the door, we have an opportunity to rethink the whole experience of generative AI. This means designing for delight first, with efficiency following close behind. So, What Now? 🧠 Think Outside the Box What would your accessories be? What makes you you and how might sharing that help others connect with you more easily? 🎨 Redefine the Use Case What if your next generative AI project didn’t start with a spreadsheet or slide deck but with a spark of curiosity, delight, or imagination? 🧊 Use It as an Icebreaker Introducing yourself to a new team? Skip the bullet points. Show them your doll version. It’s instantly more personal and gives people something fun to ask about. Generative AI didn’t go mainstream because it made us more efficient. It did it by making us smile. By letting us box ourselves in, we’ve actually opened up something much bigger: a new way to connect, create, and play. And that might just be the spark we’ve been waiting for. Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat

After four unforgettable days exploring Rome, I've found myself back home with a head full of memories, phone full of photos, and unfortunately… a bug that has completely wiped me out. But while I’ve been battling high temperatures and living off hot fruit juice and paracetamol, one thing has remained consistent: the pace of change in the AI space is as fast as ever. Especially when it comes to AI-generated images. Despite being stuck in bed, I’ve had brief moments to dive into the latest advancements in ChatGPT’s image capabilities, and I’m genuinely blown away. These new tools aren’t just interesting but they’re already reshaping the way professionals and creatives approach content creation. Inspired by posts from my network, let me walk you through a couple of real-world examples I've tried myself. Professional Headshots in Minutes, Not Weeks Not long ago, I needed a fresh set of professional headshots for an article I was writing on Microsoft 365 Copilot. You probably know the drill: Book a slot Do your hair Head into the office Ride the lift to the umpteenth floor 15 seconds of photos Wait 3–5 business days for delivery (plus edits) All in all, a two-week turnaround for a few usable images. This morning, using ChatGPT’s image generation tools, I was able to produce high-quality headshots in under 8 minutes. No studio. No lighting. No scheduling. Just a single prompt, and a reference image. The results were surprisingly polished and honestly, good enough for most professional use cases. The prompt: Using the gentleman in the attached picture, please could you create me three professional headshots for a new LinkedIn profile picture? I would like options you create to include: A) A head-on photograph B) A photograph with a slight tilt towards the right C) A photograph with a slight tilt towards the left. The demo: The results: Not bad right, even if one of the tilts was a further rotation to one side. For busy teams, consultants, remote workers, or anyone needing quick image updates, this is a genuine productivity unlock. Media Asset Creation: From Blank Canvas to Branded Content in Minutes I’ve always loved designing and reimagining iconic creations. Whether it's drawing inspiration from advertising campaigns or experimenting with new design styles, I can happily lose hours perfecting a single piece. But time is the one thing most of us don’t have in abundance. Starting from scratch could be 2–4 hour project, minimum. With ChatGPT’s new visual capabilities, you can take a previously created asset, like a social post, a campaign banner, or a simple poster and reimagine it in minutes. That means faster iteration, sustained content quality, and more room to experiment without the risk of sunk time. Naturally, I had to test this with a design and area that I'm highly passionate about: F1. Here's how we got on... The prompt: Recreate my [poster] (second photo attached) with my [new protagonist] (first photo attached). Please change the text saying '[insert text here]' to '[insert text here]'. The demo: The result: So What Does This Mean for Creators, Marketers, and Businesses? Here are a few takeaways if you're thinking about incorporating AI image generation into your workflow: Speed  – What once took days or weeks can now be done in minutes. Creativity on Demand  – Need a new visual angle? A rebranded asset? An AI-generated draft lets you test ideas faster. Scalability  – Whether you're building a campaign or refreshing headshots for a global team, you can scale up without burning out your design resources. Democratisation  – You don’t need to be a designer or have access to expensive tools to get good results. For transparency, the demos created here have been made with ChatGPT Plus however, it has been reported at the time of writing that free users will soon be able to generate up to three images per day. The Bottom Line: AI Isn’t Coming for Creativity - It’s Collaborating With It Whether you're in bed with a fever or working against a tight deadline, these tools open up a whole new layer of creative possibilities. They reduce friction. They save time. And when paired with a human sense of style, storytelling and creativity, they can really shine. How have you used the latest features to improve your creativity? Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat

We live in a world that increasingly values speed and glorifies productivity. Instant replies, rapid decision making, and AI-generated content are all designed to remove friction and save time. But while efficiency is important, there are moments when speed can actually diminish an experience - where getting there fast doesn’t always last. When things move too quickly, they can feel rushed or impersonal. On the other hand, poorly managed delays can leave people feeling lost and forgotten. The real key is not just how long something takes, but how well expectations are managed throughout the process. A Relatable Example: Hiring – Striking the Right Balance Between Speed and Thoughtfulness We've all been applicants, and many of us have sat on the other side of the desk (or screen, nowadays). We know there’s a lot on the line for both the applicant and the employer - the effort poured into applications, and the pressure to hire the right candidate. In the early stages of the hiring journey, there’s a perfect example of why balancing speed and care is crucial. Good candidates spend hours tailoring their CVs, crafting cover letters, and refining applications. If they receive a rejection or even an invitation to interview within minutes, it can feel at best rushed and at worst dismissive, as if their effort and application wasn’t truly considered. On the flip side, if a company takes weeks to respond, applicants feel ignored, left in limbo, and ultimately disengage. The most effective hiring processes manage time deliberately. A response that is timely but not immediate signals thoughtfulness. Automated confirmation emails reassure applicants that their materials were received. Even a simple update like, "We're still reviewing applications,"  prevents frustration. The process doesn’t need to be instant, but it does need to feel fair and intentional. Clearly outlining your application process and expected review time benefits both successful and unsuccessful candidates, helping to maintain trust, strengthen your brand, and uphold your reputation.. AI Interactions: Delays - The Illusion of Thoughtfulness AI, much like hiring decisions, benefits from pacing that feels natural. Some AI tools instantly generate a long, fully formed response in milliseconds. While impressive, this can feel mechanical, like the output was copied and pasted rather than crafted in real time. It also removes any sense of co-creation, an important feeling to have if you are to adopt generative AI in your day-to-day. This is why many AI systems simulate the experience of typing. The delay isn’t always because the AI needs  time to process and think; it’s also because that pause makes the interaction feel more human, as though the response is forming organically. As communication expert Vinh Giang puts it: Pausing prior to answering allows you to think through your answer - this comes across as more thoughtful and gives more weight to your answer. When applied to AI, this subtle design choice of pausing or simulating typing at a more human speed builds trust. It makes users feel like they’re engaged in a real conversation rather than receiving a pre-generated answer. Similarly, automated customer service agents often introduce short delays between responses. This prevents interactions from feeling robotic and reassures users that their input is being considered rather than instantly understood - particularly important when the agent hasn't quite understood the query. In many cases, the illusion of thoughtfulness is just as important as the actual content of a response. Expectation Management: Transparency - The Real Key to Trust The frustration we feel in slow processes or unexpected results isn’t necessarily about time itself - it’s about uncertainty. When people don’t know what’s happening or when expectations aren’t met, they assume the worst. Managing expectations, whether through progress updates in hiring, onboarding, or even guiding users on how to get the best out of AI can make all the difference. This principle applies to many examples: A process doesn’t need to be the fastest - it just needs to feel considered, transparent, and fair. And interestingly, sometimes when there is an intentional delay introduced, the perceived quality can increase. Rory Sutherland talks a lot about this - I would highly recommend taking a listen. Essentially, slow and steady doesn’t just win the race, it can build trust along the way. The best experiences aren’t defined by speed alone but by how well they guide people through the journey. Final Thoughts In a world obsessed with speed, we often underestimate the power of pacing. Whether it’s a job application or an AI response, deliberate timing can enhance trust, engagement, and overall satisfaction . Next time you're designing an experience, consider this: A little extra time, when well-managed, isn’t an inconvenience. It’s an opportunity to build a deeper, more thoughtful connection. Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Quote: Giang, V. (2024) ‘Don’t be scared to pause before you answer’, LinkedIn , 25 February. Available here .

The Unexpected Power of a Simple Habit It’s amazing how much joy can be found in reflecting on the little moments that made life special a year ago. After three years of celebrating, grafting, laughing, and everything in between, I’ve captured it all - from the mundane to the monumental - and in doing so, I’ve started to see myself, and the people all around me, in an entirely new light. A good one I might add. But where did it all begin? I owe this habit largely to my sister. In July 2022, she gifted me a One Line a Day  journal - a simple notebook with space to document a short daily entry over five years. At first, it seemed like a fun way to capture the highlights of my upcoming 30th birthday trip to New York. The soaring skyscrapers, the amazing aircraft on Intrepid, and the delicious delight that was Nathan’s famous hot dogs over at Coney Island. But beyond the excitement of travel, journaling became something deeper. It became a lens through which I started to see my life differently . From Novelty to Necessity Post-New York, reality hit: not every day is that exciting.  It would have been easy at that point to stop, but instead, I became more intentional about adding novelty and making each day count . I also considered shifting my approach, turning my journal into more of a gratitude practice, however my love for consistency kept me tied to my original approach. Then, this Christmas, I received a new journal with lines upon lines of space. Finally, I had the golden opportunity I'd been waiting for - to start a gratitude practice without altering my one line a day. Now, my evening routine has evolved to: Five minutes of journaling Ten minutes of gratitude reflections (and now quality capturing too) Three minutes of Duolingo (because habits are contagious!) And one very patient partner. This simple routine has brought unexpected benefits  that I never anticipated. The Benefits I Never Saw Coming 1. Strengthening Friendships and Remembering Key Moments Journaling has become my secret weapon for reconnecting with loved ones. I’ve used my entries to: ✔ Remind friends of special moments we’ve shared  (like inside jokes or old adventures). ✔ Reach out on anniversaries —from weddings to loss—offering support at just the right time. ✔ Deepen relationships  by remembering the small details that matter most. The ability to reflect on both highs and lows  has made my friendships richer and more meaningful. 2. Tracking My Growth & Maturity Reading old entries, I see just how much I’ve changed. Journaling has helped me: ✔ Spot patterns —in decision-making, relationships, and work. ✔ Learn from past mistakes  and avoid repeating them. ✔ Worry less —seeing how I’ve overcome previous challenges reminds me to trust the process. There’s something powerful about revisiting old worries and realizing how trivial they seem now. It’s made me calmer, more confident, and less reactive  to life’s inevitable ups and downs. 3. Shifting My Focus from What’s Missing to What’s Good When I expanded beyond one line a day  into gratitude journaling, I realized just how many small joys I was overlooking. Suddenly, I started appreciating: ✔ The simple pleasure of morning coffee. ✔ That wobbly feeling post-gym (a reminder of effort put in). ✔ A random kind gesture from a stranger. This shift has boosted my mood, improved my sleep, and rewired my thinking  to focus on abundance rather than lack. How to Start Your Own Journaling Habit Journaling doesn’t need to be complicated. If you’re unsure where to begin, try my simple MGQ method: My MGQ Method 📖 M – Moments:   What stood out in your day? 💡 G – Gratitude:   What are you thankful for? ✨ Q – Qualities:   What personal qualities did you display today?* Example Entry: M:  Caught up with an old friend over coffee, walking around a sunlit park. G:  Grateful for the free biscuit that came with my drink. Q:  Showed generosity by paying for my friend’s coffee. 💡 Don’t overthink it—just write what comes to mind! *If you're wondering why I also capture qualities, this is a recent practice I've found extremely useful for improving positive thinking, self-esteem and self-worth. In reflecting on and writing down the qualities displayed throughout the day, you are actively seeking good traits that make you feel better about how you showed up, not matter how big or small. Journaling Might Just Change the Way You Think After years of journaling and a few months of gratitude tracking, I now see my life through a lens of appreciation, reflection, and growth . I no longer dwell on what’s missing; I focus on the memories made, the journey I'm on, and the good already present in my day-to-day. So, here’s my challenge to you: Start today.  Pick up a notebook and jot down a single sentence. Do it again tomorrow. And keep going. And if you don’t see the benefits? I dare you to tell me I’m wrong. Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat

As a frequent user and coach on maximising tools like Microsoft 365 Copilot, finding shortcuts to improve adoption and efficiency has become a personal mission. I’ve covered simple, chain, and mega-prompting techniques with various groups, but one recurring challenge has been the ability to quickly access previously written or curated prompts. For those perhaps less familiar, a prompt  is a command given to the generative AI to elicit a specific type of response. The way we structure our prompts - our technique - greatly impacts the quality of the results. My best responses have come from mega-prompts , where detailed instructions provide the AI with ample context to generate tailored and useful replies. Until recently, I relied heavily on Excel spreadsheets and OneNote templates to store prompts for easy access. But not anymore. Introducing Copilot Prompt Gallery Rediscover and Share Your Best Prompts in an Instant Rediscover yours and your teams saved prompts Gone are the days of copying and pasting prompts into shared libraries that rarely get revisited. Microsoft now enables users to save, share, and retrieve prompts within seconds , making the entire process far more seamless. The new save feature allows users to add a title to each prompt , making rediscovery quick and easy. While more organisational and categorisation features are expected soon, I recommend saving your most valuable six to eight prompts  and using a structured naming convention to ensure efficiency. Example of a simple naming convention you may wish to adopt for consistency and ease of use Why does this matter? Efficiency, Quality, Collaboration, and Adoption. Efficiency:  Why start from scratch when you can access a curated prompt in seconds? Those who write good prompts will outperform others, but those who can access well-crafted prompts on demand will excel even further . Quality:  If a prompt works, there’s no need to reinvent the wheel—perhaps just refine it. Having saved, shareable prompts fosters consistency, improving output across teams and organizations. Collaboration:  A prompt shared is a problem halved. By sharing what works within teams, knowledge is preserved, even as people move on, ensuring everyone benefits from collective learning . Adoption:  Not everyone finds it intuitive or natural to use generative AI. A readily accessible prompt gallery lowers barriers to entry , encouraging more experimentation and boosting engagement with Copilot. What would make your top eight prompts? Whether you're persevering with your personal productivity or redesigning processes for departments, curating, saving, categorising, and refreshing your best prompts for easy use is a worthwhile exercise. Let me know in the comments what your core prompts centre on, and let’s keep advancing together. Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: Microsoft Community Hub (2024), OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat

Why is it that nearly 80% of us abandon our New Year's Resolutions (NYR) by February? A lack of joy, perhaps. And maybe an absence of novelty. While there are many techniques to help us stick to our promises, what if it's the nature of the promises themselves that are tripping us up? Health, finance, and relationships tend to be at the core of most of our NYRs, and more often than not, we attach targets or hard boundaries that make them nearly impossible to stick to. Well, not this year. After a short conversation with a close friend, I was given this gem of wisdom that made me rethink resolutions altogether: Make your New Year's Resolutions joyful, fun, and exciting - not restrictive. Joyful Resolutions Over Restrictive Rules The turning point this year is a shift of focus to the experience and journey over the outcome. But what might this look like? Here are a few that have been suggested to me so far (and feel free to share your own below): Pasta Shake-up : Mix up your meals by trying as many new and different pasta shapes as possible. Adventurous Ales : Explore different breweries and brews, collecting stamps on a Beer Passport as you go. Badminton Battles : Pick up a racket and have a go at different mini-games with novel rules and gameplay to create unpredictability. These are all about new experiences, and I'm already excited about the prospect of trying these three. How AI Can Be Recruited To Your Resolution Aid So where does generative AI come into this? One of my favorite uses of tools like Gemini, Copilot, or ChatGPT is to tap into their creative brainstorming skills. Here’s a prompt you could tweak and use to get some inspiration like the above examples: "You're a personal coach that specialises in the creation of fun and joyful New Year's Resolutions. I need you to help me brainstorm a number of ideas that are similar to . Present these in a bullet point list and give me your best five, prioritised by how likely I am to enjoy them and stick to them. Ask me any questions before you begin to understand me and what I might like." AI-Generated Resolution Examples Here are some of the examples I got when prompting ChatGPT with the examples I'd been given: Movie Mix-Up : Try a new film from a different genre/era each month, hosting friends or family. Cuisine Explorer : Cook a dish from a different country every month to experience new flavors. Artistic Adventures : Try different art forms, from pottery to watercolor painting. Let’s Refresh Our Resolutions Hopefully, you're encouraged to add a splash of joy into your resolutions for the year ahead. And if you're stuck, perhaps you're ready to give generative AI a spin to give you a bit of inspiration. Whether you're inspecting some new pale ales or battling it out in badminton, let’s make this the year you’ll actually stick to your resolutions, all with a little joy and help from AI! Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: OpenAI. (2025).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat

Why did the AI refuse to go caroling? It couldn’t find its festive algorithm. (ChatGPT 4.0, 2024) Not bad, right?! But let’s just say the rest of its top five “jokes” didn't make the cut. Anyway, it’s that magical time of year again, and what a year it has been! A mere twelve months ago, I hadn’t even heard of generative AI, let alone used it. Now, it has become my go-to tool for personal and professional tasks, transforming how I tackle my day-to-day. So, in the spirit of giving, here are three AI-powered prompt ideas to save you time and maybe even your sanity this festive season. Present Inspiration Long gone are the days of flipping through the Argos catalogue and punching in those seven-digit codes to see if that item  was still in stock. Why do I look back on those experiences fondly? Who knows—maybe it’s the nostalgia of the anticipation. But these days, as the years tick by, coming up with thoughtful gift ideas has become harder and harder. That was, of course, until ChatGPT came to the rescue. Try this: Act as my personal shopping assistant. We are looking to purchase a present for a mid-twenties male who is interested in Premiership Football, Online Gaming, and Ballroom Dancing. The budget for this present is between £20 and £30 and needs to be something that could be easily shipped or posted within the UK. I would like ten ideas presented in a table format with the item name, description, picture, rationale for suggestion, where to buy the cheapest, and with a link if possible. ( Note: See the full prompt template at the end of the article. ) Result: Food Preparation This year, I’ve been promoted from Sous Chef to Head Chef - much to my family’s amusement and my rising anxiety levels. Let’s face it: no one wants dry turkey or to need to carve a Brussel sprout. Thankfully, AI can help me get ahead of the game, from crafting a precise shopping list to orchestrating the perfect culinary timeline. Try these: Act as my Head Chef. We are looking to cook the best Christmas meal ever tasted and need to ensure our timings and actions are to perfection. We have two cooks with access to a standard oven, induction hob, microwave, steamer, warming draw and other standard kitchen accessories. They will be cooking for six people and there are three courses to the menu which include: Prawn Cocktail Salad, Turkey Dinner, Christmas Pudding. I have three requests that I would like your help with. Please let me know if you understand and when you’re ready for the first request. The first request is for your support in creating a shopping list for the three course meal separating ingredients out into where I would find them in the supermarket. The second request is for you to provide the list of ingredients purchased underneath each dish along with the expected cooking apparatus needed to make this dish. The third request is for you to suggest the appropriate preparation, cooking order, and timings to create this three course meal and assign actions between the two chefs (A and B). The plan is to serve the first course at 5pm so I need to understand when I need to start preparation. Result: Present Acknowledgments Ah, the tradition of thank-you letters—equal parts gratitude and hand cramps. As a kid, I dreaded the ache of drafting and rewriting these notes, especially with Tipp-Ex forbidden and errors met with tears. Over time, the dread waned, mostly because the letters grew fewer. Still, there’s something undeniably special about a well-crafted thank-you note, and AI can make the process faster without sacrificing sincerity. Try this: You are a grateful receiver of gifts and an exceptional writer. Please create a template to thank relatives and friends for specific presents they have given you. I want you to include what you plan to do with that gift and how grateful you are for their generosity. You should also hope that they’ve had a fantastic Christmas and wish them a happy New Year. Please create a draft thank you to each of these people, noting the gift they gave. £15 gift card (Uncle Tom) Toy train (Auntie Joan) Taylor Swift Vinyl (Cousin Travis) Result: Wrapping It Up Hopefully, these festive prompting ideas leave you full of inspiration, with time to spare and a Christmas dinner that’s remembered for all the right reasons. Whether it’s finding the perfect gift, nailing your holiday feast, or drafting heartfelt thank-you notes, AI is here to play Santa’s little helper this year. Now, merry prompting, you filthy animals! Prompt Templates Present Ideation Prompt: Act as my personal shopping assistant. We are looking to purchase a present for who is interested in . The budget for this present is between and needs to be . I would like ideas presented in a table format with the item name, description, picture, rationale for suggestion, where to buy the cheapest, and with a link if possible. Food Preparation Prompts: Act as my Head Chef. We are looking to cook the best Christmas meal ever tasted and need to ensure our timings and actions are to perfection. We have cooks with access to . They will be cooking for people and there are courses to the menu which include: . I have three requests that I would like your help with. Please let me know if you understand and when you’re ready for the first request. The first request is for your support in creating a shopping list for the course meal separating ingredients out into where I would find them in the supermarket. The second request is for you to provide the list of ingredients purchased underneath each dish along with the expected cooking apparatus needed to make this dish. The third request is for you to suggest the appropriate preparation, cooking order, and timings to create this course meal and assign actions between the chefs (). The plan is to serve the first course at 5pm so I need to understand when I need to start preparation. Present Acknowledgement Prompt: You are a grateful receiver of gifts and an exceptional writer. Please create a template to thank relatives and friends for specific presents they have given you. I want you to include what you plan to do with that gift and how grateful you are for their generosity. You should also hope that they’ve had a fantastic Christmas and wish them a happy New Year. Please create a draft thank you to each of these people, noting the gift they gave. - () - () - () Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2024).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: OpenAI. (2024).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat

After two refreshing weeks away from the hustle and bustle of consulting, it was time to put some of the AI learning I'd been delivering into practice. Many will be familiar with that heightened wave of anxiety that starts to build in the days or hours leading up to the return to work. Well for some unusual reason, that feeling wasn't quite there today. I believe this in part stems from my daily habit of using Generative AI and an eagerness to try out some use cases particularly relevant to the return from extended periods of leave. Armed with the knowledge that Microsoft 365 Copilot can really help from a summarisation standpoint, I knew I easily had three actions ready to deploy to make that transition back to work just a little bit smoother. But what awaited me after a fortnight away? It could've been worse. So what did I do next and how did it benefit me? Let's just say that what I did next has saved at least two hours already along with a whole heap of early wins.... Catch me up - Saved >30 minutes and prioritised tasks for the day and week ahead I was determined not to lose that blissful holiday feeling within moments, but seeing over 300 unread emails could have easily done the trick. Rather than spending at least 30 minutes trawling through countless emails and Teams chats, I called upon Microsoft 365 Copilot to bring me back up to speed in a flash. Using Copilot in Teams, I quickly asked: Catch me up on what should be on my radar from emails, chats, and messages from the last two weeks. Use bullet points to highlight any actions, and prioritise any actions in order of importance and deadlines. With this short prompt, it raced through the myriad of messages and made the mountain of communications easily digestible, catching me up on what I had missed. The important updates - prioritised. The noise - minimised. Not only did I avoid replying to something already resolved by my colleagues, I could quickly focus on the most pressing actions and prevent the feeling of overwhelm stopping me right in my tracks. Swapping holiday piña coladas for a GenAI-enabled work assistant turned out to be a surprisingly palatable trade... Summarise the actions - Saved >25 minutes and quickly understood the requirements Sometimes, I long for those office days where you could poke your head up like a meerkat and ask a colleague to catch you up on what you’d missed while on holiday. Meerkats aside, I didn't want to fumble my way through thread after thread trying to work out what was required of me on my return. So on a few email chains I clicked: And just like that, in about five seconds, Copilot had produced a series of concise bullet points. And with those bullet points I had saved at least five minutes per thread and had good insight into what the important details were and what I needed to do next. Getting on top of these things promptly really helped avoid the panicked rush of reading everything and potentially replying prematurely. Copilot read and contextualised the information I needed, freeing me up to channel my reading skills and energy into finishing that novel I’d started on the beach - later in the day, of course. Prepare for my meetings - Saved >20 minutes and led a positive meeting 9:30 am meeting, really?! It could've been worse - at least I had 30 minutes to prepare even if I did only require five, and most of that was just reviewing the summaries I'd gleaned just seconds ago. I typed in the following prompt: Prepare me for my upcoming meetings this week, providing any necessary context and references to allow me to contribute fully. Provide this information in sections for each meeting, keeping information concise and easily understandable. Being briefed and informed about the meetings’ background allowed me to waltz into each session with confidence and clarity on what needed to be achieved. There are few things better than a meeting that meets its intended objectives and has full contribution from those in attendance. Not only did Copilot’s preparation enable me to contribute fully, but it also gave me enough time to grab a cappuccino and briefly reminisce about doing the same last week - only in temperatures 20 degrees warmer. Overall, I easily saved an immediate hour or two this morning and over the course of the week, I suspect a whole lot more. But it's not just about the time saving, it's about keeping that refreshed feeling for as long as possible. If AI can make your transition back from holiday or time away a little smoother, why wouldn’t you give it a try? Give the three AI actions above a go to make returning to work from holiday or even the weekend just that little bit easier. How long could Copilot help you keep that post-holiday glow? Credits Author: Rob Anderton Brainstorming: OpenAI. (2024).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Editors: Rob Anderton and OpenAI. (2024).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat Images: Rob Anderton GIFs and OpenAI. (2024).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat

Unlocking the value of AI in architecture through a Father’s Day conversation, Formula 1, and shared observations of where AI can accelerate creativity and the confirmation of client requirements. If you had told me that Father’s Day morning would start with a Colombian coffee, an architectural journal, and a pot of berried muesli with greek yoghurt, I’d have thought we were playing an inverse game of two truths and a lie. Now I’m a muesli convert. Whilst at one point I had myself down for following in my father’s architectural footsteps, the knowledge that there was more to it than simply colouring in drawings of university campuses soon kiboshed that fantasy. But there we were, chatting over an article in the RIBA journal, about how AI is impacting the landscape of architecture services - a sort of first for blending my Dad’s profession and mine.  When talking about AI in my role, a few topics frequently surface. Loss of intellectual property and data privacy are certainly towards the top of that list. The article my Dad slid over the kitchen table was discussing how a renowned practice was looking at using AI for design, setting parameters to maintain their signature style whilst inspiring new concepts. What was interesting about this was that much of the AI conversation to date centred around productivity was now shifting to creative consistency, with particular focus on customer delivery. Many organisations have quickly acclimatised to the administrative easing afforded by such tools as Microsoft 365 Copilot, but few have yet to really tap into how these tools transform and relay value to the customer.    There I was, brew in one hand, article in the other, my eyes hooked on this fascinating visualisation. A beachside mansion in pearl white concrete curiously shaped to look like a classic acoustic guitar - my interest was piqued. On face value, you would have struggled to tell it was AI generated. On closer inspection, staircases leading to walls, the odd E-string too many, and even the musically unaware could spot some of these comical errors.   Still impressed by the overly strung building, my Dad’s curiosity centred on how this technology transformed text to image, and at what pace this could be achieved. What I hadn’t fully appreciated was the different techniques he had deployed in his line of business to accelerate design inspiration. He cited that one technique involved collating words and seeking synonyms around a topic, pooling the individual and collective experiences, memories and knowledge of architects in the practice. For example, designing a golf clubhouse could invoke words such as manicured, pristine, crisp, and immaculate. For me, I’d throw in sandy. The idea was that collating these words would provide the jumping-off point for possible designs and encompass all the emotions they wanted to evoke within the client. The evolution of that particular process led us both to think about how other applications of the technology may encourage architectural firms to consider bringing outsourced and previously laboursome tasks back in-house, saving both time and money.    Seeing is believing though so a few moments later, and with Chat GPT 4o open, I brought another of our shared passions into the mix - Formula 1. In a time that would have the best pit stop crew in awe, I’d drafted this prompt: “Create an image of a state-of-the-art property for Lewis Hamilton, that is three stories, by a beach and inspired by racing. There must be capacity for three F1 cars.” We got this response. Not bad right? I’m happy for you to forward this to Lewis if he’s in the market for some renovations, or a garage extension for a new Ferarri or two. The eagle-eyed amongst us may have noticed that the property featured well in excess of the three car parameter I’d given. Nevertheless, this brought us quickly onto the topic of hallucinations, or the fact that the output we get isn’t always in line with what we request. Not ideal in times where there is little room for error, and for maintaining professional integrity, it’s definitely recommended that we take a second look. For times of creativity and giving a client early visibility, having models that push the boundaries of possibility can make the odd hallucination a light bulb moment for new ideas. This thought reminded me of the Edison quote: “I have not failed. I've just found 10,000 ways that won't work.” With AI, we may not always get exactly what we expect. Yet experimentation and imperfect responses might just be what we need to think differently and more critically.   The next bit surprised me. I knew from an architect's perspective that being able to show a design from different angles could make all the difference between a client’s acceptance or rejection of a concept. However, from experience, prompting a model to make a change to an image previously created had always led to a completely different visualisation. Could this time be different? For example, I wanted an aerial view of our design so I prompted: “Could you show me this exact image but with five stories, a helipad and from an aerial view” Aha! Different, yes. Massively different, no. But we had created a moment. A moment where what my Dad and I did collided - AI meeting architecture. Whilst we both agreed that neither of these would be submitted directly to a client due to apparent inconsistencies, the speed in which we created these ideas was a game changer. Rapidly creating a mood board to meet or better understand what a client likes and dislikes not only would help to refine requirements but could also be key to winning that next bid or framework.   This was a first for me in creating a use case demonstration in the field of architecture. It highlighted that not only are there many different uses for AI within the field, but the way in which we think of deploying it should not solely be about employee productivity but an ability to better meet the needs of our clients in real-time.   What this experience reinforced in my mind was that applying AI to augment familiar day-to-day actions led to a quicker understanding of the technology and an increased appetite to continue experimenting. It indicated that tailored demonstrations could create exciting ‘aha’ moments, moderated by an appreciation that there is still a need to critique AI generated outputs. Importantly, it also spotlighted that I may need to seek further AI inspiration for breakfast suggestions to go along with my coffee… Credits Author: Rob Anderton Images: OpenAI. (2024).  ChatGPT 4o [Large language model].  https://chat.openai.com/chat