『Discussing Stupid: A byte-sized podcast on stupid UX』のカバーアート

Discussing Stupid: A byte-sized podcast on stupid UX

Discussing Stupid: A byte-sized podcast on stupid UX

著者： High Monkey
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Discussing Stupid returns to the airwaves to transform digital facepalms into teachable moments—all in the time it takes to enjoy your coffee break! Sponsored by High Monkey, this podcast dives into ‘stupid’ practices across websites and Microsoft collaboration tools, among other digital realms. Our "byte-sized" bi-weekly episodes are packed with expert insights and a healthy dose of humor. Discussions focus on five key areas: Business Process & Collaboration, UX/IA, Inclusive Design, Content & Search, and Performance & SEO. Join us and let’s start making the digital world a bit less stupid, one episode at a time. Visit our website at https://www.discussingstupid.com© 2025 Discussing Stupid: A byte-sized podcast on stupid UX マーケティング マーケティング・セールス 経済学
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  • S3E18 - Intentional AI: Series takeaways - the real reason AI isn't working for you

    S3E18 - Intentional AI: Series takeaways - the real reason AI isn't working for you
    2026/06/16
    Season 3 of the Intentional AI series started with a simple premise: AI is a powerful tool, but the way it gets marketed and the way most people actually use it are two very different things. Eighteen episodes later, that premise has held up.In this finale, Virgil and Cole take stock of what the season actually taught them. Not the hype, not the headlines - what they observed firsthand through testing, building, and paying attention to how AI performs when real work is on the line.A big part of this episode centers on a real-world example: Virgil's experience building an internal business application using an AI low-code tool called Zite. What made it work wasn't the tool. It was the month of planning that happened before a single line of code was written - database diagrams, stakeholder conversations, process mapping, all of it done before AI touched anything. The app ended up replacing four SaaS systems. That kind of result doesn't come from letting AI lead. It comes from knowing exactly what you need before you ask AI for help.The flip side of that shows up in a small but telling moment: a teenager at the gym using AI to generate a workout plan. It probably gave him something reasonable. But here's the problem - he won't know whether it worked for three to six months, and he likely has no framework to evaluate it either way. That's the same trap organizations fall into when they hand big process decisions to AI without the expertise to judge the output.Cole frames it simply: AI is a mirror. Whatever you bring to it, it reflects back. Strong process knowledge, clear goals, and domain expertise get amplified. Gaps and blind spots get amplified too. The tool doesn't know the difference.Virgil runs through where AI held up the most across the season - SEO, analytics, research, coding, wireframes - and where it didn't, including original content, image generation, video, and design. Eighteen episodes in, the picture is a lot clearer than when we started.Previously in the Intentional AI series:Episode 1: Intentional AI and the Content LifecycleEpisode 2: Maximizing AI for Research and AnalysisEpisode 3: Smarter Content Creation with AIEpisode 4: The role of AI in content managementEpisode 5: How much can you trust AI for accessibilityEpisode 6: You’re asking AI to solve the wrong problems for SEO, GEO, and AEOEpisode 7: Why AI can make your content personalization worseEpisode 8: The real value of AI wireframes is NOT the wireframesEpisode 9: Just because AI can create images doesn't mean you should use themEpisode 10: The Super Bowl didn't sell AI, it exposed itEpisode 11: AI video rewards planning, not your ideasEpisode 12: AI might struggle with creativity, but coding isn't creativeEpisode 13.1: What the rise of conversational search means for your websiteEpisode 14: AI agents are only as good as your workflowEpisode 15: AI can't fix your social media if you have nothing to sayEpisode 16: The most important operation in analytics - understanding your "why?"Episode 17: How to get better results from AI promptsThat's a wrap on Season 3. Thanks for coming along for the ride - see you in Season 4!For more conversations about AI, design, and digital strategy, visit https://www.highmonkey.com/podcast and subscribe on your favorite podcast platform.(0:00) - Intro(1:15) - Season 3 milestone: 2,000 listeners(2:06) - Why we started this series(3:09) - The AI backlash: justified or not?(6:33) - Virgil's AI-built internal app(7:29) - AI is only as powerful as the person using it(9:56) - AI at the gym!(13:00) - The workout is a microcosm of how AI gets misused(15:24) - AI's real value: saving time(16:42) - Plan first, build second(21:04) - Security: the thing low-code builders miss(24:59) - AI is a mirror: it reflects what you bring to it(25:32) - Where we would use AI(28:07) - Cheers to Season 3 + what's next(28:48) - OutroSubscribe for email updates on our website:https://www.discussingstupid.com/Watch us on YouTube:https://www.youtube.com/@discussingstupidListen on Apple Podcasts, Spotify, or Soundcloud:https://podcasts.apple.com/us/podcast/discussing-stupid-a-byte-sized-podcast-on-stupid-ux/id1428145024https://open.spotify.com/show/0c47grVFmXk1cco63QioHp?si=87dbb37a4ca441c0https://soundcloud.com/discussing-stupidCheck Us Out on Socials:https://www.linkedin.com/company/discussing-stupidhttps://www.instagram.com/discussingstupid/https://www.facebook.com/discussingstupidhttps://x.com/DiscussStupid
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    30 分
  • S3E17 - Intentional AI: How to get better results from AI prompts

    S3E17 - Intentional AI: How to get better results from AI prompts
    2026/06/02
    Near the end of Season 3, Virgil and Cole sit down to look back at the prompts used throughout the Intentional AI series, what worked, what did not, and what that gap says about how most people approach AI.The conversation starts with a simple premise: the prompt itself is not really the point. The words you type are just the output of a more important process, which is knowing clearly what you want before you start. When that clarity is missing, the prompt cannot compensate. When it is there, even a basic prompt tends to work.One of the more durable takeaways from across the season is that asking AI what to ask it is a legitimate strategy, not a workaround. When you do not have a clear framework for your task, AI can actually help you build one. Ask it what information it needs to do the thing you want done. From wireframes to strategic planning, that back-and-forth approach consistently produced better results than leading with a one-shot prompt and hoping for the best.The episode also draws a clear line between creative and analytical tasks. Across the season, analytical and pattern-based tasks like coding, research, and schema building tended to produce more reliable results. Creative work was another story. Not because the tools are broken, but because creativity requires judgment the AI does not have and the human has to supply. And that supply only works if the human actually knows the domain they are working in.That last point carries the most weight. Domain expertise is not just helpful when using AI - it is the variable that determines whether you can evaluate the output at all. If you do not know what good looks like in a given area, the AI can produce something plausible and you will not know whether it actually helped. That reality is a big part of why so many AI rollouts have underdelivered, and plays a part in a lot of the AI backlash we're seeing.Previously in the Intentional AI series:Episode 1: Intentional AI and the Content LifecycleEpisode 2: Maximizing AI for Research and AnalysisEpisode 3: Smarter Content Creation with AIEpisode 4: The role of AI in content managementEpisode 5: How much can you trust AI for accessibilityEpisode 6: You’re asking AI to solve the wrong problems for SEO, GEO, and AEOEpisode 7: Why AI can make your content personalization worseEpisode 8: The real value of AI wireframes is NOT the wireframesEpisode 9: Just because AI can create images doesn't mean you should use themEpisode 10: The Super Bowl didn't sell AI, it exposed itEpisode 11: AI video rewards planning, not your ideasEpisode 12: AI might struggle with creativity, but coding isn't creativeEpisode 13.1: What the rise of conversational search means for your websiteEpisode 14: AI agents are only as good as your workflowEpisode 15: AI can't fix your social media if you have nothing to sayEpisode 16: The most important operation in analytics - understanding your "why?"New episodes drop every other Tuesday.For more conversations about AI, design, and digital strategy, visit https://www.highmonkey.com/podcast and subscribe on your favorite podcast platform.(0:00) - Intro(0:55) - Today's topic: AI prompts(2:45) - You never know where a prompt will take you(5:10) - Ask AI what to ask it(7:05) - The repeatability problem(9:00) - Creative vs. analytical: two very different conversations(11:20) - One area where AI delivers: Research(14:00) - Domain expertise = major missing variable(16:45) - The AI backlash was predictable(19:05) - As AI models continue to evolve, so will our workflows(20:45) - Closing thoughts & finale preview(21:27) - OutroSubscribe for email updates on our website:https://www.discussingstupid.com/Watch us on YouTube:https://www.youtube.com/@discussingstupidListen on Apple Podcasts, Spotify, or Soundcloud:https://podcasts.apple.com/us/podcast/discussing-stupid-a-byte-sized-podcast-on-stupid-ux/id1428145024https://open.spotify.com/show/0c47grVFmXk1cco63QioHp?si=87dbb37a4ca441c0https://soundcloud.com/discussing-stupidCheck Us Out on Socials:https://www.linkedin.com/company/discussing-stupidhttps://www.instagram.com/discussingstupid/https://www.facebook.com/discussingstupidhttps://x.com/DiscussStupid
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    23 分
  • S3E16 - Intentional AI: The most important operation in analytics - understanding your "why?"

    S3E16 - Intentional AI: The most important operation in analytics - understanding your "why?"
    2026/05/19
    If there is one thing AI should be genuinely good at, it is analytics. Pattern recognition across large data sets is more or less what it was built for. But just because AI can look at your data does not mean it knows what you are actually trying to learn from it. That is the part most people skip.In this episode, Cole brings in a framework from a LinkedIn post by Tim Stoddart that puts the problem into clear terms: data is cheap, insight is expensive, storytelling is priceless. The Lego analogy Stoddart uses is a good one. You can sort a pile of bricks by color, arrange them beautifully, and end up with something completely meaningless if you started with the wrong bricks. The same is true with analytics. Before AI can help you, you have to be honest about whether you are even pulling from the right data to begin with.Virgil has been testing this directly using the podcast's own analytics across Google Analytics, Captivate, YouTube, Apple Podcasts, Spotify, SoundCloud, and their mailing list. The challenge is not a lack of data. It is that the data lives in separate places, each with its own reporting logic, and none of them talk to each other. When he ran actual queries against the data he could access, the results were uneven. One question surfaced a genuinely useful insight about engagement that he would not have found on his own. Another hit a wall that no amount of follow-up prompting could get past.The bigger point underneath all of it is about starting with the outcome rather than the data. Virgil has applied this same logic to web strategy for years. The last page you should build is the homepage. The same principle applies here. If you cannot clearly name what you want to understand before you open your analytics, the data is not going to organize itself into an answer.The tools for cross-platform AI analytics are not quite where they need to be yet, but the direction is clear. AI is already starting to suggest its own follow-up questions, which changes the dynamic considerably for people who do not know what to ask next. The dashboard as a destination is fading. What replaces it is a conversation with your data - one that only works if you walk in knowing what you are trying to find out.Previously in the Intentional AI series:Episode 1: Intentional AI and the Content LifecycleEpisode 2: Maximizing AI for Research and AnalysisEpisode 3: Smarter Content Creation with AIEpisode 4: The role of AI in content managementEpisode 5: How much can you trust AI for accessibilityEpisode 6: You’re asking AI to solve the wrong problems for SEO, GEO, and AEOEpisode 7: Why AI can make your content personalization worseEpisode 8: The real value of AI wireframes is NOT the wireframesEpisode 9: Just because AI can create images doesn't mean you should use themEpisode 10: The Super Bowl didn't sell AI, it exposed itEpisode 11: AI video rewards planning, not your ideasEpisode 12: AI might struggle with creativity, but coding isn't creativeEpisode 13.1: What the rise of conversational search means for your websiteEpisode 14: AI agents are only as good as your workflowEpisode 15: AI can't fix your social media if you have nothing to sayNew episodes drop every other Tuesday.For more conversations about AI, design, and digital strategy, visit https://www.highmonkey.com/podcast and subscribe on your favorite podcast platform.(0:00) - Intro(0:48) - Today's topic: AI and data analytics(1:51) - Virgil example: 3 million rows, one question(4:02) - The Lego analogy: from a pile of bricks to a story(5:04) - What if you're sorting the wrong bricks?(6:26) - Building with Legos from multiple sets(8:59) - You have to know what you're building(11:00) - A live example with podcast analytics(13:59) - Where AI can name the problem but not solve it(16:04) - AI that tells you what to ask next(17:40) - Stop reading your data, start asking it questions(20:36) - The tools landscape today and what's coming(22:00) - OutroSubscribe for email updates on our website:https://www.discussingstupid.com/Watch us on YouTube:https://www.youtube.com/@discussingstupidListen on Apple Podcasts, Spotify, or Soundcloud:https://podcasts.apple.com/us/podcast/discussing-stupid-a-byte-sized-podcast-on-stupid-ux/id1428145024https://open.spotify.com/show/0c47grVFmXk1cco63QioHp?si=87dbb37a4ca441c0https://soundcloud.com/discussing-stupidCheck Us Out on Socials:https://www.linkedin.com/company/discussing-stupidhttps://www.instagram.com/discussingstupid/https://www.facebook.com/discussingstupidhttps://x.com/DiscussStupid
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    23 分
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