MAIVENS AI News and Community for Women

Cheyenne Dominguez

MAIVENS is a podcast for non-techy, everyday women who want to explore how AI can support them at work, at home, and in life—whether that means earning more, negotiating better, planning travel, improving wellness, or advancing in your career or creative pursuits. We offer real-life stories, practical tools, and a welcoming community to grow. womenai.substack.com

  1. Sep 18

    Could AI Kill Us All? 😨

    Hello M(AI)VENS, I planned to bring you 15 of ChatGPT’s newest features and enhancements this week. Then a 27-year-old AI researcher resigned from Anthropic, warned that AI could “kill us all by the end of the decade,” and his post attracted more than 170 million views. Suddenly, everyone was debating whether AI could destroy humanity. So, the ChatGPT update is coming next week. This story deserves our attention first, especially because September’s M(AI)VENS Book & Movie Club selection, The AI Doc: Or How I Became an Apocaloptimist, explores this very question. Here’s what happened… Last week, Jacob Coxon resigned from Anthropic and posted a stark warning on X: “The people building AI earnestly believe that it could kill us all by the end of the decade.” Coxon, who had trained advanced models at Anthropic and OpenAI, accused both companies of racing toward self-improving superintelligence and “gambling with our lives.” His post attracted more than 170 million views, and his decision to leave two months before his Anthropic equity vested gave the warning added weight. Other AI leaders soon joined him. Anthropic CEO Dario Amodei warned that swarms of AI agents could potentially take over the internet within six to twelve months without stronger safeguards. OpenAI CEO Sam Altman said companies need to give safety research and independent evaluation time to catch up. Their concern centers on recent incidents in which AI models acted beyond their instructions, found ways around safeguards and completed increasingly complex sequences of actions. As systems become more autonomous and capable of improving themselves, they fear human control could erode faster than our ability to protect it. A competing view emerged just as quickly. At the Politico Decoded summit, LinkedIn cofounder Reid Hoffman criticized the most catastrophic predictions as a kind of “Cassandra” performance. He argued that AI progress should continue because it could strengthen cybersecurity, biosecurity, medicine and economic growth. White House AI adviser David Sacks called the warnings part of a “fear-mongering playbook” and placed responsibility for product safety with the companies developing them. Nvidia CEO Jensen Huang offered a more measured version of the optimistic case at a gathering of AI leaders convened by King Charles in Scotland. He calls his position “responsible optimism”: acknowledge the risks, test carefully, hold back products that are not ready and continue developing the technology. It seems that all we do know is that experts do not agree. And then, there is a third perspective I have heard far less about, and it’s probably closest to where I personally land: and that is to follow the money. I take the safety concerns seriously. I also wonder how much the call for a coordinated slowdown reflects the extraordinary financial pressure behind this race. Based on all I’ve seen, OpenAI is still spending far more than it earns. Anthropic recently told investors that it had recorded positive adjusted operating income for two consecutive quarters, following years of heavy losses and enormous outside investment. Building and operating these models requires staggering amounts of money, computing power, land, energy and talent. The companies are also carrying the weight of investor expectations, ambitious valuations and a race in which slowing down alone could mean surrendering market share to a competitor. A coordinated slowdown could relieve some of that financial pressure. It could give revenue more time to catch up with spending, reassure investors and customers, and allow the largest AI companies to help shape the regulations that every company entering the field is likely to eventually have to follow. I have not seen evidence that money is driving these warnings, so I raise it as a question rather than a conclusion. Safety concerns and financial incentives can exist at the same time. I’m not here to convince you that either side is right. What I do want is for women to know about this story, understand the differing perspectives, familiarize themselves with the cast of characters on each side and, ultimately, decide for themselves. Understanding what AI systems can do, where they fail and what safeguards they require is part of becoming AI fluent. So, where do you land? Take our quick poll. 👇 I can’t wait to see the poll results! For a closer look at this debate, AP News provides an overview of what has unfolded, while The Guardian asked six experts to examine both the extinction warnings and the arguments against them. Before you go, mark your calendar for our September Book & Movie Club selection, The AI Doc, which feels especially fitting after this week’s debate about the future of AI. I hope you’ll join us Friday, September 25 at 12:00 pm eastern for a great discussion. Watch the movie trailer below. 💜 Cheyenne September Book & Movie Club 🎬 Our September selection is The AI Doc: Or How I Became an Apocaloptimist, a documentary from Academy Award-winning filmmaker Daniel Roher and co-director Charlie Tyrell. As Roher prepares to become a father, he sets out to understand the extraordinary possibilities of AI alongside the risks we cannot afford to ignore. I chose it because it reflects the complicated mix of excitement and concern that many of us are feeling right now. Watch the movie on your own then gather with M(AI)VENS on Friday, September 25, 2026, to discuss it together. The film is streaming on Netflix, Peacock and available to rent or purchase on Apple TV. Join us! 📍 If you can see this, you’re a premium member! Register for the Zoom meeting. You’ll receive a confirmation email with the details. It’s always okay to attend even if you didn’t read the book or finish the movie. This post has bonus content, including the Zoom event link, for paid members. Upgrade to get full access. Copyright © 2026 M(AI)VENS. All rights reserved. M(AI)VENS is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to M(AI)VENS at womenai.substack.com/subscribe

  2. Sep 10

    🛍️ How to Take AI Thrifting With You

    Hello M(AI)VENS, September has arrived, and while some people are shopping for an entirely new fall wardrobe, Second Hand September invites us to buy less, choose secondhand when we do shop, and find more possibilities in what we already own. For those of us who are excited about the opportunities AI is creating while also concerned about its environmental cost, this feels like a meaningful way to put the technology to work. We can use AI to help us consume more thoughtfully, extend the life of clothing and household items, rediscover things we already own, and make better decisions about what we bring home. Second Hand September encompasses both what we buy and how fully we use what we already have, which brings me to our free AI Wardrobe Stylist. If you’ve been following along, you know that our AI Wardrobe Stylist allows you to photograph pieces from your wardrobe, add them to a digital closet, and discover new outfits using clothes you already own. Here’s the backstory in case you missed it… When we launched the prototype, I went Live on Substack and showed everyone the first 16 pieces I personally photographed and uploaded while testing the app. One item was a pretty white Vineyard Vines summer dress which I casually mentioned I had thrifted. After the Live, a friend asked me where I like to go thrifting. The answer depends on where I am and how much time I have. I wish I had more time for it because every once in a while, I love walking into a thrift shop and really diving in. You never know what you’ll find. Some trips produce very little. But once in a while, hidden among dozens of lackluster items, you spot the piece that fits you perfectly and follows you home. That got me thinking about the ways AI could help us reduce the urge to always buy more. AI can help us take a second look at clothes already hanging in our closets, including the pieces we’ve forgotten about. And when we do go thrifting, it can help us investigate unfamiliar labels, assess quality and condition, compare prices, and decide if we’ve found treasure. First, shop your own closet If you’ve ever stood in front of a full closet and announced that you have nothing to wear, consider this your Second Hand September challenge. Start by photographing 10 pieces and adding them to the free M(AI)VENS AI Wardrobe Stylist. Include a useful mix of tops, bottoms, dresses, layers, and shoes so the AI Stylist has enough variety to begin creating combinations. Then choose something you haven’t worn in a while as your “foundation piece” and let the AI stylist show you new ways to wear it. Maybe it’s a jacket you always pair with the same pants, a dress you reserve for one kind of occasion, or a top you like but never quite know how to finish. As your digital closet grows from 10 pieces to 20, 30, and eventually 50 or more, the stylist can uncover increasingly interesting combinations from the wardrobe you already paid for. And if Second Hand September inspires you to visit a thrift or consignment shop, AI can help there, too. Use AI to inspect Thrift shopping asks us to make quick decisions about pieces with an unknown history. Something can look wonderful on the rack while hiding worn fabric, damaged seams, a broken zipper, or repairs that cost far more than the item is worth. When something catches your eye, take several photos and upload them to ChatGPT, Claude, or another AI tool with image capabilities. For clothing, photograph the entire piece as well as the fabric, stitching, seams, lining, buttons, zipper, hem, cuffs, collar, and any suspicious areas. Ask AI: * What signs of wear or damage can you see? * How would you assess the stitching, seams, and overall construction? * Does the fabric appear to be pilling, fading, stretching, or thinning? * Do you see evidence that this has been altered or repaired before? * Which areas should I inspect more closely before buying it? * Based on the photos, which problems appear fixable and which could be difficult to repair? If your version of the ChatGPT mobile app includes live video in Voice, tap the camera button and show ChatGPT the piece from different angles as you talk. You could ask it to guide you through an inspection while you examine the collar, seams, lining, closures, and areas that tend to show the most wear. Research the label Once you understand the item’s condition, turn your attention to the label. One of the fun parts of thrifting is encountering brands you have never heard of. A label may belong to a well-made independent designer, a discontinued department-store line, a mass-produced fast-fashion company, or a brand with a long and interesting history. Take clear photographs of the brand label, fabric tag, care tag, and country of manufacture. Then ask: * What can you tell me about this brand? * What is the brand known for, and how is its quality generally regarded? * Is this label still in use? * Can you estimate when this version of the label was used? * Where was this item made, and does that offer any useful information about its age or production? * What would a similar item from this brand likely have cost when it was new? This is where AI’s ability to search the web becomes especially helpful. It can investigate a label you have never seen, locate old catalogs or product listings, and help you understand whether you are holding an ordinary mass-produced item or something more interesting. Decide whether it belongs in your wardrobe An item can be well made, attractively priced, and still spend the next five years untouched in your closet. Before buying it, take a photo of the entire piece and ask AI to help you imagine how you would wear it: * Give me five different ways to style this piece. * How could I wear it casually? * How could I dress it up? * Which colors, shoes, and accessories would pair well with it? * Does it look current, classic, vintage, or dated? * What alterations could improve the fit or update the look? * Based on its design, how versatile is this likely to be? If the thrifted piece comes home with you, add it to your digital closet. The AI Wardrobe Stylist can help make sure your exciting find becomes something you wear rather than another piece waiting patiently in the back of your closet. Investigate a possible designer find Designer bags and accessories can be among the most exciting thrift-store discoveries. They also come with a different set of questions. Photograph the bag from every angle, including the logo, label, lining, stitching, hardware, zipper, serial number or date code, corners, handles, and bottom. Then ask: * Can you identify the possible brand, collection, style, and approximate age? * Do any visible details appear inconsistent with known authentic versions? * What additional photographs would be useful for investigating authenticity? * What did this style likely retail for when it was new? * Find comparable examples that have recently sold. What prices did they receive? * How much could the visible wear affect its resale value? * Would cleaning or professional restoration meaningfully improve its value? AI can help you gather evidence, research the bag’s history, and identify details that deserve closer attention, which is especially useful if you think you have stumbled upon a designer gem. Look beyond the clothing racks The same approach works with furniture, artwork, lamps, dishes, glassware, books, and other household finds. Start with photos of the entire object, then capture any maker’s marks, labels, signatures, joints, hardware, undersides, and damaged areas. The goal here is to understand what the object might be and what it would take to restore it. Ask: * What style and approximate era does this appear to be? * Can you identify this maker’s mark, signature, or label? * Does the construction suggest solid wood, veneer, particleboard, or another material? * Which details suggest quality craftsmanship? * What damage or deterioration can you see? * What type of cleaning, repair, refinishing, or reupholstering might it require? * Which parts of the restoration could reasonably be done at home, and which would likely require a professional? * What search terms would help me research this exact type of item? AI may not identify every mystery object from a photograph, but it can often give you better language for continuing your research. Knowing that you may be looking at a “mid-century bentwood side chair” rather than simply an “old wooden chair” can make an enormous difference when searching for gems. Could you flip it for a profit? For anyone who enjoys reselling thrifted finds, the important question is not simply what the item might sell for. AI can help you understand the likely restoration costs, the prices buyers are paying right now, potential shipping costs, and whether there will be enough profit left to justify the effort. Give AI photographs of the item, the asking price, its dimensions, any identifying information, and the repairs you believe it may need. Then ask: This item is priced at $___. Based on its visible condition, estimate what I would likely need to spend cleaning, repairing, or restoring it to a condition suitable for resale. Research comparable items that have recently sold and suggest a competitive resale price. Then account for likely selling fees, shipping or local delivery costs, and the time required to prepare and sell it. Does this appear to offer enough potential profit to be a worthwhile flip? That gives AI a genuine research and evaluation assignment. It can help estimate the investment required, compare recent sales, calculate the likely profit, and identify costs that might otherwise be easy to overlook. If the opportunity still looks promising, AI can help you choose the right marketplace, write a compelling description, create a title using the terms buyers are likely to search, and develop a list of photographs to include. Your Second Hand Se

  3. Aug 13

    🎧 Your AI Podcast Roundup: 12 Episodes Worth Adding to Your Queue

    Hello M(AI)VENS, Our Prompt Parties are becoming a real favorite! More than 500 people watched last week’s conversation about developing your own personal AI strategy. With that kind of response, you can expect more Prompt Parties ahead. And we’re already back this Friday August 14 with: AI & Healthier Habits, featuring Rachel Johnson. We’ll explore how AI can help us eat better, move more, improve our sleep, and follow through on the goals we set for ourselves. Everyone is welcome to watch live for free. Premium members have special access to the live chat and Q&A. 📅 And don’t forget our next Book & Movie Club meetup for premium members on Friday, Aug 28. We’re discussing I AM NOT A ROBOT by Joanna Stern. I’m looking forward to this discussion because it will give us a lot to laugh about. 🎙 Let’s Talk About Podcasts Podcasts have become one of my favorite ways to learn about AI. I can listen while I’m driving, walking the dogs or getting things done around the house, and I often finish an episode with an idea I want to try or a topic I want to explore further, or even an idea for a future edition of this newsletter. I put together a roundup of some podcast shows and specific episodes I’ve recently enjoyed and though you might find helpful. 💜 Full disclosure: the list starts with two podcasts where I personally had the pleasure of being a guest to talk about women using AI. One conversation focused on building confidence, community and opportunities, while the other explored simple ways small business owners can use ChatGPT. From there, I’m sharing ten more episodes and shows covering AI for business, leadership, visibility, entrepreneurship, ethics, and the latest news. Choose one that sounds most useful to you and add it to your queue. Not subscribed yet? Come join us. 💜 1. For building confidence, community and opportunities AI for the Rest of Us: Building Confidence, Community & OpportunitiesFemme Force Podcast with Rachel Paskevich Rachel and I talked about why I created M(AI)VENS and my own path into AI as someone without a technical background. We explored how women can become more confident using these tools through experimentation, shared learning and community. We also talked about the opportunities AI can create in our careers, businesses and professional lives. Try this after you listen: Identify one area where learning alongside other women would help you move forward. Invite a friend or colleague to experiment with an AI tool and compare what you learn. 2. For small business owners learning ChatGPT AI for Beginners: A Simple Guide on How to Use ChatGPT for Small Business with Cheyenne DominguezThe Freedom Method Podcast with Sophie Biggerstaff Sophie and I discussed approachable ways small business owners can begin using ChatGPT, including working through ideas, creating content and saving time on everyday tasks. I also shared more about how I’ve incorporated AI into my own work. Try this after you listen: Write down one recurring business task that takes up too much of your time. Ask ChatGPT or Claude to help you create a simpler process for completing it. 3. For the woman ready to use AI more confidently How Women Startup Founders Can Start Using AI Confidently to Grow Their BusinessDear FoundHer with Lindsay Pinchuk Lindsay interviews Dr. Nici Sweaney, founder of AI Her Way, about using AI as a thought partner, protecting client information and giving AI enough context to produce stronger work. The conversation is especially helpful for women who have tried ChatGPT and are ready to make it a more consistent part of their businesses. Try this after you listen: Create a separate AI chat for one business project and give it background about your goals, audience, voice and current challenges. 4. For leaders deciding where AI belongs How Leaders Can Use AI to Solve Real Business ProblemsHBR IdeaCast Journalist Josh Tyrangiel talks about the importance of identifying the business challenge first and then deciding how AI could help solve it. The conversation covers strategy, organizational change and the human expertise needed to implement AI successfully. Try this after you listen: Choose one specific problem affecting your organization and describe it in a single sentence. Use that sentence to begin a conversation with AI about possible solutions. 5. For getting better work from AI Why Your AI Output Is Generic (And the Brief That Fixes It)The Strategic Entrepreneur with Cindy Gordon Cindy explains how to give AI a complete assignment. She presents four roles AI can play in a business: researcher, editor, project manager and analyst. Her briefing framework can help you move beyond vague prompts and receive work that reflects your needs. Try this after you listen: Take a recent prompt and add the intended audience, desired outcome, relevant background and preferred format. Compare the new response with the first one. 6. Using AI for PR How Female Entrepreneurs Can Use AI for PR Without Hiring an Expensive PR FirmCrush the Rush with Holly Haynes and Gloria Chou PR strategist Gloria Chou shares ways entrepreneurs can use AI to develop media angles, research opportunities and create stronger pitches. She and Holly also discuss how expert quotes, podcast appearances and media coverage can help people and AI search tools recognize your authority. Try this after you listen: Ask AI to identify five timely story angles connected to your experience, business or area of expertise. 7. Building a system with partnerships and speaking opportunities My Monthly PR Process: What I Actually Do Every Month to Stay Visible Without Social MediaCrush the Rush with Holly Haynes This companion episode brings together strategic partnerships, podcast appearances, community speaking, email and AI search. Holly explains how a manageable monthly process can help new people discover your work and how relationships can support long-term business growth. Try this after you listen: Make a list of three people, organizations or communities with audiences related to yours. Consider one useful collaboration you could propose to each. 8. For entrepreneurs What Is AI Actually Going to Look Like in 18 Months?She Means Business with Carrie Green Carrie shares how she’s using AI inside her business, including building an AI resource based on her own frameworks and knowledge. She also considers how entrepreneurs may incorporate AI into their offers as the tools continue to develop. Try this after you listen: Think about the knowledge, process or framework you’ve developed through your own experience. Ask AI to help you outline ways it could become a resource for your clients or community. 9. For building wealth with AI Female Entrepreneurs and the AI Wealth Gap: Why Midlife Businesswomen Can’t Sit This One OutThe Midlife Comeback Club This episode explores why midlife women may be especially exposed to AI-driven changes at work while remaining underrepresented in AI adoption. The host draws on her experience as an independent musician to explain how learning new skills and owning her work allowed her to build long-term wealth. She sees a similar opportunity with AI and encourages women to create their own systems, retain more of the value they produce and begin building now. Try this after you listen: Choose one part of your expertise that you could turn into a repeatable AI-assisted system, resource or offer. 10. For AI’s impact on the world Good RobotUnexplainable from Vox, four-part series This four-part series examines the contrast between AI’s potential dangers and its power to improve lives and address global challenges. Through conversations with researchers, ethicists and other influential voices, it offers a thoughtful look at the decisions being made now and the kind of future they could create. I must add, this series is especially well produced, using interviews, storytelling and immersive sound to bring the ideas and people behind AI to life. It feels like an audio documentary. Try this after you listen: Consider which potential use of AI you believe could do the most good, what safeguards would need to accompany it, and how you might advocate for those safeguards. 11. For keeping up with AI news The Artificial Intelligence ShowHosted by Paul Roetzer and Mike Kaput This is one of the podcasts I listen to regularly to keep up with AI news. Each week, Paul and Mike break down major news announcements, research, tools and industry developments, then explain what they could mean for businesses and professionals. Since AI news moves so quickly, start with the most recent episode in the feed. Try this after you listen: Choose one development from the episode and dive deeper into how it could affect your specific industry, organization or work during the next year. 12. For understanding AI agents AI Agents in 2026 Explained: What They Are and When You Should Use ThemEveryday AI with Jordan Wilson AI agents can plan and complete a series of steps toward a goal, sometimes using other tools along the way. Jordan explains how agents differ from chatbots and traditional automation, where they may be useful and what businesses should consider before giving them access to important systems. Try this after you listen: Identify a multi-step task you complete regularly. Map the steps and decide which ones require your judgment and which could eventually be handled by AI. I hope this list helps you find a conversation that meets you wherever you are in your AI journey. Save this edition, add a few episodes to your queue and send it to a girlfriend who might enjoy listening along with you. If you have an AI podcast or episode you love, please share it in the comments. I’m always looking for shows to recommend, and something good to listen to during my next drive or dog walk. 💜 Cheyenne P.S. If you’re looking for a podcast guest, I especially enjoy talking about how wom

  4. Jul 16

    👗 I Built an AI Wardrobe Stylist. Try It Free.

    Hello M(AI)VENS, A year ago, if you told me to build my own AI-powered wardrobe stylist with a few prompts and two free AI tools, I would have laughed. That’s because I would’ve assumed I needed a tech brain, a software engineer, startup funding, and months of development work to pull something like that off. But recently I actually built one using ChatGPT and a free AI app-building platform called Lovable. I published the working prototype and linked it below so M(AI)VENS readers can try it too. 😊 And the entire experience completely shifted the way I think about what non-techy women can create with AI without having much experience. This personal project was inspired by my friend Lynn on Instagram. She had been doing a thoughtful 30-day series focused on wearing and restyling pieces already in her closet instead of buying new things. Every day, for 30 days in a row, she’d remix outfits using items she already owned, and I found myself paying much closer attention to my own closet because of it. That got me thinking: what if AI could help me maximize my wardrobe and figure out what to wear using the pieces I already own? Join a growing community of women learning how to leverage AI at work and at home. You don’t need permission. You need a starting point. So I opened ChatGPT and started describing the idea. I explained that I wanted a digital closet where I could upload photos of my clothing items, organize them into categories, and then select a piece I wanted to wear and click something like “Style Me” to generate outfit recommendations using the rest of my closet. ChatGPT turned my idea into prompts I could copy and paste directly into Lovable.dev, which builds apps from written instructions. That was basically the workflow: describe idea → generate prompt → paste into Lovable → test → refine. And the wild part is I think this entire project only took about five or six prompts total. The first few prompts got the foundation built surprisingly quickly. Then I ran out of free Lovable credits and had to wait until the next day to continue refining the styling experience. So technically the project stretched across two days, but mostly because I hit the free usage limit. Here’s what I did and how you can use it… Prompt #1 First, I explained (in a prompt) to ChatGPT what I wanted to build and asked it to provide me with a prompt that I could use in Lovable. Yes, I prompted for a prompt. Stay with me. Thanks to ChatGPT, the prompt I pasted into my free account at Lovable.dev pretty clearly described what I was looking to build. Build a polished, mobile-friendly web app called M(AI)VENS Closet Lab. It helps users create a digital wardrobe and generate outfit ideas. Users can create an account, upload clothing photos, categorize each item as top, bottom, dress, jumpsuit, jacket, or shoes, add tags for color, season, occasion, formality, travel-friendly, and confidence piece, view their closet in a visual gallery, select multiple items, and ask an AI stylist to create outfit combinations using only the selected items. The design should feel elegant, feminine, modern, and easy for non-technical women to use. Wow! The framework was already in place with just one prompt. 📸 Then I got to work photographing and uploading 16 pieces of my wardrobe. I pulled a variety of dresses, jackets, shoes, pants, and blouses and took photos of each, making sure I had decent natural lighting. Once the photos were completed, I uploaded each item into the app and categorized it. See image below. Once I had a variety of items uploaded to the digital closet, it was time to test it. I selected my hot pink wide-leg pants as my “anchor” piece and asked the AI app to “Style Me” with outfit suggestions. Unfortunately, the “Style Me” feature returned an error message. 😤 I was bummed and figured my my idea was too complicated. But since I hadn’t really invested much time at this point, I decided to give it a bit more effort. 😁 Prompt #2 The ‘Style Me’ feature initially opens correctly, but generating outfits returns an error after submission. Please fix. And voila! It was fixed. The closet grid was clean, the uploaded images displayed beautifully, and the categories and tags worked. The interface already felt surprisingly usable. That was the first moment where I thought: wait a second… this is becoming real. Next, I realized I had wrongly categorized one of the clothing items when I originally uploaded it. But there was no option to edit. So, I worked on a prompt to enable the ability to edit wardrobe items. Prompt #3 I need the ability to edit a piece after it’s already been added to the closet. That worked. The response was Lovable added an Edit button (a little pencil icon) on each closet clothing tile which opens a dialog to update category, name, tags, formality, and the travel/confidence toggles. Is this thing working? Unfortunately, the ‘Style Me’ feature, which was the main functionality I wanted, still wasn’t working the way I had hoped. The problem? When I selected a clothing item as an anchor piece, the system wasn’t bringing back outfit suggestions. And that was the whole reason I wanted this digital closet. So, I explained the problem to ChatGPT and asked it to give me a prompt that I could paste into Lovable. So, prompt #4 was key and ChatGPT helped me frame it perfectly. Prompt #4 Update the “Style Me” feature so it creates complete outfit recommendations. When the user selects 1 or more pieces, treat those as anchor pieces. Then search the user’s full closet and recommend complete outfits using the selected anchor item(s) plus other compatible pieces from the closet. If the selected item is a top, recommend bottoms, shoes, and optional jacket. If it is a bottom, recommend tops, shoes, and optional jacket. If it is a dress or jumpsuit, recommend shoes and optional jacket. Return 3 outfit options when possible. Each outfit card should include: outfit name, occasion, selected pieces used, additional closet pieces added, and a short styling note. Do not say ‘no outfit possible’ just because only one item is selected. The Result 👠 The clothing item I selected became the “anchor item,” and the AI would then pull complementary pieces from the rest of the digital closet to suggest several complete looks. It was working! Now when I selected those same hot pink wide-leg pants, the app offered three (3) different ways to style them, using the images of my clothing I had uploaded. * The first outfit suggestion was called “pink power suit” which was to pair the hot pink pants with the matching suit jacket, a pink blouse, and black heels. * The second was called “chic & playful” which paired the hot pink pants with a black & white long sleeve blouse and loafers. * The third suggestion was called “modern classic” and paired the pants with a white peplum blouse, black heels, and my light denim jacket. The app generated multiple outfit combinations pulled directly from my uploaded wardrobe photos. Not only that, it explained the styling logic behind each look, including the occasion, silhouette balance, layering suggestions, and ways to dress pieces up or down. At one point I literally sat there staring at my screen thinking:wait… I built this? 👗 This isn’t really about fashion I’m excited to upload photos of my full wardrobe to explore all the different ensembles I can create using what I already own. But, I share all of this with you not really for the fashion (although that’s fun). It’s about the fact that AI is dramatically lowering the barrier between having an idea and creating something tangible. And I think that’s the story here. I’m sure you have ideas sitting in notebooks: business ideas, workflow ideas, community ideas, creative projects, organizational systems, little frustrations in everyday life they wished someone would solve. The leap between “idea” and “build” used to feel enormous. You needed technical expertise, developers, funding, or permission from someone who understood software. That gap is shrinking very quickly. What surprised me most during this experiment was how fast the idea became visual and interactive. Within an hour, I wasn’t imagining the app anymore. I was clicking through it, testing it, refining it, and watching it improve in real time. And maybe that’s what feels most exciting about this moment in AI. I didn’t need to understand coding language to move this idea forward. I mostly needed curiosity, experimentation, and a willingness to keep refining the prompts. The whole experience also made me think differently about AI itself. A lot of AI conversations still center around productivity, automation, and efficiency. But some of the most interesting AI use cases may end up being much more personal: organizing our homes, planning travel, building custom tools for our businesses, managing routines, designing systems around our real lives, or yes… finally figuring out what to wear with the hot pink pants in my closet. I can already see so many practical uses for my new digital AI closet stylist: * conference packing * capsule wardrobes * shopping my own closet before buying more * travel outfit planning * styling around one statement piece * or reducing the mental load of getting dressed every morning And the craziest part? This entire experiment was free. No developer. No design team. No coding bootcamp. Just an idea, a handful of prompts, some uploaded clothing photos, and a willingness to experiment. Experiences like this are making me think the next wave of AI adoption may look much more personal and creative than that. Women building tools for their own lives, their own workflows, their own businesses, their own communities, and their own ideas. Give it a Spin! 📱 I published the free prototype of the M(AI)VENS AI Wardrobe Stylist so readers can

About

MAIVENS is a podcast for non-techy, everyday women who want to explore how AI can support them at work, at home, and in life—whether that means earning more, negotiating better, planning travel, improving wellness, or advancing in your career or creative pursuits. We offer real-life stories, practical tools, and a welcoming community to grow. womenai.substack.com