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If you’re anything like most teams right now, your calendar looks less like a plan for the week and more like a losing game of Tetris. Endless recurring invites. No clear agendas. Back-to-back meetings being the default. Context switching every hour. And an ever-growing list of names on each call because nobody wants to be the one who misses out. Sound familiar? It’s easy to think that AI tools like Microsoft Copilot will fix all this. That somehow, magically, the same culture that got us into this mess will get better because a smart assistant can summarise, schedule and “catch you up.” But here’s the uncomfortable truth: AI can’t solve for bad meeting culture. At best it’ll just make them more efficient. And that’s not the same as better. The real problem: we stopped asking why I've never heard anyone asking or pining for more meetings. Most of us barely have five minutes to come up for air these days. As a new joiner to a new firm, this is not me just now (fortunately, and so far by intention) but I have worked in many teams where meetings evolve and multiply and before you know it, you're back-to-back all day, every day. But how does it come about? From my experience, someone sets up a weekly check-in “just for now”, another person adds a daily stand-up to “keep everyone aligned”, and before you know it, you’re five layers deep in catch-ups about the next catch-up. The problem isn’t necessarily the number of meetings but it’s the lack of intention behind them. We've forgotten to ask: Does this need to be a meeting at all? If it does, do I really need to be there? And if I am there, what do I need to know to contribute well? Nobody including AI will ask these questions for you. For now, you still have to decide where your time goes. But once you’ve made those decisions, AI can  help you make the meetings you keep far more meaningful. Using AI to make the meetings you do have… actually useful If you’ve decided a meeting is the right way forward, make it worth everyone’s time. Here are three Copilot prompts to help. 1. Creating a clear agenda “Create a focused meeting agenda for [meeting title] based on recent emails, chat threads, and documents. Summarise the main discussion points, objectives, and decisions needed. Keep it to no more than three topics and suggest pre-reads if relevant.” A well-defined agenda is more than an admin task, it’s an inclusive strategy that helps everyone succeed and get the most out of the meeting. It ensures everyone knows why they're there, what success looks like, and what they'll leave with. Providing meeting agendas in advance helps individuals prepare, manage anxiety, and participate more effectively. 2. Catching up on pre-reads “Summarise the key points from the pre-read materials for [meeting name]. Highlight any recommendations, risks, or open questions I should be aware of before attending.” No one likes spending the first fifteen minutes of a meeting waiting for everyone to “get up to speed.” Let Copilot do some of the legwork so you walk in prepared and ready to contribute, ask questions and not just observe. 3. Checking whether you should even attend “For the meetings in my calendar this week, identify where I have a clear role (decision-maker, contributor, or observer). Flag any meetings where my role is unclear or optional so I can consider declining.” This one’s my favourite. It puts you back in control. Because the truth is, being invited doesn’t always mean being needed. If you're not clear why you've been invited, the fear of missing out should apply only to the work you won't be doing by attending and not the promise of the unknown. Meetings aren’t the enemy. Mindlessness is. AI can summarise, schedule and support. But it can’t give you back the time you waste saying yes to things you didn’t need to attend in the first place. And you don't need to start afresh in a new firm to make this a reality, you just need to start asking the right questions and empowering your colleagues and team to do the same. So before you reach for Copilot to “make meetings more efficient”, ask yourself: Does this actually need to be a meeting? If it does, do I need to be on it? And if I do, what do I need to know to make it count? AI will make it easier to do meetings. Only you can decide if they’re worth doing. References Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 5 [Large language model].  https://chat.openai.com/chat Images: Google Gemini 2.5 Flash. (2025). [Large language model]. https://gemini.google.com/

I remember when language learning was fun, fast and free. Now, there's a moment every Duolingo learner dreads. You find your seat on the train or bus, keep-cup in hand, ready to knock out a quick lesson. You open the app and select 'can't speak now' to respect the quiet carriage or embarrassment you may feel from your northern pronunciation of French (speaking for myself here)! You're halfway through learning how to say "the giraffe drank a lot of orange juice", a common expression I'm led to believe, and your progress is frozen with a cheery slap in the face: "You ran out of energy". (Splurts out coffee) Energy. Not hearts. Not a polite "try again tomorrow" reminder. Energy. I'm caffeined up, raring to go but that green owl has other ideas... It's like signing up to a marathon (which I've sillily done for April next year) and discovering the organisers have replaced the water stations with toll booths. You don't get to finish unless you're willing to add another subscription to your endless list of monthly subscriptions. And you don't even get the option to watch a Temu ad for a free toolbox with 420 screwdrivers you didn't even realise you needed. And here's the thing, it's not just frustrating, it's poor design and poor user expectation management. Nobody enjoys starting something they used to complete fairly smoothly, only to be held ransom halfway through. Whilst appreciating the improvement of not punishing mistakes (as per the old ways), the answer isn't to disincentivise progress or punish getting things right. Here are three reasons why this change feels like poor design and poor expectation management: If you don't have enough 'energy' to complete the lesson you are embarking upon, the option to spend gems or subscribe should appear upfront so the learner doesn't feel like their earnt XP is up for ransom If you get different levels of energy for getting an answer correct, you're adding confusion that distracts from the learning experience . I've spent more time questioning why one correct answer is worth 2 energy points and another one is worth 4 than I have on the lesson itself If you are going to change the learning mechanics so drastically, more communication and engagement are needed to support understanding of the changes than a once and done. As there is such a strong and loyal community of users (I know from the countless friendship streaks I cannot afford to break) who have been used to the heart mechanism from the beginning, reminders of what this change means for me would have helped me buy into what currently feels like a user-limiting experience. As someone who has a big thing for culture, values and mission, I was sad to read that Duolingo's mission has been subtly watered down. Its mission used to promise that learning languages would be "free forever". And whilst you can argue parts are still free (and that they do need to make money), for meaningful language learning, you're heavily forced into one of their paying models. That original promise the owl made allowed you to stomach the sad and changeable face of the app icon and the incessant nudges to not let your streak fade. Not anymore. Whilst "free forever" has morphed into "universally accessible" (a principle i'm 100% behind, meaning barriers are removed so that everyone can achieve the same results independently), the new experience isn't universally enjoyable. The reality is that instead of having an owl cheer you on, it's shaking you down. The irony of all this is that the new approach risks breaking the very habit Duolingo has been famous for creating. The streak mechanic worked because it rewarded small, consistent, daily wins. We showed up, we learnt a bit more, we reinforced our learning, and we left feeling proud of ourselves. But here's the harsh truth. The first time I saw the "out of energy" screen, I didn't feel motivated to pay to continue, I felt done. It was the first time I seriously considered letting my streak die. Not because I couldn't be bothered, but because the app told me I wasn't allowed to finish. That's no longer encouraged learning, that's gatekeeping and feels somewhat contrary to the mission of universally accessible. So in short, I'll keep practising my French but I'm in the market for a less passive-aggressive owl. One that helps me wrestle with tricky verbs, not confusing energy meters. References Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 5 [Large language model].  https://chat.openai.com/chat Images: OpenAI. (2025).  ChatGPT 5 [Large language model].  https://chat.openai.com/chat

Sometimes career development feels like trying to navigate without a map. You think you’re heading in a straight line, only to find the path bends, loops, and squiggles its way in unexpected directions. That’s why I’ve always connected with Helen Tupper and Sarah Ellis’s Squiggly Careers  approach. Careers aren’t linear, and that’s perfectly okay. So when I spotted their latest Squiggly Careers Skills Sprint × AI , I jumped straight in. The timing couldn’t have been better: a week off between jobs, a fascination with AI, and a desire to keep learning. The stars aligned (quite literally), as I’d soon discover in the form of a strengths constellation. Let's begin our strength discovery... The first sprint focused on strengths: the things that give you energy, help you do your best, and shape what you’re known for. To help uncover these, the sprint suggested a 10-minute exercise using AI. This was the prompt Helen and Sarah shared, along with a choice of free generative AI tools (Claude, ChatGPT or Copilot): Act as a squiggly career coach. Be high care and high challenge in your approach. Ask me 10 questions, one at a time, to help me explore what my strengths might be. At the end, use my answers to create a summary of what my top strengths could be. The prompt turned Claude (my tool of choice for creative copy) into a “Squiggly Career Strengths Coach.” I thought it would be good to try a different tool as a regular user of both Copilot and ChatGPT. The idea was simple: Claude asked me 10 structured questions, one at a time, then used my answers to generate a personalised summary of my strengths. What struck me wasn’t just the end result but the quality of the questions themselves and how they built from one another. The power of good questions Claude didn’t just fire questions at me. It nudged me to go deeper, to share more detail, and to reflect on things I might otherwise skim over. The style felt surprisingly warm and personal, and at times almost therapeutic. Whether that’s down to the orange squiggle icon or the tone of its responses, it felt more like a conversation than filling out a form. Here are a few of the questions that stood out (lightly adapted from my own session to keep them broadly useful to you): Flow moments:  Think about a time when you were completely absorbed in what you were doing, so much so that you lost track of time. What exactly were you doing, and why did it engage you so much? Energy drainers:  On the flip side, what types of work situations leave you feeling drained or frustrated? What specifically about them has that effect? Problem-solving style:  When you face something complex with lots of moving parts, how do you naturally go about breaking it down? Learning curve:  When you tackle something completely new, what helps you stick with it through the steep learning phase? Future identity:  If in five years people came to you for one particular capability or expertise, what would you secretly hope it was? Each question acted like a mirror, reflecting not just what I do but why I do it, and how it connects to the energy I gain or lose in my daily life and at work. My constellation At the end, Claude pulled my answers together into a strengths constellation. Not only did I get a neat HTML visualisation that mapped out my core strengths, but I was also able to use natural language to tailor the constellation to my own style and colour palette. That aside, the constellation felt accurate but also aspirational, showing me not just who I am today but who I could lean into becoming. Why AI works well here There’s something powerful about using AI in this context. The speed, supportive tone, and accessible interface felt less judgemental than a human conversation, and the framing of Claude’s questions encouraged honesty and reflection. Claude also replayed me back to myself. By presenting my own words in new ways, it pushed me to see patterns and insights I might have otherwise missed. It also reminded me of some of the work I’ve been doing recently with Copilot Studio, where I’ve been building an agent that assesses an individual’s current skills and competencies, maps them against their roles, and predicts future skill gaps based on the impact of AI. The reliance on good data inputs is the same. Whether it’s my Copilot agent or Claude in this exercise, better questions lead to more valuable insights. My takeaway from Day 1 Give it a go. Even if you’re sceptical, you’ll either learn something new about yourself or, at the very least, learn something about how AI can be used in more personal and reflective ways. If you do try it, please feel free to share your constellation and see whether it shifts how you approach your work, your energy, and the skills you lean into. This is just Day 1 of the sprint, and I hope to share more reflections as the week goes on. If you’d like to join in yourself, you can sign up via Amazing If  and download the Skills Sprint × AI guide . Credits Author: Rob Anderton Editorial: Rob Anderton / OpenAI. (2025).  ChatGPT 5 [Large language model].  https://chat.openai.com/chat Images: Claude (2025). Sonnet 4 [Large language model] https://claude.ai/ / Midjourney (2025). V7 [Image generation model] https://www.midjourney.com/  / OpenAI. (2025).  ChatGPT 5 [Large language model].  https://chat.openai.com/chat References Inspiration and sign-up info: AmazingIf: https://www.amazingif.com/ Sprint Day 1 video: https://www.youtube.com/watch?v=XTD26WCqztA

Just a quick peek, just a little look… those are the voices I’m hearing on the train, not to the office, but to the airport. For some reason, I’m fighting the urge to check in, to see what’s happening while I’m away. It’s unlikely much has changed between 7pm when I put my laptop down and 7am when I found myself rattling down the underground tracks. So why am I so tempted to read emails, to continue supporting, to not switch off? The easy answer is that we’re always connected. My personal phone is also my work phone, so I’m essentially always reachable, despite disabling notifications and never having a separate number. Because I can , I feel like I should . For some, the answer lies in the behaviours of teammates or managers. But I’ve read studies showing more of us are now checking emails on Sundays, working weekends, unable to apply the once-ubiquitous 9–5. Our hours wouldn’t fit neatly into a Dolly Parton remix anymore. The harder answer, and the one that rings true for me sometimes is a slight fear. Fear of falling behind. Fear that by taking time out, I won’t catch up, or won’t be able to hit the ground running on my return. But it’s counterproductive. There’s no rest, no break, nothing to come back with, if you don’t allow yourself to step away. And stepping away is powerful for so many reasons. It gives you time to rest, to reset, and to support your wellbeing. It also gives others a chance to step up, to realise how much they depend on you and the value you bring. Of course, not everyone has the luxury of being completely switched off. In fact, I suspect that’s a myth. But there are still steps you can take to detach more fully from work when you’re not supposed to be working. Here are a few I’ve found helpful: 1. Add your out-of-office dates to your email signature and MS Teams notes so your team knows leave is coming. 2. Before going on leave, create a handover (if possible) with what needs attention and where you’ve left open work. 3. Disable notifications and work profiles on personal devices, or limit yourself to one or two short check-in windows. Being able to move from work to rest shouldn’t feel like a battle, or like something we don’t deserve. Yet since the pandemic, it increasingly feels like a luxury. I’ve tried to put some of these tips into practice, and they’ve helped. Let me know what’s worked for you, and if you ever hear those same voices tempting you to “just take a quick look.”

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