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  • S4E3 - How these political party websites are failing us all

    S4E3 - How these political party websites are failing us all
    2026/11/03

    It’s Election Day, and every party is asking for your vote. So we checked whether their websites let everyone in. Virgil and Cole reviewed the national DNC, RNC and Green Party websites for accessibility and usability, and did their best to leave the politics out of it.

    The idea behind the episode is simple. A party that wants every vote should have a website that every voter can use, whether they’re on a phone, using a screen reader, or just trying to find out what the party stands for. None of the three gets a clean bill of health. Each one falls short in its own way, whether that’s a site that mostly follows the rules but still gets in your way, a site built to push you toward one action, or a site nobody seems to have looked after in years.

    What the sites prioritize says a lot. These are organizations with real budgets, and their websites work more like donation funnels than introductions. The ask for money is front and center, while the information about who they are and what they believe is harder to find, and harder for some people to use at all.

    Virgil also wonders how much of this comes from organizations working in a constant scramble, pushing changes live in a hurry with nobody checking what they break. That isn’t unique to politics. Plenty of organizations run their websites the same way.

    Virgil and Cole also disagree on whether a smaller budget excuses an inaccessible site, and Virgil makes the case that free tools leave little room for excuses. They close with the first thing they’d fix on each site, and most of the fixes come down to basic attention to detail.

    (0:00) - Intro

    (1:45) - Today's topic: Political websites, critiqued

    (3:30) - Built for donations, not voters

    (4:52) - The pop-ups you hit first

    (6:04) - How the three sites scored

    (7:22) - Why big-budget sites still fail

    (11:13) - The worst offense on each site

    (13:16) - Should the Green Party get a pass?

    (15:10) - None of these sites are innocent

    (18:18) - What we would fix on each site

    (21:52) - Closing thoughts

    Subscribe for email updates on our website:

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    23 分
  • S4E2 - The new WCAG 2.2 rules you're already breaking (part 2)

    S4E2 - The new WCAG 2.2 rules you're already breaking (part 2)
    2026/10/20
    Part 1 covered three of WCAG 2.2's nine new success criteria. Part 2 finishes the list, the other three Level AA criteria plus all three Level AAA ones, with Seth Moline back to walk through what each one asks for, who it helps, and what it costs to build.Part 2 covers the remaining six.The remaining Level AA criteria:2.5.7 Dragging Movements (Level AA), which says anything you can drag also needs a way to do it with a single click or tap.2.5.8 Target Size, Minimum (Level AA), which says clickable targets need to be at least 24 by 24 pixels, or have enough space around them, so someone without precise motor control can actually hit them.3.3.8 Accessible Authentication, Minimum (Level AA), which says logging in can't require solving a puzzle or memorizing something, and specifically protects your right to paste a password.Then the AAA tier:2.4.12 Focus Not Obscured, Enhanced, the stricter version of part 1's Focus Not Obscured, where partially covered no longer passes.3.3.9 Accessible Authentication, Enhanced, which closes the one loophole the AA version left open, object recognition CAPTCHAs no longer count as compliant.2.4.13 Focus Appearance, which sets actual size and contrast requirements for what the thing you tabbed to has to look like.Part 1 was mostly about practices people have recommended for years. Part 2 gets into changes that are harder to make, because they touch decisions that other teams own. Target Size affects how designers size and space buttons and icons. Accessible Authentication affects how security teams set up logins, including whether people can paste a password and whether a CAPTCHA is used. Virgil expects pushback from designers and from internal IT teams.What stood out was the gap between how these read and what they touch. A password manager filling in a generated password should be simple, except plenty of login forms block paste specifically to stop that. A close button on a modal is an easy fix in theory, except making it big enough changes a layout a designer already signed off on. Target Size, in particular, is the one Virgil flagged as the biggest of the bunch back in part 1. After sitting through target size, authentication, and a fairly personal rant about image CAPTCHAs, it's clear why.One note: video's back for this one.(0:00) - Intro(2:01) - 2.5.7 Dragging Movements (AA)(9:06) - 2.5.8 Target Size, Minimum (AA)(17:25) - 3.3.8 Accessible Authentication, Minimum (AA)(23:52) - 2.4.12 Focus Not Obscured, Enhanced (AAA)(24:48) - 3.3.9 Accessible Authentication, Enhanced (AAA)(25:17) - 2.4.13 Focus Appearance (AAA)(25:53) - Closing thoughtsKey Episode LinksWhat's New in WCAG 2.2 (W3C): https://www.w3.org/WAI/standards-guidelines/wcag/new-in-22 Understanding 2.5.7 Dragging Movements: https://www.w3.org/WAI/WCAG22/Understanding/dragging-movements Understanding 2.5.8 Target Size (Minimum): https://www.w3.org/WAI/WCAG22/Understanding/target-size-minimum.html Understanding 3.3.8 Accessible Authentication (Minimum): https://www.w3.org/WAI/WCAG22/Understanding/accessible-authentication-minimum Understanding 2.4.12 Focus Not Obscured (Enhanced): https://www.w3.org/WAI/WCAG22/Understanding/focus-not-obscured-enhanced Understanding 3.3.9 Accessible Authentication (Enhanced): https://www.w3.org/WAI/WCAG22/Understanding/accessible-authentication-enhanced Understanding 2.4.13 Focus Appearance: https://www.w3.org/WAI/WCAG22/Understanding/focus-appearance.html Full WCAG 2.2 specification: https://www.w3.org/TR/WCAG22/ Subscribe 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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    27 分
  • S4E1 - The new WCAG 2.2 rules you're already breaking (part 1)

    S4E1 - The new WCAG 2.2 rules you're already breaking (part 1)
    2026/10/06
    WCAG 2.1 became 2.2, and most people building websites still have not looked at what actually changed. Seth Moline, High Monkey's accessibility specialist, joins Virgil and Cole to go through the new success criteria one at a time and explain what each one asks for, who it helps, and what it costs to build.Part 1 covers three of them. 3.2.6 Consistent Help (Level A), which says your support options need to stay in the same place across your site instead of vanishing the moment someone enters checkout. 3.3.7 Redundant Entry (Level A), which says stop making people re-enter information you already have. And 2.4.11 Focus Not Obscured, Minimum (Level AA), which says the field someone tabs to should not be sitting behind a sticky header or a chat bubble.If you just recognized your own site in any of those, that is sort of the point. Almost none of this is new thinking. These are UX practices people have advocated for years, now written down as standards with teeth. Good UX and good accessibility keep turning out to be the same thing, which is either reassuring or uncomfortable depending on how your last redesign went.What surprised us was the gap between how simple these sound and what they take to fix. Maintaining form state across five screens, auditing every third-party checkout tool, changing the architecture of systems owned by different teams with different permissions. Easy to explain in a sentence, expensive to repair in a codebase.There was too much here for one episode, so this is a two-parter. Part 2 drops October 20 and takes on 2.5.7 Dragging Movements, 2.5.8 Target Size, 3.3.8 Accessible Authentication, and the AAA criteria, including the one Virgil keeps calling the biggest on the list.One note: this episode is audio only. We had a recording issue, and Virgil explains it himself in the first minute. Video returns in part 2.(0:00) - Intro(4:37) - 3.2.6 Consistent Help (A)(9:27) - 3.3.7 Redundant Entry (A)(18:05) - 2.4.11 Focus Not Obscured, Minimum (AA)(23:51) - Closing thoughtsKey Episode LinksWhat's New in WCAG 2.2 (W3C): https://www.w3.org/WAI/standards-guidelines/wcag/new-in-22Understanding 3.2.6 Consistent Help: https://www.w3.org/WAI/WCAG22/Understanding/consistent-helpUnderstanding 3.3.7 Redundant Entry: https://www.w3.org/WAI/WCAG22/Understanding/redundant-entryUnderstanding 2.4.11 Focus Not Obscured (Minimum): https://www.w3.org/WAI/WCAG22/Understanding/focus-not-obscured-minimumFull WCAG 2.2 specification: https://www.w3.org/TR/WCAG22/Subscribe 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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    24 分
  • Season 4: The Teaser

    Season 4: The Teaser
    2026/09/15

    Welcome to Season 4 of Discussing Stupid!

    This podcast has always been about the same thing: the bad habits, lazy defaults, and inherited decisions that make digital work harder than it needs to be. Season 3 narrowed in on AI for a full run of episodes. This season we're back to the whole field.

    That means accessibility, user experience, content, search, design, and the way organizations actually make decisions about all of it. Some episodes will be about things that have been broken for fifteen years and nobody has bothered to fix. Others will be about brand new mistakes people are making with very new tools. AI is still in the mix, but it's one topic among many instead of the whole map.

    The format isn't changing - two people who do this work for a living, talking through what's going wrong and what to do instead. No theory for its own sake and absolutely no pretending there's a clean answer when there isn't one.

    We've got a decent list of topics for this season going, but we'd love to hear what's driving you nuts as well in the digital world. Drop a comment on YouTube, hit us up on social, or use the contact form at highmonkey.com/podcast.

    Also, in this trailer you'll hear a preview of our new theme music, written and produced by Cole.

    Episode 1 drops October 6!

    (0:00) - Welcome to Season 4

    (0:26) - Setting the Season 4 scene

    (2:07) - Send us your topics

    (2:29) - Original music for Season 4

    (3:32) - Music sneak peek

    (4:09) - Brought to you by High Monkey

    (4:20) - We have a video version

    (4:50) - Season 4 starts October 6

    Subscribe for email updates on our website:

    https://www.discussingstupid.com/

    Watch us on YouTube:

    https://www.youtube.com/@discussingstupid

    Listen on Apple Podcasts, Spotify, or Soundcloud:

    https://podcasts.apple.com/us/podcast/discussing-stupid-a-byte-sized-podcast-on-stupid-ux/id1428145024

    https://open.spotify.com/show/0c47grVFmXk1cco63QioHp?si=87dbb37a4ca441c0

    https://soundcloud.com/discussing-stupid

    Check Us Out on Socials:

    https://www.linkedin.com/company/discussing-stupid

    https://www.instagram.com/discussingstupid/

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    https://x.com/DiscussStupid
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    5 分
  • 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
  • S3E15 - Intentional AI: AI can't fix your social media if you have nothing to say

    S3E15 - Intentional AI: AI can't fix your social media if you have nothing to say
    2026/05/05
    AI-generated social media content is everywhere right now. The question is not whether you should use AI for it. The question is whether what you are producing is actually worth putting out there.In this episode, Cole and Virgil get into the honest version of this conversation. Social media is already oversaturated. The algorithm rewards activity, but activity without a message is just noise at scale. The real problem with a lot of AI-assisted social content is not that it sounds like AI. It is that there was nothing behind it to begin with.Cole ran the same prompt across three tools - Gemini, ChatGPT, and Claude - asking each to write a LinkedIn post promoting an article from earlier in the series. The source material was not great, the prompt was intentionally minimal, and the results reflected that. Each tool handled it differently, and the gap between them comes down to how well each one understood what LinkedIn actually requires from a post.The takeaway is not which tool won. It is that the output ceiling is set before you open the tool. Know what you actually want to say, then use AI to help you say it faster and across more formats. That is where it earns its place.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 workflowNew 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(1:17) - Today's topic: AI social post creation strategy(1:58) - The social media volume crisis(4:33) - Start with your message, not the tool(6:14) - Good AI use case for social media(6:56) - On standing out(8:04) - Focusing on small wins(10:48) - AI has evolved and so have our perspectives on it(14:28) - We tested 3 tools for AI social posts(15:42) - Testing Gemini(17:49) - Testing Claude(20:39) - Testing ChatGPT(22:52) - Replacing monotony is not replacing creativity(24:23) - Closing thoughts(25:14) - 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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    26 分