Md Ashraful Alam Sujan

Blog

  • Good designers, bad websites: a proposal

    Good designers, bad websites: a proposal

    I want to discuss accessibility because it is the most important thing for making websites. Other A List Apart articles give you innovation and insight. This article will give you homework. These are just my personal views, but they’re pretty good.

    I want to start off with a couple of statements, and you will agree:

    1. Designers are good people. I have never heard a designer say, “I don’t care if somebody can’t read this text”, “Not my fault if somebody can’t use this device”, or “Who cares if this is confusing?”
    2. Some designs exclude people. You have seen people unable to read the text on a website or app that somebody designed. You’ve seen people unable to use a physical device that somebody has designed. You’ve seen people utterly bamboozled while trying to use a service that somebody designed.

    So what?

    The first question is, “Is this life-or-death stuff?” The answer is, “Yes.” In my favorite essay, This Is All There Is, Aral Balkan makes the point that pretty much everything that we design can affect life events and death events. Aral gives the example of how even a straightforward bus timetable app can affect life and death events, if we design it badly:

    • somebody might miss a life event, such as their daughter’s fifth birthday party; or
    • somebody might miss a death event, such as the chance to say goodbye to a dying grandmother.

    The next—and frustrating—question is, “Why do some designs still exclude people?” After all, we know that:

    • not everybody can see perfectly;
    • not everybody can hear perfectly;
    • not everybody thinks the same way; and
    • not everybody moves the same way.

    I think the answer is that there’s too much to recall. Consider, if you will, the wide variety of topics that A List Apart articles cover. Designers are expected to remember all of that guidance, plus all of the accessibility guidance, plus so much more. It is too much.

    Recognizing accessibility issues while designing

    I’d like to point toward one possible solution, starting from Jakob Nielsen’s 10 Usability Heuristics for User Interface Design. These are from the mid-1990s, and—although there’s a good chance that you, gentle reader, are a lot younger than that—please bear with me. 

    Seeing as the problem is that there’s too much to recall, I want to look at heuristic № 6, “Recognition rather than Recall.” Jakob Nielsen said that for users, information required to use the design should be visible or easily retrievable when needed. I suggest we tweak that to make life easier for designers. Let’s say that the information required to produce the design should be visible or easily retrievable when needed. In other words, let’s make it easier to recognise accessibility issues while we’re designing.

    How are we going to do that? I really like the book A Web for Everyone—Designing Accessible User Experiences by Sarah Horton and Whitney Quesenbery. I really like this book not only because it includes a quote from me—actually two quotes, but I don’t like to boast—but because it includes personas that are perfect for helping us to recognise accessibility issues. That’s the good news. The even better news is that these personas are available now for free on the companion website to the book What Every Engineer Should Know About Digital Accessibility, again by Sarah Horton, with David Sloan this time.

    Meet your users

    I’m going to introduce you to these personas now:

    I want to throw one more persona at you now, because, well, A List Apart readers are overachievers. One of my favorite authors, Cennydd Bowles—who literally wrote the book on Future Ethics—says to create Personas Non Grata. In other words, every time we design something, we have to think about what a bad guy could do with that thing, and whom that might affect.

    To actually use these personas while designing, I like what Eric Meyer and Sara Wachter-Boettcher in Design for Real Life call the Designated Dissenter: for each project that you work on, one of your teams should be responsible for asking, “Will this work for Vishnu?”, “How’s Trevor going to get on with this?”, and so on. 

    Then, once you’ve used the personas to recognise the accessibility issues, you can look up the guidelines for whichever platforms you’re designing for: 

    Your mission, should you choose to accept it

    I told you in the introduction of this article that I would give you homework. You thought I was joking. So, here’s your homework: I want you to grab the personas from the Know About Accessibility website, and use them throughout every design project to help you recognise accessibility issues while you work—and reclaim design for everyone.


    NOTE: This article is based on “Recognise,” my five-minute presentation from Interaction Design Association (IxDA) Dublin’s Defuse (Design for Use) event in 2025.

  • Designed for a Dead Language

    Designed for a Dead Language

    Every language app in your pocket inherited a teaching method built for Latin. Understanding why that happened is a more useful design lesson than anything the apps themselves will teach you.

    In 1788, Prussia introduced the Abitur, a standardized national examination required for entry into universities and the civil service. To pass it, students needed to demonstrate measurable, gradable knowledge. The system needed to teach language to large classrooms, produce consistent outcomes, and do it with one teacher and thirty students. The educators responsible for designing this system reached for the only teaching template they had, one that had been used in European schools for two centuries: the method developed to teach Latin.

    Latin, by 1788, was a dead language. Nobody needed to speak it. The scholars who studied it were reading Cicero and Virgil, not conducting conversations. The method built around it, memorizing grammar rules, constructing translations, analyzing written texts, reflected that reality exactly. Oral skills were irrelevant. Comprehension of written form was everything. The method was not designed to produce speakers. It was designed to produce readers of texts in a language nobody spoke.

    When Prussia applied this template to French and German, living languages spoken by living people, the premise did not change. Johann Valentin Meidinger’s textbook Praktische Französische Grammatik, published in 1804, ran to 37 editions across Europe by 1857. Karl Plotz formalized the approach into what became the dominant model for teaching modern languages across Europe and eventually the United States, where it became known simply as the Prussian Method [1]. Each institution that adopted it trained teachers in it, who trained students who became teachers. The constraint that created the method, how do you grade language at scale with limited resources, became invisible inside the method itself. What remained was the assumption: language is a body of rules to be learned consciously and measured. It was a design decision dressed up, over time, as a pedagogical truth.

    The observation that should have ended it

    There are people in the world who cannot read or write a language and speak it fluently. There are children who hold full conversations years before they can read a single word. There are immigrants who arrive in a country knowing nothing of its language and come out, years later, speaking it naturally, not because they studied it, but because they lived inside it. Literacy and fluency are separate things produced by entirely separate mechanisms. The Grammar-Translation method, as it became known, assumed they were the same thing. That assumption was inherited from a method designed for a language nobody needed to speak, and it was wrong the moment it was applied to a language people actually used.

    The evidence against it accumulated slowly. In the mid to late nineteenth century, reformers including François Gouin in France and Maximilian Berlitz in the United States argued independently that language should be taught the way it is actually acquired, through immersive exposure to real communication in the target language, not through analysis of its rules. Berlitz built an entire school network around this principle. The reformers were correct. They were also largely ignored by mainstream education systems, because the Grammar-Translation method had one decisive advantage that direct immersion did not: it could be graded.

    In 1982, the linguist Stephen Krashen gave the argument its most formal articulation in what he called the Monitor Model of second language acquisition. His distinction was precise: language acquisition, the unconscious process through which children absorb their native language and through which adults succeed in immersive environments, is categorically different from language learning, the conscious study of grammar rules and vocabulary that classrooms deliver [2]. Acquisition produces fluency. Learning, at best, produces the ability to pass a test. The evidence supporting this distinction, and the observation that immersive exposure to real native-speaker communication is the mechanism that produces genuine fluency, has only grown since.

    I went to Brazil without a word of Portuguese and came out speaking it. I studied French in a classroom for years and cannot hold a conversation in French today. This is not an unusual experience. It is the expected outcome, and it has been the expected outcome for as long as we have had formal language education.

    The same decision, made again in a different medium

    Prussian educators faced the question: How do you deliver language learning at scale, measure progress, and retain users over time? The answer it arrived at was structurally identical to the one arrived at in 1788. Duolingo gamified the grammar drill into a streak. Anki formalized the translation exercise into a spaced-repetition flashcard. Babbel organized grammar lessons into structured modules. The interfaces were new. The underlying assumption, that language is a thing you study rather than an environment you inhabit, was not.

    This was not a failure of design skill. The products that emerged from these decisions are, in many respects, genuinely well-crafted. Duolingo’s retention mechanics are sophisticated. Anki’s spaced repetition is grounded in real cognitive science. They are excellent at what they actually do. The problem is what they actually do: produce measurable engagement with a proxy for language rather than the conditions that produce language itself. A streak is measurable. A vocabulary score is measurable. The moment a user walks out of an app and holds a real conversation in another language, that happens in the world, outside the product, and cannot be instrumented.

    When the outcome a user needs is difficult to measure directly, the design process tends to reach for something that can be measured. The proxy becomes the goal. The interface optimizes for it. The gap between what the product delivers and what the user actually needed grows. This is not a pattern unique to language learning. It is a pattern that repeats across product categories whenever a design constraint—the need to measure, the need to scale, the need to produce a grade—gets built into a system so deeply that it stops being visible as a constraint and starts being mistaken for a truth about the problem itself.

    What happens when the constraint changes

    The constraint that made the Grammar-Translation method necessary in 1788 was real and rational. One teacher. Thirty students. A standardized exam. You cannot grade a conversation at scale. You can grade a translation exercise. The method was not chosen because it produced fluency. It was chosen because it produced a score.

    That constraint no longer exists in the same form. Technology has made it possible to deliver immersive, real-time conversation practice to anyone with a smartphone, at a cost that continues to fall. The design problem is no longer how to make language learning gradable at scale. It is how to make the conditions of genuine language acquisition accessible to people who cannot move to another country or afford a native-speaker tutor.

    The products that are now closest to solving the actual problem are not the ones that invented a new pedagogy. They are the ones that removed the access barrier to an old one. Praktika builds AI conversation partners with distinct personalities, regional dialects, and cultural context, replicating the specificity of a real native speaker rather than a generic language-learning voice. Langua clones native speaker voices so that the interaction feels like a real conversation rather than a lesson. Rosetta Stone’s foundational methodology, image association in the target language with no translation, was built on the same insight Berlitz arrived at in the nineteenth century: language is acquired through immersive exposure, not through analysis of its rules [3]. A 2025 meta-analysis of 31 studies found that AI conversation tools produced a statistically significant improvement in language learning outcomes, a result that no amount of flashcard optimization has consistently matched [4].

    None of these products invented a new theory of language acquisition. They translated an existing one into something more people could reach.

    The design question this leaves

    The Grammar-Translation method persisted not because educators were wrong about design, but because a design decision made under a specific constraint became, over two centuries, indistinguishable from the thing itself. The constraint, how do you grade language at scale, was forgotten. The method it produced was inherited as if it were a description of how language works, passed from Prussia to Europe to America to the App Store, from the grammar drill to the streak.

    Every time a design team optimizes for a metric because the actual outcome is hard to measure, they are making a version of the same decision. It is often the right decision given real constraints. The question worth asking is whether the constraint that made it necessary still exists, or whether it has simply become invisible inside the system it originally produced.

    Before reaching for what can be measured, it is worth asking what the user actually needs to do, and what stopped them from doing it before. Sometimes the answer is a new solution. More often it is an old one that was always out of reach.

  • Why Great Leaders Change Feelings Before Minds

    Why Great Leaders Change Feelings Before Minds

    Why Great Leaders Change Feelings Before Minds written by John Jantsch read more at Duct Tape Marketing

    Catch The Full Episode Overview What does state propaganda have in common with the voice in your head telling you to play it safe? According to social psychologist Owen Fitzpatrick, more than you’d think. In this episode, Fitzpatrick joins John Jantsch to unpack the psychological machinery behind belief change, and why the same principles that […]

    AI Strategy Starts With Leadership, Not Technology written by John Jantsch read more at Duct Tape Marketing

    Catch The Full Episode

     

    Overview

    What happens to a business when the tactical, repetitive work that once trained junior employees gets absorbed by AI? That question sits at the center of this conversation with Paul Roetzer, founder and CEO of SmarterX and the Marketing AI Institute. John Jantsch and Roetzer trace the arc of AI adoption from the early days of IBM Watson through the launch of ChatGPT, and into what Roetzer now sees as the first innings of a much longer transformation.

    The conversation moves through several themes that matter to any business owner trying to make sense of AI right now: why AI has become the underlying operating system of business rather than just another tool, why the traditional path from junior to senior employee is at risk of disappearing, and why literacy, as opposed to technology, is the real foundation of organizational transformation. Roetzer also introduces his theory of an AI-era apprenticeship model, a way for companies to reinvest efficiency gains into developing new talent rather than simply cutting costs.

    This episode is for marketing leaders, agency owners, and small business owners who want a clear-eyed view of where AI adoption is headed, along with practical thinking on how to build teams that can keep up.

     

    Guest Bio

    Paul Roetzer is the founder and CEO of SmarterX and the Marketing AI Institute, and co-author of Marketing Artificial Intelligence. He launched MAICON, the Marketing AI Conference, and co-hosts The Artificial Intelligence Show. Roetzer has delivered more than 200 keynotes on AI for organizations including Google, LinkedIn, and the US government.

     

    Key Takeaways

    • AI has become the underlying operating system for business, not just a marketing tool, which means AI literacy now matters at every level of an organization, starting with the C-suite.
    • The traditional junior-to-senior career path is breaking down because AI is absorbing the tactical, repetitive work that used to train entry-level employees.
    • Roetzer’s apprenticeship theory proposes reinvesting a portion of AI-driven revenue-per-employee gains into developing junior talent, rather than sending all of the savings straight to the bottom line.
    • Companies under near-term growth or margin pressure face the strongest incentive to reduce staff, while companies willing to play the long game are better positioned to invest in people.
    • Of Roetzer’s eight pillars of AI transformation (vision, strategy, data, technology, governance, literacy, people, performance), literacy is the true starting point, and full transformation requires vision and ownership from the CEO, not just tools handed down to teams.
    • Pushback against AI is a natural and growing response to real disruption, and business leaders need to hold space for both the opportunity and the genuine costs.

     

    Great Moments (Timestamps)

    • [00:01] – Introduction: what happens when AI absorbs the work that used to train junior employees
    • [01:52] – Roetzer’s origin story, from a 2012 concept called a marketing intelligence engine to the founding of the Marketing AI Institute
    • [06:23] – AI as the underlying operating system of business and society
    • [12:19] – The eight pillars of AI business transformation and why no company has passed the test yet
    • [15:34] – Why AI literacy is the real foundation beneath every other pillar
    • [18:05] – The Architect, the Orchestrator, and the Apprentice: Roetzer’s theory for rebuilding entry-level work

     

    Memorable Quotes

    • “I overestimated how quickly everyone else was going to figure this out and the impact it would have in the near term, but then I underestimated the long-term, true transformation it was going to cause to the economy and businesses.” — Paul Roetzer
    • “If we remove all of that repetitive, data-driven work from the first three to five years of our careers, how do we get to become the experts we all became and have that domain expertise and institutional knowledge?” — Paul Roetzer
    • “You have to play the long game for sure, and a lot of companies aren’t going to have that benefit.” — Paul Roetzer
    • “We have become an AI driven economy for better or for worse. I think we’ve gotten to the point where it’s a general purpose technology… this is on par with the invention of computers and electricity.” — Paul Roetzer

     

    Resources

    Email

    Download

    New Tab

    John Jantsch (00:01.891)

    So, what happens to a business when the entry-level work that trained your people gets absorbed by AI? Today’s guest has been thinking about that maybe harder and longer than most. And his answer is possibly uncomfortable. The traditional path from junior to senior breaks, and most organizations have no plan for what replaces it. Hello, and welcome to another episode of the Duct Tape Marketing Podcast.

    This is John Jantsch. My guest today is Paul Roetzer. He is a former, or I’m sorry, he’s the founder, not former, and CEO of SmarterX and Marketing AI Institute, and co-author of Marketing Artificial Intelligence. He launched the Marketing AI conference, MACON, co-hosts the Artificial Intelligence Show, and has delivered more than 200 keynotes for AI for organizations including Google, LinkedIn, and the US government. I think after Chat GPT launched,

    Even though Paul was on that the trail, that certainly opened up many, many doors for him. So Paul, welcome back to the show.

    Paul Roetzer (01:03.192)

    China, it’s always good to be with you and to catch up. It’s it doesn’t happen often enough.

    John Jantsch (01:05.783)

    Yeah. You you I think your first appearance was when PR twenty twenty, maybe bookwise was that was the name of the book, right?

    Paul Roetzer (01:16.492)

    the kind of the agency was PR twenty twenty. That was the agency I sold back in two thousand twenty one. And then we had, I don’t know, the a marketing agency blueprint and the marketing performance blueprint. It could have been one of those that we were on for.

    John Jantsch (01:27.171)

    Awesome. All right. Well, let’s dive into the AI Institute. you built it really to help marketers understand AI. and then it just kind of blew up, right? I mean, it was an idea that then, you know. So so what it made clear that you needed to build that, which at the time was kind of outside of the marketing realm.

    Paul Roetzer (01:38.018)

    Yeah. Seven and a half years later.

    Paul Roetzer (01:52.406)

    Yeah. So the I I I’ll give the quick origin story. So actually it goes back to the PR twenty twenty days. In two thousand and eleven, I wrote the marketing agency blueprints. That was my first book. And at the time we were a few years into being HubSpot’s first partner and kind of at the forefront of marketing technology and social media and inbound marketing and content marketing and all of those things. and that was the year IBM Watson won on Jeopardy. And I became obsessed with understanding how that technology worked. And then

    John Jantsch (02:16.226)

    Mm.

    Paul Roetzer (02:21.997)

    Could it actually be applied? That same idea of it was basically a prediction engine. Take data in, you understand the language behind it, and then you make predictions about what comes next. And so I started working on this concept of what I was calling a marketing intelligence engine. And this is back in 2012 and 13. And the premise was: if we could use Watson-like technology to predict what to do next, what net next best action, next strategy, how to spend our marketing dollars, then we could build.

    An entirely new way of doing marketing. And so that was the original hypothesis. And I shared that idea in my 2014 book. And then that was like out of the 50,000 word manuscript, it was like a thousand words. And the book was not about AI otherwise. And that was all anybody wanted me to talk about. And so fast forward to 2016, and we were like, Well, what do we do with this? Like I’m really intrigued by it. I’m convinced it’s gonna change marketing and business in the world, but like I don’t really know what’s possible.

    So we created the Marketing Institute to research it ourselves and then tell the story of AI, like what was real, what was happening. And so yeah, we created the Marketing Institute in 2016. And and then, like I always half joke, like we survived long enough financially for ChatGPT to show up. I sold my agency in 2021, focused exclusively then on AI and the institute and eventually SmarterX. raised a seed round of funding that kind of got me through the the really lean years and

    Chat GPT came and all of a sudden the interest in AI exploded.

    John Jantsch (03:53.699)

    So I’ve been through I’ve been doing this a long time. I’ve been through several of these game changing technologies that came along. And there seems to be this curve. You know, there’s the early adopters, of course, and you know, and then there’s the overhypers, you know, and then there’s the like, my god, I guess it’s not going away. We better figure it out. And and then there’s just kind of like, now it’s plumbing. we don’t even call it anything anymore.

    Do you see AI having a similar path even if it’s f faster and and more disruptive?

    Paul Roetzer (04:27.637)

    I did. so my belief was actually by 2020 we wouldn’t have to call it AI anymore. I just thought it was gonna be like marketing and software and stuff. So I what I’ve always said was I overestimated how quickly everyone else was gonna figure this out and the impact it would have, like in the near term, but then I underestimated the long-term, like true transformation it was gonna cause to the economy and businesses and things like that.

    John Jantsch (04:32.842)

    Okay. Yeah, yeah.

    John Jantsch (04:44.236)

    Yeah.

    Paul Roetzer (04:53.047)

    So I have always sort of had this feeling that, like, well, maybe we shouldn’t even call it an AI institute or AI technology or whatever. We shouldn’t differentiate in that way. But I’ve now become convinced that we have a we have a very extended runway ahead of us where being AI matters, like being AI forward matters. Like it’s a differentiator within organizations to say that you’re AI forward, that you understand the technology, you use the technology.

    John Jantsch (04:59.517)

    Mm-hmm.

    John Jantsch (05:12.406)

    Mm-hmm.

    Paul Roetzer (05:18.319)

    and then as a business, I think it’s becoming fundamental for leaders of businesses to be able to think of themselves as an AI forward organization that they’re looking at ways to infuse it into people, processes, technology. And so I don’t know, it’s like I I thought we would be past it by now. And I I honestly I feel like we’re just in the first innings still.

    John Jantsch (05:37.154)

    Yeah. Yeah. Think about how many defunct social media marketing agencies, you know, are out there, for example, right? and and I think your your idea that, we don’t wanna it’s great that that’s the thing now, but we don’t want to go down that to where it just becomes, you know, business consulting or something. But you know, I think one of the major differences is AI’s impacting

    Paul Roetzer (05:44.449)

    Yes.

    John Jantsch (06:02.301)

    every area of a business. I mean, you know, the finance people are using it, the operations people are using it. I mean, obviously the marketing people are using it. And think that’s probably a significant I mean, there are many others, but but would you say that that’s maybe in some ways why it’s you’ve got this long runway is because, you know, it’s basically gonna impact everything.

    Paul Roetzer (06:23.499)

    Yeah, I I’ve I said years ago that I believed that AI was going to become the underlying operating system to businesses and society, that it was it was literally going to be woven into every aspect of what organizations do, their people, their processes, their their technology. And then within society, it was gonna become the epicenter of the economy. It was gonna basically be the driver of growth. And that’s all starting to happen. And so I do think that.

    John Jantsch (06:31.543)

    Yes.

    John Jantsch (06:46.871)

    I was gonna say they’re definitely there are definitely people suggesting that that’s where we are, yeah.

    Paul Roetzer (06:52.041)

    Yes, it’s like you the like if if we stopped building data centers right now and if the five technology companies that are spending north of eighty to a hundred billion a year on AI infrastructure stopped doing it, the economy would crumble. Like if we whether people realize it or not, we have become an AI driven economy for better or for worse. And so I yeah, I think we’ve gotten to the point where it’s a general purpose technology. Social media is a tool. Like

    John Jantsch (07:07.576)

    Yeah.

    Paul Roetzer (07:19.297)

    This is this is on on par with like the invention of computers and electricity and like it it yeah, so that’s what that’s what’s different.

    John Jantsch (07:19.649)

    Yeah.

    John Jantsch (07:24.611)

    Cars. Yeah, yeah, yeah. So there’s a little bit of a rising bubble of people that are anti AI. you know, you you see the marketing positioning of, you know, no AI was used in the creation of this. Do you think that is simply a trend or do you think that that will

    Paul Roetzer (07:46.51)

    I think it’s going to grow significantly. I think it’s gonna be stoked by interest groups that want it to grow. And then I think it’ll naturally grow because people’s lives and communities are gonna be impacted in negative ways. So I always like the the closest thing I can equate to to try and make it tangible for people is, you know, if we go back to 1994, 1995, the internet’s like becoming a a real thing in society. And at that moment, we said, you know what?

    There’s gonna be this thing called the dark web, where these like horrible people do horrible things and it’s gonna cause like online bullying and like you’re gonna have all these downstream super negative things that happen. But we go back and say, but would we still build the internet? Yeah, like a hundred times out of a hundred, you would probably still build the internet because it has changed society in a bunch of profoundly like positive ways. And I think AI is gonna be the exact same thing. There’s going to be absolutely

    Negative things that happen as a result of it, whether it’s building of data centers in communities that don’t want them, job loss and displacement, whatever. Like those things are gonna happen. They’re a byproduct of it. But if all goes well, it’s also gonna transform health and create growth engines and opportunities we’ve never had before and solve mysteries in the universe. Like it’s gonna do all these things too. So it’s totally natural that there’s just there’s pushback because it’s starting to affect people’s lives. And we

    you know, wherever your role in this is, you have to be empathetic to that. Like it’s and that’s my problem with a lot of like the Silicon Valley mentality is accelerate at all costs and like forget if if there’s risks and fears, like throw those aside. I’m not in that boat. I feel like we have to embrace the fact that not everyone loves this and it isn’t all just abundance and amazing things. There’s actually a bunch of things we have to deal with as a society as a result of this.

    John Jantsch (09:32.652)

    Yeah.

    John Jantsch (09:43.391)

    And you know, another issue that I think is I mean, I think there were some unforeseen things that came out of other technologies. But I it feels like even if you ask the smartest people in the world who are making this stuff, they don’t really know where it’s gonna go. And I think that there’s there’s an element of that that I think people some regulation needs to be in order to like not get too far out in front of something they can’t stop.

    Paul Roetzer (10:09.227)

    Yeah, there’s growing like so recently Demis Asabas posted online about the need for regulation and experts ending a framework. He’s the the co-founder CEO of Google DeepMind. Anthropic has made proposals around regulation frameworks. Sam Altman has called for regulation on Capitol Hill. Like they all claim to want it in different forms, but the regulation can be done where it actually has the negative effect on society. So there’s this like.

    Very fine line that I am not the expert in by any means about how to do regulation well. there are very few people that are building the technology who who don’t think that there needs to be some protections and guardrails in place, that we don’t have to stop and say this is gonna have a serious impact. We should be thinking more deeply about it. The challenge has been the leaders of these labs, they’re so focused on just building the technology and competing with each other and competing with China and other countries. They’re

    John Jantsch (11:04.524)

    Trying to make money. Yeah. Yeah. Yeah.

    Paul Roetzer (11:05.525)

    Yeah, they don’t sit around and think about the writers who are going to lose their jobs. Like it’s just not and they live in a bubble where it’s like they’re all just technologists and engineers and like they’re all going to have jobs for the foreseeable future because they’re all growing and hiring more of those people, but they don’t think about the average knowledge worker and the impact it’s going to have. So they’re hiring economists and philosophers and like they’re trying to now consider it, but for a long time, they were just heads down, accelerated at all costs.

    John Jantsch (11:33.706)

    Yeah. Well and I and I think unfortunately when it comes to regulation, you know, you think about the government bodies that are going to decide they need to regulate this. I mean, they can’t even line a swimming pool. You know, so the idea that sorry, that was a cheap one, but the but the idea that they’re gonna actually you know, regulate an industry like this, you know, is pr probably kind of frightening.

    Paul Roetzer (11:55.586)

    Well, yeah, and they don’t understand the technology and where it’s going. Like the idea originally a couple of years ago is to limit it based on how much compute was needed to train a model. Well, that’s laughable amounts of compute these days. Like and then they just find ways around it. So every time they try and find a way to regulate it, it generally is a a very narrow minded way of thinking about it that would eventually be obsolete within like a year or two.

    John Jantsch (12:19.158)

    So let’s talk about eight pillars of business AI transformation. That’s something that you have written about. hopefully you remember writing about that. I’ll I’ll I’ll name them for you vision, strategy, data, technology, governance, literacy, people, and performance. the key thing, whether you want to check any of those boxes, is you said no companies ever passed this test yet. where do companies break down in terms of any of those elements when it comes to transformation at an organization?

    Paul Roetzer (12:49.419)

    Yeah, so this a relatively new concept that I shared. It’s part of a larger transformation system that I’m developing. And it’s like the first piece to it because we talk to a lot of companies of all sizes, small, mid-sized businesses, large enterprises. And everybody’s trying to figure out like what does it actually look like? We throw out this term transformation, but like no one really has quantified how do we actually do that. And what we’ve seen time and time again is, especially in larger enterprises, but it happens in small businesses too.

    Just treat it as this technology problem. Like, we just gotta go get some Chad GPT licenses and give them to people. And like then we’re gonna get all these amazing benefits of AI. What app, yeah, and they throw it into the technology pool to do. What needs to happen, and the fundamental flaw that we see is a lack of situational awareness and vision from leadership. And so, my like, if I boil this down to one simple thing, the CEO has to drive the transformation. Like

    John Jantsch (13:21.226)

    Yeah. And the CTO’s in charge of it. Yeah. Right.

    Paul Roetzer (13:43.316)

    It has to be so important to the organization that the CEO has embedded him or herself in the deep understanding of the moment, of what the technology is capable of, of the impact it’s going to have on their organizational structure, their people, their products, their markets. And if the C-suite doesn’t have that, then you are not going to see a complete transformation within an organization. So vision and strategy from the leadership on down.

    Is what’s fundamental. What’s driving most of the innovation and transformation in companies so far is actually bottom up, where people are just like bringing their own devices to work or getting their own personal accounts and just like doing their own thing. And then sometimes that turns into a collective of people doing their own thing. And then maybe a department’s like, let’s form around this and let’s get a marketing AI council or something. But what often lacks is that top leadership that truly understands this needs to be one of like

    John Jantsch (14:19.222)

    Mm-hmm.

    Yeah.

    Paul Roetzer (14:41.089)

    The three biggest priorities we are working on as an organization.

    John Jantsch (14:44.428)

    Well, and I think you hit on a really thing the thing I see all the time is that they’re treating it like tools, like, here’s a new laptop. you know, as opposed to the fact that this is probably you probably need to rethink your entire organization. You probably need to think what it is, rethink it what it is you actually do. and that might be a little bigger question, you know, about do you even have the right people? you know, do you have, you know, is the structure make any sense anymore? I mean, there’s just

    You know, a lot of people like you and I sit around and talk about this stuff, and I think a lot of fifteen person business businesses are saying, Yeah, okay, tell us. I mean, it’s one thing to say you need to rethink your organization. Okay, but like what’s the roadmap for that? I mean, how does somebody, you know, w when you talk about those pillars, are there two or three that they ought to be addressing before they ever like sign up for a subscription? Yeah.

    Paul Roetzer (15:34.87)

    Yeah, so I mean, literacy is the fundamental thing. So it it’s number six on my list, but it does it’s actually probably number one overall because the even the C suite needs AI literacy. They need the knowledge and the understanding and the belief system around AI and its impact before they can prioritize it strategically within a business. So developing understanding of AI capabilities, the comp comprehension of like what it is and what it’s capable of, and then the competency to use the tools in an intelligent way.

    John Jantsch (15:44.972)

    Yeah.

    Paul Roetzer (16:02.199)

    That like you know when to go in and ask ChatGPT for help and and then you know what good looks like. So AI literacy is actually the foundation of all the other components. And then if you do that in individually and you go through the organization and say, okay, we’re gonna raise the skill level of everyone, the understanding of AI and the ability to work with it, then you can you can move the organization forward more, not only efficiency with higher efficiency and productivity, but drive actual innovation and growth as a result of it. And then as a small business, you can start to think.

    Wow, like for 20 people, we could be performing at the level of 50 people. I was actually having this conversation today with our director of operations, who she and I used to work at my agency together. And we were laughing. I said, Could you imagine if we had these tools back when we owned an agency? Like it like 90% of what we did for clients, AI is capable of doing now. And so, like, like the perfect example we gave was we used to like give.

    John Jantsch (16:49.301)

    Yeah.

    Paul Roetzer (16:59.443)

    Monthly performance reports to clients by the 15th of the following month. So you’d wrap the month up, you’d organize the data, you’d put it into the thing, you’d do the analysis, you would create the PowerPoint, you’d schedule the meeting, and by the middle of the month, you were talking about what happened the previous month. We now at SmarterX, our COO runs those things in real time. So like at any moment, she has it connected to the data.

    John Jantsch (17:04.514)

    Yeah. Right.

    Paul Roetzer (17:27.585)

    She can tell the narrative of what is happening across all of our KPIs. And boom, here’s the update in Zoom. Stuff that we used to spend dozens of hours creating on a 15 day lag, we now do in real time. And so when you apply that across entire businesses, all different departments, you start to realize how different we can run companies today.

    John Jantsch (17:49.535)

    One thing that and and I said it in my beginning kind of question was that also trained a lot of people, right? A lot of the people that did that work learned a lot about marketing by doing that work, and they’re now missing that. how do we fill that gap?

    Paul Roetzer (17:57.495)

    Yes.

    Paul Roetzer (18:05.547)

    I don’t know. it is the focus of my Make Con 2026 keynote. So the name of the keynote is The Architect, the Orchestrator, and the Apprentice. And my basic hypothesis is that we have to redefine entry-level work because the tactical things that all of us did to become experts, to know what good looks like, to have judgment and taste, and to be able to work with these amazing tools in a responsible way.

    We can do it because we did the data-driven repetitive work all those years and learned right from wrong and good from bad and things like that. And then we edited other people’s work. And it’s like if you remove all of that work from the first three to five years of our careers, how do we get to become the experts we all became and have that domain expertise and institutional knowledge? And so I don’t know the answer, but my current theory is that it looks something like an apprenticeship.

    That organizations will have an increased revenue per employee number in as a benefit of AI. So you use AI to run a more efficient business, thereby generating more revenue per employee. But rather than putting that straight to the bottom line, you reinvest a portion of that increased revenue and profit back into developing entry-level talent through an apprenticeship program where they don’t have a direct impact on revenue. They’re actually an expense item for the first maybe two to three years of their career. And so

    John Jantsch (19:02.304)

    Mm-hmm.

    Paul Roetzer (19:31.81)

    That’s a theory, but then you actually have to operationalize well, okay, if if that actually is a viable idea, how do we do it? How do we train them? How do we use these tools to advance their learning so they still come out after two or three years with not only the level we had after two or three years, but maybe like 2x that. So we actually accelerate their learning, their taste, their judgment, their capabilities by leveraging AI technology to train them in new ways. And I have yet to meet a single leader.

    Of any company of any size that has solved for

    John Jantsch (20:05.558)

    Yeah, that’s really interesting too, because I mean I I see it every day. It’s like right now some of the entry level people can’t recognize when AI is just hallucinating and saying stupid stuff. and and or just off brand, you know, even. and I think a lot of that comes from, you know, the fact that you can sit around and look at something and and immediately, you know, know the course correct.

    but that just comes from experience. And I think I think that’s a really brilliant idea, the idea of of apprentice. but again, you also mentioned expense. and I think that’s what’s gonna make it hard for people. But the you know, companies that invest like that, you know, long term, we’ve seen it time and time again, win. so I think that yeah, yeah.

    Paul Roetzer (20:52.833)

    Yeah, you have to play the long game for sure. And a lot of companies aren’t gonna have that benefit. Like I’ve always said, if you’re publicly traded, venture capital backed or private equity owned, you’re f you’re fighting an uphill battle to follow that kind of model, to play the long game and not just take the near term benefits of cost reduction.

    John Jantsch (21:10.134)

    Are are we past the period when, you know, there was a lot of noise about like I’m I’ve gonna be able to reduce my staff to, you know, a third of what I have. Are we past people realizing that because they’re actually working harder now than they ever were?

    Paul Roetzer (21:24.853)

    No, I I don’t think we’re any I don’t even think we’ve scratched the surface of people realizing that they can reduce their staff. Like, so my my basic premise here is I I do think that AI is gonna drive a lot of innovation, a lot of new businesses, a lot of growth and jobs through entrepreneurship and and creation. But when I talk with leaders at enterprises who are under these very near-term

    financial requirements to run the company where you have to either be growing or if you’re not growing fast enough, you have to be cutting expenses to still maintain the profit margins that are required. In those businesses, it’s really hard to sit there and say if you’ve had 15 marketers for the last 10 years, that you still need 15 marketers. Because we if if you train someone properly, like a a manager director level can do a lot of the entry-level work and where you maybe just don’t.

    need that entry level higher you were gonna make this year. And so in companies that aren’t growing, I think it’s very hard to make an argument that they will maintain or increase their staffing levels. I I think companies that are growing less than 10% will be under tremendous pressure in the very near future. Once their CEOs realize what’s possible, I think they’re gonna be a lot enough pressure to reduce their staff.

    John Jantsch (22:41.131)

    Mm-hmm.

    John Jantsch (22:44.748)

    Talk to me a little bit about MACON. I appreciate you stopping by the Duct Tape Marketing Podcast, but once you spend our last minute or so together talking about Makeon and inviting people I think you said you even had a special discount code for me.

    Paul Roetzer (22:57.187)

    yeah. So Mekon, this is our seventh year. It’s hard to believe. I I was I posted something recently about how crazy it actually seems in retrospect. We started this conference in 2019, three years before ChatGPT. We were running an AI conference for marketers. sometimes I struggle to think like, what were we teaching at that point? But it was a lot of like, here’s what it could become, here’s how to find use cases, here’s companies that are building, you know, like.

    John Jantsch (23:06.946)

    Mm-hmm.

    Paul Roetzer (23:22.729)

    Email subject line writing tools and predictive modeling for ad spend and things like that’s what we were focused on back in those days. So it’s become something much larger. That first year we had 300 attendees from 12 countries. This year will be well over 2,000. I know I think we had 19 countries already represented last time I saw it. and we we basically break it into applied AI and strategic AI. So now there’s like two fundamental tracks: track for leaders that are thinking more big picture about the impact on the organization.

    John Jantsch (23:24.929)

    Yeah.

    Paul Roetzer (23:51.618)

    And applied AI is all about use cases, technologies, things like that, where you go in and then we have build sessions and workshops. So it’s an incredibly immersive environment. It’s a great community of other AI forward marketers and business leaders. So if you’re trying to find your people, try and find that community of other people who are thinking and trying to work toward like a human centered approach to this, that’s what Make On is all about. So yeah, you can go to makeon.ai, it’s A I C O N.ai, it’s in Cleveland.

    October thirteenth to the fifteenth, and then duct tape one fifty is the promo code for saving a hundred and fifty bucks.

    John Jantsch (24:24.492)

    So two T’s in there, so D U D U C T T A P E. Yes, okay. Awesome. Duct tape one fifty gets you hundred and fifty dollars off, I’m guessing.

    Paul Roetzer (24:28.481)

    Yes.

    Paul Roetzer (24:34.209)

    That’s I’m guessing too. Looks like looks like that that would be what the one fifty would be in my mind. So if not, we’re gonna make it so.

    John Jantsch (24:40.546)

    Awesome. What yeah, awesome, awesome. Well, you know, that idea of literacy, you know, if you’re if you’re finding yourself behind, what a great place to pick up that component and and actually do some hands-on work as well. Well, Paul, I appreciate you taking a few moments to stop by and hopefully it won’t be that long. we’ll run into you one of these days out there on the road.

    Paul Roetzer (25:04.205)

    All right, John, it’s great to see you.

    John Jantsch (25:05.907)

    Dude.

    Scroll back to top

    powered by

  • AI Strategy Starts With Leadership, Not Technology

    AI Strategy Starts With Leadership, Not Technology

    AI Strategy Starts With Leadership, Not Technology written by John Jantsch read more at Duct Tape Marketing

    Catch The Full Episode   Overview What happens to a business when the tactical, repetitive work that once trained junior employees gets absorbed by AI? That question sits at the center of this conversation with Paul Roetzer, founder and CEO of SmarterX and the Marketing AI Institute. John Jantsch and Roetzer trace the arc of […]

    AI Strategy Starts With Leadership, Not Technology written by John Jantsch read more at Duct Tape Marketing

    Catch The Full Episode

     

    Overview

    What happens to a business when the tactical, repetitive work that once trained junior employees gets absorbed by AI? That question sits at the center of this conversation with Paul Roetzer, founder and CEO of SmarterX and the Marketing AI Institute. John Jantsch and Roetzer trace the arc of AI adoption from the early days of IBM Watson through the launch of ChatGPT, and into what Roetzer now sees as the first innings of a much longer transformation.

    The conversation moves through several themes that matter to any business owner trying to make sense of AI right now: why AI has become the underlying operating system of business rather than just another tool, why the traditional path from junior to senior employee is at risk of disappearing, and why literacy, as opposed to technology, is the real foundation of organizational transformation. Roetzer also introduces his theory of an AI-era apprenticeship model, a way for companies to reinvest efficiency gains into developing new talent rather than simply cutting costs.

    This episode is for marketing leaders, agency owners, and small business owners who want a clear-eyed view of where AI adoption is headed, along with practical thinking on how to build teams that can keep up.

     

    Guest Bio

    Paul Roetzer is the founder and CEO of SmarterX and the Marketing AI Institute, and co-author of Marketing Artificial Intelligence. He launched MAICON, the Marketing AI Conference, and co-hosts The Artificial Intelligence Show. Roetzer has delivered more than 200 keynotes on AI for organizations including Google, LinkedIn, and the US government.

     

    Key Takeaways

    • AI has become the underlying operating system for business, not just a marketing tool, which means AI literacy now matters at every level of an organization, starting with the C-suite.
    • The traditional junior-to-senior career path is breaking down because AI is absorbing the tactical, repetitive work that used to train entry-level employees.
    • Roetzer’s apprenticeship theory proposes reinvesting a portion of AI-driven revenue-per-employee gains into developing junior talent, rather than sending all of the savings straight to the bottom line.
    • Companies under near-term growth or margin pressure face the strongest incentive to reduce staff, while companies willing to play the long game are better positioned to invest in people.
    • Of Roetzer’s eight pillars of AI transformation (vision, strategy, data, technology, governance, literacy, people, performance), literacy is the true starting point, and full transformation requires vision and ownership from the CEO, not just tools handed down to teams.
    • Pushback against AI is a natural and growing response to real disruption, and business leaders need to hold space for both the opportunity and the genuine costs.

     

    Great Moments (Timestamps)

    • [00:01] – Introduction: what happens when AI absorbs the work that used to train junior employees
    • [01:52] – Roetzer’s origin story, from a 2012 concept called a marketing intelligence engine to the founding of the Marketing AI Institute
    • [06:23] – AI as the underlying operating system of business and society
    • [12:19] – The eight pillars of AI business transformation and why no company has passed the test yet
    • [15:34] – Why AI literacy is the real foundation beneath every other pillar
    • [18:05] – The Architect, the Orchestrator, and the Apprentice: Roetzer’s theory for rebuilding entry-level work

     

    Memorable Quotes

    • “I overestimated how quickly everyone else was going to figure this out and the impact it would have in the near term, but then I underestimated the long-term, true transformation it was going to cause to the economy and businesses.” — Paul Roetzer
    • “If we remove all of that repetitive, data-driven work from the first three to five years of our careers, how do we get to become the experts we all became and have that domain expertise and institutional knowledge?” — Paul Roetzer
    • “You have to play the long game for sure, and a lot of companies aren’t going to have that benefit.” — Paul Roetzer
    • “We have become an AI driven economy for better or for worse. I think we’ve gotten to the point where it’s a general purpose technology… this is on par with the invention of computers and electricity.” — Paul Roetzer

     

    Resources

    Email

    Download

    New Tab

    John Jantsch (00:01.891)

    So, what happens to a business when the entry-level work that trained your people gets absorbed by AI? Today’s guest has been thinking about that maybe harder and longer than most. And his answer is possibly uncomfortable. The traditional path from junior to senior breaks, and most organizations have no plan for what replaces it. Hello, and welcome to another episode of the Duct Tape Marketing Podcast.

    This is John Jantsch. My guest today is Paul Roetzer. He is a former, or I’m sorry, he’s the founder, not former, and CEO of SmarterX and Marketing AI Institute, and co-author of Marketing Artificial Intelligence. He launched the Marketing AI conference, MACON, co-hosts the Artificial Intelligence Show, and has delivered more than 200 keynotes for AI for organizations including Google, LinkedIn, and the US government. I think after Chat GPT launched,

    Even though Paul was on that the trail, that certainly opened up many, many doors for him. So Paul, welcome back to the show.

    Paul Roetzer (01:03.192)

    China, it’s always good to be with you and to catch up. It’s it doesn’t happen often enough.

    John Jantsch (01:05.783)

    Yeah. You you I think your first appearance was when PR twenty twenty, maybe bookwise was that was the name of the book, right?

    Paul Roetzer (01:16.492)

    the kind of the agency was PR twenty twenty. That was the agency I sold back in two thousand twenty one. And then we had, I don’t know, the a marketing agency blueprint and the marketing performance blueprint. It could have been one of those that we were on for.

    John Jantsch (01:27.171)

    Awesome. All right. Well, let’s dive into the AI Institute. you built it really to help marketers understand AI. and then it just kind of blew up, right? I mean, it was an idea that then, you know. So so what it made clear that you needed to build that, which at the time was kind of outside of the marketing realm.

    Paul Roetzer (01:38.018)

    Yeah. Seven and a half years later.

    Paul Roetzer (01:52.406)

    Yeah. So the I I I’ll give the quick origin story. So actually it goes back to the PR twenty twenty days. In two thousand and eleven, I wrote the marketing agency blueprints. That was my first book. And at the time we were a few years into being HubSpot’s first partner and kind of at the forefront of marketing technology and social media and inbound marketing and content marketing and all of those things. and that was the year IBM Watson won on Jeopardy. And I became obsessed with understanding how that technology worked. And then

    John Jantsch (02:16.226)

    Mm.

    Paul Roetzer (02:21.997)

    Could it actually be applied? That same idea of it was basically a prediction engine. Take data in, you understand the language behind it, and then you make predictions about what comes next. And so I started working on this concept of what I was calling a marketing intelligence engine. And this is back in 2012 and 13. And the premise was: if we could use Watson-like technology to predict what to do next, what net next best action, next strategy, how to spend our marketing dollars, then we could build.

    An entirely new way of doing marketing. And so that was the original hypothesis. And I shared that idea in my 2014 book. And then that was like out of the 50,000 word manuscript, it was like a thousand words. And the book was not about AI otherwise. And that was all anybody wanted me to talk about. And so fast forward to 2016, and we were like, Well, what do we do with this? Like I’m really intrigued by it. I’m convinced it’s gonna change marketing and business in the world, but like I don’t really know what’s possible.

    So we created the Marketing Institute to research it ourselves and then tell the story of AI, like what was real, what was happening. And so yeah, we created the Marketing Institute in 2016. And and then, like I always half joke, like we survived long enough financially for ChatGPT to show up. I sold my agency in 2021, focused exclusively then on AI and the institute and eventually SmarterX. raised a seed round of funding that kind of got me through the the really lean years and

    Chat GPT came and all of a sudden the interest in AI exploded.

    John Jantsch (03:53.699)

    So I’ve been through I’ve been doing this a long time. I’ve been through several of these game changing technologies that came along. And there seems to be this curve. You know, there’s the early adopters, of course, and you know, and then there’s the overhypers, you know, and then there’s the like, my god, I guess it’s not going away. We better figure it out. And and then there’s just kind of like, now it’s plumbing. we don’t even call it anything anymore.

    Do you see AI having a similar path even if it’s f faster and and more disruptive?

    Paul Roetzer (04:27.637)

    I did. so my belief was actually by 2020 we wouldn’t have to call it AI anymore. I just thought it was gonna be like marketing and software and stuff. So I what I’ve always said was I overestimated how quickly everyone else was gonna figure this out and the impact it would have, like in the near term, but then I underestimated the long-term, like true transformation it was gonna cause to the economy and businesses and things like that.

    John Jantsch (04:32.842)

    Okay. Yeah, yeah.

    John Jantsch (04:44.236)

    Yeah.

    Paul Roetzer (04:53.047)

    So I have always sort of had this feeling that, like, well, maybe we shouldn’t even call it an AI institute or AI technology or whatever. We shouldn’t differentiate in that way. But I’ve now become convinced that we have a we have a very extended runway ahead of us where being AI matters, like being AI forward matters. Like it’s a differentiator within organizations to say that you’re AI forward, that you understand the technology, you use the technology.

    John Jantsch (04:59.517)

    Mm-hmm.

    John Jantsch (05:12.406)

    Mm-hmm.

    Paul Roetzer (05:18.319)

    and then as a business, I think it’s becoming fundamental for leaders of businesses to be able to think of themselves as an AI forward organization that they’re looking at ways to infuse it into people, processes, technology. And so I don’t know, it’s like I I thought we would be past it by now. And I I honestly I feel like we’re just in the first innings still.

    John Jantsch (05:37.154)

    Yeah. Yeah. Think about how many defunct social media marketing agencies, you know, are out there, for example, right? and and I think your your idea that, we don’t wanna it’s great that that’s the thing now, but we don’t want to go down that to where it just becomes, you know, business consulting or something. But you know, I think one of the major differences is AI’s impacting

    Paul Roetzer (05:44.449)

    Yes.

    John Jantsch (06:02.301)

    every area of a business. I mean, you know, the finance people are using it, the operations people are using it. I mean, obviously the marketing people are using it. And think that’s probably a significant I mean, there are many others, but but would you say that that’s maybe in some ways why it’s you’ve got this long runway is because, you know, it’s basically gonna impact everything.

    Paul Roetzer (06:23.499)

    Yeah, I I’ve I said years ago that I believed that AI was going to become the underlying operating system to businesses and society, that it was it was literally going to be woven into every aspect of what organizations do, their people, their processes, their their technology. And then within society, it was gonna become the epicenter of the economy. It was gonna basically be the driver of growth. And that’s all starting to happen. And so I do think that.

    John Jantsch (06:31.543)

    Yes.

    John Jantsch (06:46.871)

    I was gonna say they’re definitely there are definitely people suggesting that that’s where we are, yeah.

    Paul Roetzer (06:52.041)

    Yes, it’s like you the like if if we stopped building data centers right now and if the five technology companies that are spending north of eighty to a hundred billion a year on AI infrastructure stopped doing it, the economy would crumble. Like if we whether people realize it or not, we have become an AI driven economy for better or for worse. And so I yeah, I think we’ve gotten to the point where it’s a general purpose technology. Social media is a tool. Like

    John Jantsch (07:07.576)

    Yeah.

    Paul Roetzer (07:19.297)

    This is this is on on par with like the invention of computers and electricity and like it it yeah, so that’s what that’s what’s different.

    John Jantsch (07:19.649)

    Yeah.

    John Jantsch (07:24.611)

    Cars. Yeah, yeah, yeah. So there’s a little bit of a rising bubble of people that are anti AI. you know, you you see the marketing positioning of, you know, no AI was used in the creation of this. Do you think that is simply a trend or do you think that that will

    Paul Roetzer (07:46.51)

    I think it’s going to grow significantly. I think it’s gonna be stoked by interest groups that want it to grow. And then I think it’ll naturally grow because people’s lives and communities are gonna be impacted in negative ways. So I always like the the closest thing I can equate to to try and make it tangible for people is, you know, if we go back to 1994, 1995, the internet’s like becoming a a real thing in society. And at that moment, we said, you know what?

    There’s gonna be this thing called the dark web, where these like horrible people do horrible things and it’s gonna cause like online bullying and like you’re gonna have all these downstream super negative things that happen. But we go back and say, but would we still build the internet? Yeah, like a hundred times out of a hundred, you would probably still build the internet because it has changed society in a bunch of profoundly like positive ways. And I think AI is gonna be the exact same thing. There’s going to be absolutely

    Negative things that happen as a result of it, whether it’s building of data centers in communities that don’t want them, job loss and displacement, whatever. Like those things are gonna happen. They’re a byproduct of it. But if all goes well, it’s also gonna transform health and create growth engines and opportunities we’ve never had before and solve mysteries in the universe. Like it’s gonna do all these things too. So it’s totally natural that there’s just there’s pushback because it’s starting to affect people’s lives. And we

    you know, wherever your role in this is, you have to be empathetic to that. Like it’s and that’s my problem with a lot of like the Silicon Valley mentality is accelerate at all costs and like forget if if there’s risks and fears, like throw those aside. I’m not in that boat. I feel like we have to embrace the fact that not everyone loves this and it isn’t all just abundance and amazing things. There’s actually a bunch of things we have to deal with as a society as a result of this.

    John Jantsch (09:32.652)

    Yeah.

    John Jantsch (09:43.391)

    And you know, another issue that I think is I mean, I think there were some unforeseen things that came out of other technologies. But I it feels like even if you ask the smartest people in the world who are making this stuff, they don’t really know where it’s gonna go. And I think that there’s there’s an element of that that I think people some regulation needs to be in order to like not get too far out in front of something they can’t stop.

    Paul Roetzer (10:09.227)

    Yeah, there’s growing like so recently Demis Asabas posted online about the need for regulation and experts ending a framework. He’s the the co-founder CEO of Google DeepMind. Anthropic has made proposals around regulation frameworks. Sam Altman has called for regulation on Capitol Hill. Like they all claim to want it in different forms, but the regulation can be done where it actually has the negative effect on society. So there’s this like.

    Very fine line that I am not the expert in by any means about how to do regulation well. there are very few people that are building the technology who who don’t think that there needs to be some protections and guardrails in place, that we don’t have to stop and say this is gonna have a serious impact. We should be thinking more deeply about it. The challenge has been the leaders of these labs, they’re so focused on just building the technology and competing with each other and competing with China and other countries. They’re

    John Jantsch (11:04.524)

    Trying to make money. Yeah. Yeah. Yeah.

    Paul Roetzer (11:05.525)

    Yeah, they don’t sit around and think about the writers who are going to lose their jobs. Like it’s just not and they live in a bubble where it’s like they’re all just technologists and engineers and like they’re all going to have jobs for the foreseeable future because they’re all growing and hiring more of those people, but they don’t think about the average knowledge worker and the impact it’s going to have. So they’re hiring economists and philosophers and like they’re trying to now consider it, but for a long time, they were just heads down, accelerated at all costs.

    John Jantsch (11:33.706)

    Yeah. Well and I and I think unfortunately when it comes to regulation, you know, you think about the government bodies that are going to decide they need to regulate this. I mean, they can’t even line a swimming pool. You know, so the idea that sorry, that was a cheap one, but the but the idea that they’re gonna actually you know, regulate an industry like this, you know, is pr probably kind of frightening.

    Paul Roetzer (11:55.586)

    Well, yeah, and they don’t understand the technology and where it’s going. Like the idea originally a couple of years ago is to limit it based on how much compute was needed to train a model. Well, that’s laughable amounts of compute these days. Like and then they just find ways around it. So every time they try and find a way to regulate it, it generally is a a very narrow minded way of thinking about it that would eventually be obsolete within like a year or two.

    John Jantsch (12:19.158)

    So let’s talk about eight pillars of business AI transformation. That’s something that you have written about. hopefully you remember writing about that. I’ll I’ll I’ll name them for you vision, strategy, data, technology, governance, literacy, people, and performance. the key thing, whether you want to check any of those boxes, is you said no companies ever passed this test yet. where do companies break down in terms of any of those elements when it comes to transformation at an organization?

    Paul Roetzer (12:49.419)

    Yeah, so this a relatively new concept that I shared. It’s part of a larger transformation system that I’m developing. And it’s like the first piece to it because we talk to a lot of companies of all sizes, small, mid-sized businesses, large enterprises. And everybody’s trying to figure out like what does it actually look like? We throw out this term transformation, but like no one really has quantified how do we actually do that. And what we’ve seen time and time again is, especially in larger enterprises, but it happens in small businesses too.

    Just treat it as this technology problem. Like, we just gotta go get some Chad GPT licenses and give them to people. And like then we’re gonna get all these amazing benefits of AI. What app, yeah, and they throw it into the technology pool to do. What needs to happen, and the fundamental flaw that we see is a lack of situational awareness and vision from leadership. And so, my like, if I boil this down to one simple thing, the CEO has to drive the transformation. Like

    John Jantsch (13:21.226)

    Yeah. And the CTO’s in charge of it. Yeah. Right.

    Paul Roetzer (13:43.316)

    It has to be so important to the organization that the CEO has embedded him or herself in the deep understanding of the moment, of what the technology is capable of, of the impact it’s going to have on their organizational structure, their people, their products, their markets. And if the C-suite doesn’t have that, then you are not going to see a complete transformation within an organization. So vision and strategy from the leadership on down.

    Is what’s fundamental. What’s driving most of the innovation and transformation in companies so far is actually bottom up, where people are just like bringing their own devices to work or getting their own personal accounts and just like doing their own thing. And then sometimes that turns into a collective of people doing their own thing. And then maybe a department’s like, let’s form around this and let’s get a marketing AI council or something. But what often lacks is that top leadership that truly understands this needs to be one of like

    John Jantsch (14:19.222)

    Mm-hmm.

    Yeah.

    Paul Roetzer (14:41.089)

    The three biggest priorities we are working on as an organization.

    John Jantsch (14:44.428)

    Well, and I think you hit on a really thing the thing I see all the time is that they’re treating it like tools, like, here’s a new laptop. you know, as opposed to the fact that this is probably you probably need to rethink your entire organization. You probably need to think what it is, rethink it what it is you actually do. and that might be a little bigger question, you know, about do you even have the right people? you know, do you have, you know, is the structure make any sense anymore? I mean, there’s just

    You know, a lot of people like you and I sit around and talk about this stuff, and I think a lot of fifteen person business businesses are saying, Yeah, okay, tell us. I mean, it’s one thing to say you need to rethink your organization. Okay, but like what’s the roadmap for that? I mean, how does somebody, you know, w when you talk about those pillars, are there two or three that they ought to be addressing before they ever like sign up for a subscription? Yeah.

    Paul Roetzer (15:34.87)

    Yeah, so I mean, literacy is the fundamental thing. So it it’s number six on my list, but it does it’s actually probably number one overall because the even the C suite needs AI literacy. They need the knowledge and the understanding and the belief system around AI and its impact before they can prioritize it strategically within a business. So developing understanding of AI capabilities, the comp comprehension of like what it is and what it’s capable of, and then the competency to use the tools in an intelligent way.

    John Jantsch (15:44.972)

    Yeah.

    Paul Roetzer (16:02.199)

    That like you know when to go in and ask ChatGPT for help and and then you know what good looks like. So AI literacy is actually the foundation of all the other components. And then if you do that in individually and you go through the organization and say, okay, we’re gonna raise the skill level of everyone, the understanding of AI and the ability to work with it, then you can you can move the organization forward more, not only efficiency with higher efficiency and productivity, but drive actual innovation and growth as a result of it. And then as a small business, you can start to think.

    Wow, like for 20 people, we could be performing at the level of 50 people. I was actually having this conversation today with our director of operations, who she and I used to work at my agency together. And we were laughing. I said, Could you imagine if we had these tools back when we owned an agency? Like it like 90% of what we did for clients, AI is capable of doing now. And so, like, like the perfect example we gave was we used to like give.

    John Jantsch (16:49.301)

    Yeah.

    Paul Roetzer (16:59.443)

    Monthly performance reports to clients by the 15th of the following month. So you’d wrap the month up, you’d organize the data, you’d put it into the thing, you’d do the analysis, you would create the PowerPoint, you’d schedule the meeting, and by the middle of the month, you were talking about what happened the previous month. We now at SmarterX, our COO runs those things in real time. So like at any moment, she has it connected to the data.

    John Jantsch (17:04.514)

    Yeah. Right.

    Paul Roetzer (17:27.585)

    She can tell the narrative of what is happening across all of our KPIs. And boom, here’s the update in Zoom. Stuff that we used to spend dozens of hours creating on a 15 day lag, we now do in real time. And so when you apply that across entire businesses, all different departments, you start to realize how different we can run companies today.

    John Jantsch (17:49.535)

    One thing that and and I said it in my beginning kind of question was that also trained a lot of people, right? A lot of the people that did that work learned a lot about marketing by doing that work, and they’re now missing that. how do we fill that gap?

    Paul Roetzer (17:57.495)

    Yes.

    Paul Roetzer (18:05.547)

    I don’t know. it is the focus of my Make Con 2026 keynote. So the name of the keynote is The Architect, the Orchestrator, and the Apprentice. And my basic hypothesis is that we have to redefine entry-level work because the tactical things that all of us did to become experts, to know what good looks like, to have judgment and taste, and to be able to work with these amazing tools in a responsible way.

    We can do it because we did the data-driven repetitive work all those years and learned right from wrong and good from bad and things like that. And then we edited other people’s work. And it’s like if you remove all of that work from the first three to five years of our careers, how do we get to become the experts we all became and have that domain expertise and institutional knowledge? And so I don’t know the answer, but my current theory is that it looks something like an apprenticeship.

    That organizations will have an increased revenue per employee number in as a benefit of AI. So you use AI to run a more efficient business, thereby generating more revenue per employee. But rather than putting that straight to the bottom line, you reinvest a portion of that increased revenue and profit back into developing entry-level talent through an apprenticeship program where they don’t have a direct impact on revenue. They’re actually an expense item for the first maybe two to three years of their career. And so

    John Jantsch (19:02.304)

    Mm-hmm.

    Paul Roetzer (19:31.81)

    That’s a theory, but then you actually have to operationalize well, okay, if if that actually is a viable idea, how do we do it? How do we train them? How do we use these tools to advance their learning so they still come out after two or three years with not only the level we had after two or three years, but maybe like 2x that. So we actually accelerate their learning, their taste, their judgment, their capabilities by leveraging AI technology to train them in new ways. And I have yet to meet a single leader.

    Of any company of any size that has solved for

    John Jantsch (20:05.558)

    Yeah, that’s really interesting too, because I mean I I see it every day. It’s like right now some of the entry level people can’t recognize when AI is just hallucinating and saying stupid stuff. and and or just off brand, you know, even. and I think a lot of that comes from, you know, the fact that you can sit around and look at something and and immediately, you know, know the course correct.

    but that just comes from experience. And I think I think that’s a really brilliant idea, the idea of of apprentice. but again, you also mentioned expense. and I think that’s what’s gonna make it hard for people. But the you know, companies that invest like that, you know, long term, we’ve seen it time and time again, win. so I think that yeah, yeah.

    Paul Roetzer (20:52.833)

    Yeah, you have to play the long game for sure. And a lot of companies aren’t gonna have that benefit. Like I’ve always said, if you’re publicly traded, venture capital backed or private equity owned, you’re f you’re fighting an uphill battle to follow that kind of model, to play the long game and not just take the near term benefits of cost reduction.

    John Jantsch (21:10.134)

    Are are we past the period when, you know, there was a lot of noise about like I’m I’ve gonna be able to reduce my staff to, you know, a third of what I have. Are we past people realizing that because they’re actually working harder now than they ever were?

    Paul Roetzer (21:24.853)

    No, I I don’t think we’re any I don’t even think we’ve scratched the surface of people realizing that they can reduce their staff. Like, so my my basic premise here is I I do think that AI is gonna drive a lot of innovation, a lot of new businesses, a lot of growth and jobs through entrepreneurship and and creation. But when I talk with leaders at enterprises who are under these very near-term

    financial requirements to run the company where you have to either be growing or if you’re not growing fast enough, you have to be cutting expenses to still maintain the profit margins that are required. In those businesses, it’s really hard to sit there and say if you’ve had 15 marketers for the last 10 years, that you still need 15 marketers. Because we if if you train someone properly, like a a manager director level can do a lot of the entry-level work and where you maybe just don’t.

    need that entry level higher you were gonna make this year. And so in companies that aren’t growing, I think it’s very hard to make an argument that they will maintain or increase their staffing levels. I I think companies that are growing less than 10% will be under tremendous pressure in the very near future. Once their CEOs realize what’s possible, I think they’re gonna be a lot enough pressure to reduce their staff.

    John Jantsch (22:41.131)

    Mm-hmm.

    John Jantsch (22:44.748)

    Talk to me a little bit about MACON. I appreciate you stopping by the Duct Tape Marketing Podcast, but once you spend our last minute or so together talking about Makeon and inviting people I think you said you even had a special discount code for me.

    Paul Roetzer (22:57.187)

    yeah. So Mekon, this is our seventh year. It’s hard to believe. I I was I posted something recently about how crazy it actually seems in retrospect. We started this conference in 2019, three years before ChatGPT. We were running an AI conference for marketers. sometimes I struggle to think like, what were we teaching at that point? But it was a lot of like, here’s what it could become, here’s how to find use cases, here’s companies that are building, you know, like.

    John Jantsch (23:06.946)

    Mm-hmm.

    Paul Roetzer (23:22.729)

    Email subject line writing tools and predictive modeling for ad spend and things like that’s what we were focused on back in those days. So it’s become something much larger. That first year we had 300 attendees from 12 countries. This year will be well over 2,000. I know I think we had 19 countries already represented last time I saw it. and we we basically break it into applied AI and strategic AI. So now there’s like two fundamental tracks: track for leaders that are thinking more big picture about the impact on the organization.

    John Jantsch (23:24.929)

    Yeah.

    Paul Roetzer (23:51.618)

    And applied AI is all about use cases, technologies, things like that, where you go in and then we have build sessions and workshops. So it’s an incredibly immersive environment. It’s a great community of other AI forward marketers and business leaders. So if you’re trying to find your people, try and find that community of other people who are thinking and trying to work toward like a human centered approach to this, that’s what Make On is all about. So yeah, you can go to makeon.ai, it’s A I C O N.ai, it’s in Cleveland.

    October thirteenth to the fifteenth, and then duct tape one fifty is the promo code for saving a hundred and fifty bucks.

    John Jantsch (24:24.492)

    So two T’s in there, so D U D U C T T A P E. Yes, okay. Awesome. Duct tape one fifty gets you hundred and fifty dollars off, I’m guessing.

    Paul Roetzer (24:28.481)

    Yes.

    Paul Roetzer (24:34.209)

    That’s I’m guessing too. Looks like looks like that that would be what the one fifty would be in my mind. So if not, we’re gonna make it so.

    John Jantsch (24:40.546)

    Awesome. What yeah, awesome, awesome. Well, you know, that idea of literacy, you know, if you’re if you’re finding yourself behind, what a great place to pick up that component and and actually do some hands-on work as well. Well, Paul, I appreciate you taking a few moments to stop by and hopefully it won’t be that long. we’ll run into you one of these days out there on the road.

    Paul Roetzer (25:04.205)

    All right, John, it’s great to see you.

    John Jantsch (25:05.907)

    Dude.

    Scroll back to top

    powered by

  • 15 Movies Where Nobody Actually Seems to Know What Happened

    15 Movies Where Nobody Actually Seems to Know What Happened

    It’s only natural to discuss a movie after the credits roll, letting audiences discuss the ideas and thoughts that the movie sparked. What we don’t expect is needing those discussions to make sense of what we watched, since some movies can be quite complicated to even begin to grasp.

    This is actually the appeal for many of these films, and the intended way to consume them. You’re meant to reach your own conclusion rather than getting everything in a neat bow. If you want to force your brain to form thoughts, here are some movies to watch and obsess over.

    The post 15 Movies Where Nobody Actually Seems to Know What Happened appeared first on Den of Geek.

    In the early days of Hollywood, movie studios controlled almost every part of an actor’s career. They decided which roles performers accepted, how they looked in public, and sometimes even what they could say in interviews. That level of control was only one chapter in an industry shaped by censorship battles, political investigations, labor disputes, and legal fights that changed filmmaking forever.

    Here are 15 facts from the troubled history of Hollywood.

    ©Wikimedia Commons

    The Hollywood Blacklist

    During the late 1940s and 1950s, hundreds of writers, directors, and actors found themselves unable to work after being accused of communist sympathies. Many were never formally charged with a crime, yet their careers were effectively put on hold for years.

    ©Wikimedia Commons

    The Hays Code changed what audiences could see

    For more than three decades, Hollywood followed strict censorship rules that limited everything from romance and violence to crime and even the way married couples could be shown on screen.

    ©Wikimedia Commons

    Olivia de Havilland challenged the studio system

    In 1943, Olivia de Havilland successfully sued Warner Bros., helping actors escape restrictive long-term contracts that had given studios enormous control over their careers.

    ©Wikimedia Commons

    The Paramount Decree broke up Hollywood’s biggest monopoly

    A landmark 1948 court ruling forced major studios to sell their theater chains, changing the way movies were distributed across the United States.

    ©Wikimedia Commons

    Judy Garland paid the price of becoming a child star

    While working under MGM, Garland was reportedly given pills to help control her weight and energy levels, highlighting the intense pressure young performers often faced during Hollywood’s Golden Age.

    ©Wikimedia Commons

    United Artists was created to give filmmakers more control

    Charlie Chaplin, Mary Pickford, Douglas Fairbanks, and D.W. Griffith founded United Artists in 1919 because they wanted greater creative and financial independence from the major studios.

    ©Wikimedia Commons

    Sound movies changed Hollywood almost overnight

    When talking pictures replaced silent films, many actors struggled to adapt because of their voices, accents, or performance style. Some of the biggest stars of the silent era quickly disappeared from the spotlight.

    ©Wikimedia Commons

    Movie ratings replaced strict censorship

    In 1968, Hollywood abandoned the Hays Code and introduced the MPAA ratings system instead. Filmmakers gained much more creative freedom while audiences received clearer guidance about movie content.

    ©Wikimedia Commons

    The 2007 writers’ strike brought productions to a halt

    Television series and movie projects across Hollywood were delayed for months as writers fought for better compensation in the early days of streaming and digital distribution.

    ©Wikimedia Commons

    The 2023 Hollywood strikes focused on streaming and AI

    Writers and actors walked picket lines together while negotiating higher streaming residuals, better working conditions, and protections against the growing use of artificial intelligence.

    ©Wikimedia Commons

    Hattie McDaniel made history but still faced segregation

    After becoming the first Black performer to win an Academy Award in 1940, McDaniel was required to sit at a separate table because the ceremony took place in a segregated hotel.

    ©Wikimedia Commons

    Charlie Chaplin became a political target

    During the Red Scare, Chaplin was accused of having communist sympathies. Although he was never convicted of a crime, the controversy contributed to his decision to settle in Europe.

    ©Wikimedia Commons

    The Fatty Arbuckle scandal transformed Hollywood’s public image

    Roscoe “Fatty” Arbuckle was acquitted after being accused in one of Hollywood’s earliest major scandals, but the case permanently damaged his career and pushed studios to exercise tighter control over their stars’ public reputations.

    ©Wikimedia Commons

    Studios once controlled nearly every part of an actor’s career

    For decades, major studios decided which films performers made, how they dressed, what interviews they gave, and even how they appeared in public, leaving many actors with little control over their own image.

    ©Wikimedia Commons

    The Oscars weren’t televised until 1953

    For more than two decades, the Academy Awards had no television audience. Once the ceremony entered American living rooms, it quickly became one of Hollywood’s biggest annual events.

    The post 15 Facts from the Troubled History of Hollywood appeared first on Den of Geek.

  • 15 People Share Sitcoms With the Most Unlikable Main Characters

    15 People Share Sitcoms With the Most Unlikable Main Characters

    Every long-running sitcom has at least one character who gets under someone’s skin. Sometimes that’s exactly the point. A selfish lead, an overconfident know-it-all, or someone who never seems to learn from their mistakes can keep a comedy moving for years. The problem is that not every viewer finds those personalities entertaining. While plenty of sitcom stars have become television icons, others inspire endless debates about whether they’re funny or simply exhausting to spend time with.

    These are the sitcoms with the most unlikable main characters.

    The post 15 People Share Sitcoms With the Most Unlikable Main Characters appeared first on Den of Geek.

    In the early days of Hollywood, movie studios controlled almost every part of an actor’s career. They decided which roles performers accepted, how they looked in public, and sometimes even what they could say in interviews. That level of control was only one chapter in an industry shaped by censorship battles, political investigations, labor disputes, and legal fights that changed filmmaking forever.

    Here are 15 facts from the troubled history of Hollywood.

    ©Wikimedia Commons

    The Hollywood Blacklist

    During the late 1940s and 1950s, hundreds of writers, directors, and actors found themselves unable to work after being accused of communist sympathies. Many were never formally charged with a crime, yet their careers were effectively put on hold for years.

    ©Wikimedia Commons

    The Hays Code changed what audiences could see

    For more than three decades, Hollywood followed strict censorship rules that limited everything from romance and violence to crime and even the way married couples could be shown on screen.

    ©Wikimedia Commons

    Olivia de Havilland challenged the studio system

    In 1943, Olivia de Havilland successfully sued Warner Bros., helping actors escape restrictive long-term contracts that had given studios enormous control over their careers.

    ©Wikimedia Commons

    The Paramount Decree broke up Hollywood’s biggest monopoly

    A landmark 1948 court ruling forced major studios to sell their theater chains, changing the way movies were distributed across the United States.

    ©Wikimedia Commons

    Judy Garland paid the price of becoming a child star

    While working under MGM, Garland was reportedly given pills to help control her weight and energy levels, highlighting the intense pressure young performers often faced during Hollywood’s Golden Age.

    ©Wikimedia Commons

    United Artists was created to give filmmakers more control

    Charlie Chaplin, Mary Pickford, Douglas Fairbanks, and D.W. Griffith founded United Artists in 1919 because they wanted greater creative and financial independence from the major studios.

    ©Wikimedia Commons

    Sound movies changed Hollywood almost overnight

    When talking pictures replaced silent films, many actors struggled to adapt because of their voices, accents, or performance style. Some of the biggest stars of the silent era quickly disappeared from the spotlight.

    ©Wikimedia Commons

    Movie ratings replaced strict censorship

    In 1968, Hollywood abandoned the Hays Code and introduced the MPAA ratings system instead. Filmmakers gained much more creative freedom while audiences received clearer guidance about movie content.

    ©Wikimedia Commons

    The 2007 writers’ strike brought productions to a halt

    Television series and movie projects across Hollywood were delayed for months as writers fought for better compensation in the early days of streaming and digital distribution.

    ©Wikimedia Commons

    The 2023 Hollywood strikes focused on streaming and AI

    Writers and actors walked picket lines together while negotiating higher streaming residuals, better working conditions, and protections against the growing use of artificial intelligence.

    ©Wikimedia Commons

    Hattie McDaniel made history but still faced segregation

    After becoming the first Black performer to win an Academy Award in 1940, McDaniel was required to sit at a separate table because the ceremony took place in a segregated hotel.

    ©Wikimedia Commons

    Charlie Chaplin became a political target

    During the Red Scare, Chaplin was accused of having communist sympathies. Although he was never convicted of a crime, the controversy contributed to his decision to settle in Europe.

    ©Wikimedia Commons

    The Fatty Arbuckle scandal transformed Hollywood’s public image

    Roscoe “Fatty” Arbuckle was acquitted after being accused in one of Hollywood’s earliest major scandals, but the case permanently damaged his career and pushed studios to exercise tighter control over their stars’ public reputations.

    ©Wikimedia Commons

    Studios once controlled nearly every part of an actor’s career

    For decades, major studios decided which films performers made, how they dressed, what interviews they gave, and even how they appeared in public, leaving many actors with little control over their own image.

    ©Wikimedia Commons

    The Oscars weren’t televised until 1953

    For more than two decades, the Academy Awards had no television audience. Once the ceremony entered American living rooms, it quickly became one of Hollywood’s biggest annual events.

    The post 15 Facts from the Troubled History of Hollywood appeared first on Den of Geek.

  • 15 Movies We Can’t Watch Because They’re Too Good

    15 Movies We Can’t Watch Because They’re Too Good

    Some movies are easy to revisit no matter how many times you’ve seen them. Others demand so much emotionally that even thinking about pressing play again feels like a challenge. It’s not because they aren’t great. In many cases, they’re among the best films ever made. They simply hit so hard that one viewing is enough for a while. Whether it’s heartbreak, grief, fear, or pure emotional exhaustion, these are the movies people often describe as masterpieces they struggle to watch again.

    Here are 15 movies we can’t watch because they’re too good.

    The post 15 Movies We Can’t Watch Because They’re Too Good appeared first on Den of Geek.

    In the early days of Hollywood, movie studios controlled almost every part of an actor’s career. They decided which roles performers accepted, how they looked in public, and sometimes even what they could say in interviews. That level of control was only one chapter in an industry shaped by censorship battles, political investigations, labor disputes, and legal fights that changed filmmaking forever.

    Here are 15 facts from the troubled history of Hollywood.

    ©Wikimedia Commons

    The Hollywood Blacklist

    During the late 1940s and 1950s, hundreds of writers, directors, and actors found themselves unable to work after being accused of communist sympathies. Many were never formally charged with a crime, yet their careers were effectively put on hold for years.

    ©Wikimedia Commons

    The Hays Code changed what audiences could see

    For more than three decades, Hollywood followed strict censorship rules that limited everything from romance and violence to crime and even the way married couples could be shown on screen.

    ©Wikimedia Commons

    Olivia de Havilland challenged the studio system

    In 1943, Olivia de Havilland successfully sued Warner Bros., helping actors escape restrictive long-term contracts that had given studios enormous control over their careers.

    ©Wikimedia Commons

    The Paramount Decree broke up Hollywood’s biggest monopoly

    A landmark 1948 court ruling forced major studios to sell their theater chains, changing the way movies were distributed across the United States.

    ©Wikimedia Commons

    Judy Garland paid the price of becoming a child star

    While working under MGM, Garland was reportedly given pills to help control her weight and energy levels, highlighting the intense pressure young performers often faced during Hollywood’s Golden Age.

    ©Wikimedia Commons

    United Artists was created to give filmmakers more control

    Charlie Chaplin, Mary Pickford, Douglas Fairbanks, and D.W. Griffith founded United Artists in 1919 because they wanted greater creative and financial independence from the major studios.

    ©Wikimedia Commons

    Sound movies changed Hollywood almost overnight

    When talking pictures replaced silent films, many actors struggled to adapt because of their voices, accents, or performance style. Some of the biggest stars of the silent era quickly disappeared from the spotlight.

    ©Wikimedia Commons

    Movie ratings replaced strict censorship

    In 1968, Hollywood abandoned the Hays Code and introduced the MPAA ratings system instead. Filmmakers gained much more creative freedom while audiences received clearer guidance about movie content.

    ©Wikimedia Commons

    The 2007 writers’ strike brought productions to a halt

    Television series and movie projects across Hollywood were delayed for months as writers fought for better compensation in the early days of streaming and digital distribution.

    ©Wikimedia Commons

    The 2023 Hollywood strikes focused on streaming and AI

    Writers and actors walked picket lines together while negotiating higher streaming residuals, better working conditions, and protections against the growing use of artificial intelligence.

    ©Wikimedia Commons

    Hattie McDaniel made history but still faced segregation

    After becoming the first Black performer to win an Academy Award in 1940, McDaniel was required to sit at a separate table because the ceremony took place in a segregated hotel.

    ©Wikimedia Commons

    Charlie Chaplin became a political target

    During the Red Scare, Chaplin was accused of having communist sympathies. Although he was never convicted of a crime, the controversy contributed to his decision to settle in Europe.

    ©Wikimedia Commons

    The Fatty Arbuckle scandal transformed Hollywood’s public image

    Roscoe “Fatty” Arbuckle was acquitted after being accused in one of Hollywood’s earliest major scandals, but the case permanently damaged his career and pushed studios to exercise tighter control over their stars’ public reputations.

    ©Wikimedia Commons

    Studios once controlled nearly every part of an actor’s career

    For decades, major studios decided which films performers made, how they dressed, what interviews they gave, and even how they appeared in public, leaving many actors with little control over their own image.

    ©Wikimedia Commons

    The Oscars weren’t televised until 1953

    For more than two decades, the Academy Awards had no television audience. Once the ceremony entered American living rooms, it quickly became one of Hollywood’s biggest annual events.

    The post 15 Facts from the Troubled History of Hollywood appeared first on Den of Geek.

  • The 15 Best Movies to Watch When You’re Getting Over a Breakup

    The 15 Best Movies to Watch When You’re Getting Over a Breakup

    Getting over a breakup doesn’t look the same for everyone. Some people want a movie that lets them cry for two hours, while others would rather laugh, get distracted, or watch someone else put their life back together. That’s probably why there isn’t one perfect breakup movie. The best choice depends on what you need that day. Whether it’s a story about moving on, finding confidence again, or simply remembering that life keeps going, certain films have a way of making the process feel a little less lonely.

    Here are 15 movies to watch when you’re getting over a breakup.

    The post The 15 Best Movies to Watch When You’re Getting Over a Breakup appeared first on Den of Geek.

    In the early days of Hollywood, movie studios controlled almost every part of an actor’s career. They decided which roles performers accepted, how they looked in public, and sometimes even what they could say in interviews. That level of control was only one chapter in an industry shaped by censorship battles, political investigations, labor disputes, and legal fights that changed filmmaking forever.

    Here are 15 facts from the troubled history of Hollywood.

    ©Wikimedia Commons

    The Hollywood Blacklist

    During the late 1940s and 1950s, hundreds of writers, directors, and actors found themselves unable to work after being accused of communist sympathies. Many were never formally charged with a crime, yet their careers were effectively put on hold for years.

    ©Wikimedia Commons

    The Hays Code changed what audiences could see

    For more than three decades, Hollywood followed strict censorship rules that limited everything from romance and violence to crime and even the way married couples could be shown on screen.

    ©Wikimedia Commons

    Olivia de Havilland challenged the studio system

    In 1943, Olivia de Havilland successfully sued Warner Bros., helping actors escape restrictive long-term contracts that had given studios enormous control over their careers.

    ©Wikimedia Commons

    The Paramount Decree broke up Hollywood’s biggest monopoly

    A landmark 1948 court ruling forced major studios to sell their theater chains, changing the way movies were distributed across the United States.

    ©Wikimedia Commons

    Judy Garland paid the price of becoming a child star

    While working under MGM, Garland was reportedly given pills to help control her weight and energy levels, highlighting the intense pressure young performers often faced during Hollywood’s Golden Age.

    ©Wikimedia Commons

    United Artists was created to give filmmakers more control

    Charlie Chaplin, Mary Pickford, Douglas Fairbanks, and D.W. Griffith founded United Artists in 1919 because they wanted greater creative and financial independence from the major studios.

    ©Wikimedia Commons

    Sound movies changed Hollywood almost overnight

    When talking pictures replaced silent films, many actors struggled to adapt because of their voices, accents, or performance style. Some of the biggest stars of the silent era quickly disappeared from the spotlight.

    ©Wikimedia Commons

    Movie ratings replaced strict censorship

    In 1968, Hollywood abandoned the Hays Code and introduced the MPAA ratings system instead. Filmmakers gained much more creative freedom while audiences received clearer guidance about movie content.

    ©Wikimedia Commons

    The 2007 writers’ strike brought productions to a halt

    Television series and movie projects across Hollywood were delayed for months as writers fought for better compensation in the early days of streaming and digital distribution.

    ©Wikimedia Commons

    The 2023 Hollywood strikes focused on streaming and AI

    Writers and actors walked picket lines together while negotiating higher streaming residuals, better working conditions, and protections against the growing use of artificial intelligence.

    ©Wikimedia Commons

    Hattie McDaniel made history but still faced segregation

    After becoming the first Black performer to win an Academy Award in 1940, McDaniel was required to sit at a separate table because the ceremony took place in a segregated hotel.

    ©Wikimedia Commons

    Charlie Chaplin became a political target

    During the Red Scare, Chaplin was accused of having communist sympathies. Although he was never convicted of a crime, the controversy contributed to his decision to settle in Europe.

    ©Wikimedia Commons

    The Fatty Arbuckle scandal transformed Hollywood’s public image

    Roscoe “Fatty” Arbuckle was acquitted after being accused in one of Hollywood’s earliest major scandals, but the case permanently damaged his career and pushed studios to exercise tighter control over their stars’ public reputations.

    ©Wikimedia Commons

    Studios once controlled nearly every part of an actor’s career

    For decades, major studios decided which films performers made, how they dressed, what interviews they gave, and even how they appeared in public, leaving many actors with little control over their own image.

    ©Wikimedia Commons

    The Oscars weren’t televised until 1953

    For more than two decades, the Academy Awards had no television audience. Once the ceremony entered American living rooms, it quickly became one of Hollywood’s biggest annual events.

    The post 15 Facts from the Troubled History of Hollywood appeared first on Den of Geek.

  • The 15 Perfect TV Shows for 2000s Teenagers

    The 15 Perfect TV Shows for 2000s Teenagers

    There was something special about growing up with TV in the 2000s. You couldn’t binge an entire season over the weekend or skip straight to the ending. If you missed an episode, you either waited for a rerun or hoped one of your friends would tell you what happened. That made every new episode feel like an event, especially when everyone at school was watching the same shows. Whether you were following the drama in Tree Hill, spending afternoons in Stars Hollow, or wondering what chaos would hit Newport Beach next, these series became a huge part of growing up for an entire generation.

    Here are 15 TV shows for 2000s teenagers.

    The post The 15 Perfect TV Shows for 2000s Teenagers appeared first on Den of Geek.

    In the early days of Hollywood, movie studios controlled almost every part of an actor’s career. They decided which roles performers accepted, how they looked in public, and sometimes even what they could say in interviews. That level of control was only one chapter in an industry shaped by censorship battles, political investigations, labor disputes, and legal fights that changed filmmaking forever.

    Here are 15 facts from the troubled history of Hollywood.

    ©Wikimedia Commons

    The Hollywood Blacklist

    During the late 1940s and 1950s, hundreds of writers, directors, and actors found themselves unable to work after being accused of communist sympathies. Many were never formally charged with a crime, yet their careers were effectively put on hold for years.

    ©Wikimedia Commons

    The Hays Code changed what audiences could see

    For more than three decades, Hollywood followed strict censorship rules that limited everything from romance and violence to crime and even the way married couples could be shown on screen.

    ©Wikimedia Commons

    Olivia de Havilland challenged the studio system

    In 1943, Olivia de Havilland successfully sued Warner Bros., helping actors escape restrictive long-term contracts that had given studios enormous control over their careers.

    ©Wikimedia Commons

    The Paramount Decree broke up Hollywood’s biggest monopoly

    A landmark 1948 court ruling forced major studios to sell their theater chains, changing the way movies were distributed across the United States.

    ©Wikimedia Commons

    Judy Garland paid the price of becoming a child star

    While working under MGM, Garland was reportedly given pills to help control her weight and energy levels, highlighting the intense pressure young performers often faced during Hollywood’s Golden Age.

    ©Wikimedia Commons

    United Artists was created to give filmmakers more control

    Charlie Chaplin, Mary Pickford, Douglas Fairbanks, and D.W. Griffith founded United Artists in 1919 because they wanted greater creative and financial independence from the major studios.

    ©Wikimedia Commons

    Sound movies changed Hollywood almost overnight

    When talking pictures replaced silent films, many actors struggled to adapt because of their voices, accents, or performance style. Some of the biggest stars of the silent era quickly disappeared from the spotlight.

    ©Wikimedia Commons

    Movie ratings replaced strict censorship

    In 1968, Hollywood abandoned the Hays Code and introduced the MPAA ratings system instead. Filmmakers gained much more creative freedom while audiences received clearer guidance about movie content.

    ©Wikimedia Commons

    The 2007 writers’ strike brought productions to a halt

    Television series and movie projects across Hollywood were delayed for months as writers fought for better compensation in the early days of streaming and digital distribution.

    ©Wikimedia Commons

    The 2023 Hollywood strikes focused on streaming and AI

    Writers and actors walked picket lines together while negotiating higher streaming residuals, better working conditions, and protections against the growing use of artificial intelligence.

    ©Wikimedia Commons

    Hattie McDaniel made history but still faced segregation

    After becoming the first Black performer to win an Academy Award in 1940, McDaniel was required to sit at a separate table because the ceremony took place in a segregated hotel.

    ©Wikimedia Commons

    Charlie Chaplin became a political target

    During the Red Scare, Chaplin was accused of having communist sympathies. Although he was never convicted of a crime, the controversy contributed to his decision to settle in Europe.

    ©Wikimedia Commons

    The Fatty Arbuckle scandal transformed Hollywood’s public image

    Roscoe “Fatty” Arbuckle was acquitted after being accused in one of Hollywood’s earliest major scandals, but the case permanently damaged his career and pushed studios to exercise tighter control over their stars’ public reputations.

    ©Wikimedia Commons

    Studios once controlled nearly every part of an actor’s career

    For decades, major studios decided which films performers made, how they dressed, what interviews they gave, and even how they appeared in public, leaving many actors with little control over their own image.

    ©Wikimedia Commons

    The Oscars weren’t televised until 1953

    For more than two decades, the Academy Awards had no television audience. Once the ceremony entered American living rooms, it quickly became one of Hollywood’s biggest annual events.

    The post 15 Facts from the Troubled History of Hollywood appeared first on Den of Geek.

  • 15 TV Shows With the Most Repetitive Plots

    15 TV Shows With the Most Repetitive Plots

    Some TV shows become comfort watches because you always know what you’re going to get. The same conflicts, familiar character dynamics, and predictable endings can be part of the appeal. Other times, though, a series leans so heavily on one formula that every episode starts to feel almost interchangeable. That doesn’t necessarily make these shows bad. In fact, several were huge hits that ran for years. Still, once you notice the pattern, it’s hard to stop seeing it.

    These are 15 TV shows with the most repetitive plots.

    The post 15 TV Shows With the Most Repetitive Plots appeared first on Den of Geek.

    In the early days of Hollywood, movie studios controlled almost every part of an actor’s career. They decided which roles performers accepted, how they looked in public, and sometimes even what they could say in interviews. That level of control was only one chapter in an industry shaped by censorship battles, political investigations, labor disputes, and legal fights that changed filmmaking forever.

    Here are 15 facts from the troubled history of Hollywood.

    ©Wikimedia Commons

    The Hollywood Blacklist

    During the late 1940s and 1950s, hundreds of writers, directors, and actors found themselves unable to work after being accused of communist sympathies. Many were never formally charged with a crime, yet their careers were effectively put on hold for years.

    ©Wikimedia Commons

    The Hays Code changed what audiences could see

    For more than three decades, Hollywood followed strict censorship rules that limited everything from romance and violence to crime and even the way married couples could be shown on screen.

    ©Wikimedia Commons

    Olivia de Havilland challenged the studio system

    In 1943, Olivia de Havilland successfully sued Warner Bros., helping actors escape restrictive long-term contracts that had given studios enormous control over their careers.

    ©Wikimedia Commons

    The Paramount Decree broke up Hollywood’s biggest monopoly

    A landmark 1948 court ruling forced major studios to sell their theater chains, changing the way movies were distributed across the United States.

    ©Wikimedia Commons

    Judy Garland paid the price of becoming a child star

    While working under MGM, Garland was reportedly given pills to help control her weight and energy levels, highlighting the intense pressure young performers often faced during Hollywood’s Golden Age.

    ©Wikimedia Commons

    United Artists was created to give filmmakers more control

    Charlie Chaplin, Mary Pickford, Douglas Fairbanks, and D.W. Griffith founded United Artists in 1919 because they wanted greater creative and financial independence from the major studios.

    ©Wikimedia Commons

    Sound movies changed Hollywood almost overnight

    When talking pictures replaced silent films, many actors struggled to adapt because of their voices, accents, or performance style. Some of the biggest stars of the silent era quickly disappeared from the spotlight.

    ©Wikimedia Commons

    Movie ratings replaced strict censorship

    In 1968, Hollywood abandoned the Hays Code and introduced the MPAA ratings system instead. Filmmakers gained much more creative freedom while audiences received clearer guidance about movie content.

    ©Wikimedia Commons

    The 2007 writers’ strike brought productions to a halt

    Television series and movie projects across Hollywood were delayed for months as writers fought for better compensation in the early days of streaming and digital distribution.

    ©Wikimedia Commons

    The 2023 Hollywood strikes focused on streaming and AI

    Writers and actors walked picket lines together while negotiating higher streaming residuals, better working conditions, and protections against the growing use of artificial intelligence.

    ©Wikimedia Commons

    Hattie McDaniel made history but still faced segregation

    After becoming the first Black performer to win an Academy Award in 1940, McDaniel was required to sit at a separate table because the ceremony took place in a segregated hotel.

    ©Wikimedia Commons

    Charlie Chaplin became a political target

    During the Red Scare, Chaplin was accused of having communist sympathies. Although he was never convicted of a crime, the controversy contributed to his decision to settle in Europe.

    ©Wikimedia Commons

    The Fatty Arbuckle scandal transformed Hollywood’s public image

    Roscoe “Fatty” Arbuckle was acquitted after being accused in one of Hollywood’s earliest major scandals, but the case permanently damaged his career and pushed studios to exercise tighter control over their stars’ public reputations.

    ©Wikimedia Commons

    Studios once controlled nearly every part of an actor’s career

    For decades, major studios decided which films performers made, how they dressed, what interviews they gave, and even how they appeared in public, leaving many actors with little control over their own image.

    ©Wikimedia Commons

    The Oscars weren’t televised until 1953

    For more than two decades, the Academy Awards had no television audience. Once the ceremony entered American living rooms, it quickly became one of Hollywood’s biggest annual events.

    The post 15 Facts from the Troubled History of Hollywood appeared first on Den of Geek.