CEO & Founder @themothershipai. A platform building consumer brands to their full potential | Founder @FastGrowthIcons

London
Joined October 2009
The World is Changing: AI For Creativity By Jeffrey Katzenberg A few months ago, I sat in my office in Silicon Valley and watched as a tech founder showed me something extraordinary. On the screen was a fully realized, beautifully lit, well-composed animated scene. It was stunning and it made me feel exactly what I felt in 1986 watching Luxo Jr. That was the first time I watched a computer-animated 3D character take a breath and seem, against all reason, to have life. It left me in awe. Later that day, I received a text from an artist I've known for thirty years, 350 miles to the south, in the city where I spent most of my career. After seeing a similar video, she texted: "Is this the end of us?" My answer was, "Certainly not.” I have spent the better part of the last decade in Silicon Valley, but the heart of my career has been in Hollywood. Being deeply connected to both worlds means I have deep loyalties to each and a responsibility to speak honestly to both. In 2023, I said that these new AI tools would cut the time and cost of producing world-class animation by as much as ninety percent within three years. Some colleagues were alarmed, many were furious. There is growing fear and resistance surrounding AI within the creative community. I deeply understand it, because I've spent countless hours walking through animation studios watching gifted artists bent over their desks, rebuilding a single second of film for the tenth time because the ninth version wasn't quite right. I've sat in screening rooms where four years of people's labor played out in minutes, and I knew the name of every person that had spent countless hours bringing those images to life. The creative process is a calling, there's really no other way to describe it. From the outside some see resistance. From the inside, it is love. People do not fight this hard for things they don't care about. The pushback coming out of Hollywood represents the collective effort of people who are deeply passionate about their craft. Is History Repeating Itself? The history here is more complicated than either side may realize. In 1906, the most famous composer in America, John Philip Sousa, published an essay titled “The Menace of Mechanical Music." He warned that the phonograph would become "a substitute for human skill, intelligence and soul." Sousa's fight was not really about the machine, it was about money. The machines were playing his compositions, and the men who built them weren't paying him a cent. His campaign helped create the Copyright Act of 1909. He did not stop the technology. He changed the terms under which it could use his work. A hundred years ago, sound came to the movies. We remember it now as a miracle, and it was. What we forget is who paid for it. Before sound, tens of thousands of musicians made their living in the orchestra pits of movie houses, scoring every film live, every night, in towns all over the world. When the soundtrack arrived, the work of one composer and one orchestra was recorded for a film that went into thousands of theaters. The union fought back with everything it had, taking out newspaper ads across the country warning against the menace of "canned music," one of them showing a mechanical man tearing the strings out of a harp while an angel wept. They were not fools, and they were not Luddites. They were right. Those pit jobs did not come back. And yet (this is the part we have to be brave enough to admit), sound gave us the movie musical, the modern score, sfx, sound design, audio engineering, and an art form vastly larger than the one it disrupted. And it helped keep Hollywood in the forefront of world entertainment for the rest of the century and into the next. The loss was real. And yet the art form expanded. This is a story that has been told over and over again. To resist technology is to risk irrelevance. Just look at Kodak or Blockbuster. To embrace technology is to open doors of new possibility. Just consider Apple and Netflix. What I Learned From Walt Disney In the mid-1980s, I was tapped to lead Disney's animation division at a moment when the studio was at an inflection point. Animation wasn't just another business unit. It was the soul of the company, a medium revered because of Walt's genius and his passion. But the production system was cumbersome and unforgiving. A single movie was 125,000 individual hand-drawn and painted cels, photographed one frame at a time. Every revision carried a cost measured in months. These degrees of difficulty shaped the kinds of stories we could tell. We found our way forward in an unexpected place: Walt himself. The Disney archives held astonishing recordings of Walt explaining his creative process. His own writings. His notes and storyboards. Work product captured at every stage of his process. This was truly a gift. Listening, reading, sitting with the work itself, we heard him talk about character, about emotion, about how an audience feels when a character truly comes alive. He talked about making bold choices and refining a scene until it genuinely moved people. We didn't hear a word about pencils or paintbrushes. In fact, Walt was famous for being a technologist, forever hunting for state-of-the-art tools, often inventing them himself to achieve the images he saw in his head. But he never defined animation by the tools. He defined it by whether the audience believed the character. His principles were timeless. The tools were not. That realization changed everything. We co-developed the Computer Animation Production System (CAPS) with a young Northern California company called Pixar, replacing hand-painted cels with CGI. In The Little Mermaid, the final scene shimmered with a dimensionality and light that the old process simply couldn't achieve. In Beauty and the Beast, the ballroom sequence moved with a cinematic sweep that placed the audience inside the emotion of the moment. In Aladdin, the Cave of Wonders felt vast and alive, and the Magic Carpet became an intricate, compelling character all its own. In The Lion King, the stampede carried a scale and intensity that raised the emotional stakes beyond anything we'd done before. Technology didn't diminish the craft, it expanded the canvas. It gave artists more room to create. A decade later, the canvas expanded again. When Disney released Pixar's Toy Story, it wasn't simply a technical milestone. It was proof that a fully computer-animated film could carry real emotional weight, that it could make audiences laugh, cry, and believe. At DreamWorks, we made the difficult decision to sunset hand-drawn animation and become a fully computer-animated studio. It was the right thing to do, but it was not without pain. It cost talented people their place in an industry where they had worked their whole lives. Some made the leap to the new tools and did the finest work of their careers. Some never did. Tools are never the point. The instruments change with every generation. What endures is taste and imagination. The magical ability to make an audience feel. One of the greatest storytellers of our generation, George Lucas, succinctly captured the eternal essence of this issue: “It’s not the how, it’s the why.” A Distinction With a Difference I asked one of the leading AI models a question that has been challenging me for months. What is the difference between reasoning and creating? Its answer changed how I think about almost everything happening in this industry. It said . . . Reasoning and creating are two distinct cognitive modes, though they also work together. Reasoning is fundamentally evaluative and analytical. It operates on what already exists: facts, premises, evidence. It moves toward a conclusion that was in a sense already implied by the input. Reasoning is constrained by logic and truth. Its goal is to arrive somewhere correct, not to invent somewhere new. Creating is fundamentally generative. It produces something that didn't exist before. And crucially, there's no single right answer waiting to be found. A blank page has infinite valid responses. Creation involves choices that can't be fully justified by logic alone. Taste, intuition and vision fill the gap where deduction runs out. Reasoning is what Silicon Valley has been perfecting. Creating is what Hollywood has been practicing for more than a century. AI today operates almost entirely on the reasoning side of the line. It can deduce, evaluate, optimize, and pattern-match brilliantly. And while it can create, there is a real distinction to being creative. What it doesn’t yet have is those things that make us human: empathy, devotion, serendipity, the kind of creativity that comes from a person trying to say something only they could say. When the bot generates a piece of art, it is not trying to communicate anything. It is statistics, not soul; it is emulating things that have been done. By contrast, human creativity isn’t about repeating patterns of zeros and ones; it is about doing something new. One day, AI may close this gap. Three years ago, the leaders building AI would have called what they are achieving today, improbable, if not impossible. Impossible is no longer improbable. Today, the line between reasoning and creating is real. Even the leading technologists acknowledge we are not there yet. There is no scientific path to crossing this divide that anyone in the field can articulate today. Understanding that gap is where we will find common ground. A Path Forward In 2016, I closed one chapter in Hollywood with the sale of DreamWorks and opened another in Northern California, co-founding WndrCo. We’ve backed more than 50 founders building the next generation of technology and watched how breakthroughs in Silicon Valley emerge, first as experiments, then as platforms, and finally as infrastructure that reshapes entire industries. It's worth remembering that the last great revolution in animation also came from the north. Pixar was a Northern California company, forged not in the conventions of the Hollywood studio system, but in the technological breakthroughs of Silicon Valley. I've spent years on both sides of this bridge. For sure, I don’t have all the answers (take Quibi, for one!). But, from my past and present vantage points of my long career, here is what I see . . . Brilliant people in Northern California building this technology have made something extraordinary. They have earned the right for the rest of us to be, if not believers, at least optimistic that what comes next will be remarkable. But they have not made an artist. The tools are powerful, but they are not what makes a story matter. That knowledge lives 350 miles to the south, inside people whose life's work has informed the very models you are building. The right path forward includes them by design, with credit, with consent, and with compensation. Build this with the storytellers. Not on top of them. Taste is not something that can be synthesized, it is uniquely human. At the same time, Hollywood needs to accept that AI is not going away. The energy they are spending trying to make it disappear is energy they are not spending deciding the terms on which it will exist. And the terms are everything. The north needs something from it that they cannot build and cannot buy: creativity. The kind that takes a blank page and conjures a single right answer where there was none and has held audiences for a century. Without it, the most powerful reasoning engine ever invented will still be missing the only thing that makes a story worth telling. The artists who learn to wield these new instruments will do things the engineers never dreamed of. They always have. Edison invented the motion picture but made terrible movies. It took Chaplin, Lloyd, Keaton and so many others to make movies emotional. Now, the canvas is about to expand yet again. We should decide now that we intend to paint on it. There are so many valuable lessons in history. This has happened many times before, and it was never settled by the technology. It was settled by the terms. Sousa did not stop the phonograph; he helped write the law that made sure composers got paid. And two years ago, when the writers and the actors walked out, they were fighting for the very things Sousa was fighting for in 1906. Consent, compensation, the basic recognition that human creative work has a price that must be paid. The terms of that fight are still being negotiated, but the principle is older than any of us. The tools-versus-no-tools argument is a trap. First, we must all agree that there should be terms. Then we can have the crucial debate about what fairness requires. What I Learned From Steve Jobs Years ago, Steve Jobs said, "It's in Apple's DNA that technology alone is not enough. It's technology married with the liberal arts, married with the humanities, that yields us the result that makes our hearts sing." He was describing a device. But he could just as easily have been describing this tale of two cities. What I See Coming Soon As the barriers and the costs come down, more films will get made, not fewer. Studios will get to take more risks. There will be more seats at the table, and very soon entirely new forms of storytelling. In the 1980s, animation was dismissed as a niche corner of the business. Today it is one of the most beloved and profitable forms of storytelling in the world. In live action, filmmakers like Steven Spielberg, James Cameron and Peter Jackson embraced new visual tools not as shortcuts, but as instruments, and expanded cinema in the process. Every time storytelling has met a genuine technological shift, from synchronized sound to color to computer animation, it has redefined the boundaries of the medium and grown larger in the process. Assuredly, I don’t have all the answers, but I am confident that the creative opportunities will expand yet again. How we come through this is a choice. The north has the new tools. The south has the creative soul. The best future will draw on the best of both worlds.
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Ben Fletcher retweeted
I completely agree with this take related to the “AI will create viruses that will kill us all” BS. But let me add my few cents, because I am really really angry! I worked with one of the deadliest viruses in history, HIV, for two decades. I was one of the early scientists to engineer it, and engineered versions of HIV are now helping cancer patients. I understand the immune system that defends us against viruses extremely deeply. I have worked in high security biohazard labs. I don’t have a PhD in AI, but I have been involved with AI since the early 90s and have been all in on AI for years. People claiming that you can just make a virus in your garage, use AI to engineer it, and somehow build a virus that will kill everyone don’t know what the hell they are talking about! Of course bioweapons are extremely dangerous. In fact, viruses and bacteria have killed more humans throughout history than almost anything else. HIV alone killed tens of millions of people, yet today, if you have access to effective medicines and take them properly, HIV is generally no longer a death sentence. COVID-19 killed millions. Why doesn’t it kill at anything close to the same scale anymore? Not because the virus disappeared. It is still here. We developed collective defenses against it through our immune systems, prior exposure, vaccines, treatments, and better medical care. And this is exactly the point. The best way to fight biological threats, whether natural or synthetic, is to use AI to develop vaccines, treatments, antibodies, antivirals, and eventually engineer our immune system to create much stronger defenses against them. By the way, it is already possible to make synthetic viruses. You don’t need some hypothetical superintelligent AI model to do that. We have had sophisticated molecular biology and genetic engineering for decades. So how many people have actually died from synthetic viruses compared with natural viruses killing millions every year? And if someday there really is an AI capable of making some unbelievable “supervirus,” then why the hell wouldn’t that same AI make it even easier to develop defenses against it? Or cure diseases, for that matter? Where is this damn superintelligence that has cured a single major disease?! These AI companies and AI doomers keep talking like, “OMG, AI is going to become so unbelievably powerful that it could kill all of humanity!” Then why is nobody asking the obvious question? If your AI is already becoming this godlike, unbelievably powerful intelligence, why hasn’t it cured anything? I mean ANYTHING. Where is the cure for cancer? Where is the cure for Alzheimer’s? Where is the cure for aging? Forget those. Where is the vaccine that prevents the common cold? You are telling me this intelligence will soon be smart enough to engineer some magical virus capable of wiping out 8 billion people, defeating every immune system, every vaccine, every antiviral, every laboratory, every government, and the entire global biomedical community… …but somehow it still can’t cure one disease? I call that greatest intellectual dishonesty ever! At least WE actually know how to cure things and save millions of lives with our supposedly stupid human intelligence compared with this future “superintelligence.” Humans eradicated smallpox, which killed hundreds of millions of people throughout history. We turned HIV from a almost certain death sentence into a manageable disease. We developed vaccines in record time against COVID. If we had the same AI back then, would have saved millions more! We engineer immune cells to kill cancer. We developed antibiotics, antivirals, monoclonal antibodies, gene therapies, organ transplantation, and thousands of medicines. We aren't fast enough but we did all of that with our ordinary human intelligence. So imagine what actual superintelligence could do for medicine! And here is the part that really makes me angry. If you actually have, or are close to having, an AI capable of curing diseases and saving millions of lives, and you are deliberately slowing it down or refusing to make those capabilities available, then we also need to talk about the human cost of THAT decision, which you fearmongering people are going to be responsible for! More than 150,000 people die every single day around the world. Every. Single. Day. More than 90% from Cancer, heart disease, infections, aging. How many die because of AI? ZERO! Talk about the people dying TODAY. Talk about curing cancer. Talk about stopping the next pandemic before it starts. Talk about developing universal vaccines. Talk about engineering our immune system so viruses become almost irrelevant. Talk about curing genetic diseases. Talk about reversing aging. Talk about saving millions and eventually billions of lives. Instead, we constantly hear this “AI WILL KILL US ALL!” crap, delivered with absolute certainty and with this smug smile on your faces in front of cameras, as though imagining a science fiction extinction scenarios. I am actually angry about this. Each one of you causing a delay in AI advance every single day will be personally responsible for those 100 thousands deaths that could have been prevented! Because if you truly believe intelligence is about to become this powerful, then the greatest question humanity should be asking is NOT: “How could this intelligence hurt us?” It should also be: “WHY THE HELL AREN’T WE USING IT TO SAVE EVERYONE WE CAN?” And if superintelligence really is coming, then make sure one of the first things we do with it is make humanity biologically damn near impossible to kill.
Well, I’d add one more with myself, as one with a PhD in biology and another PhD in AI and now working in both, to make n=2. Generating a hypothetical genome blueprint of a virus from LLM versus generating a true virus are completely different things. It is either an intentional attention-harnessing lie or true ignorance. The material, the manufacturing, and actual biological viability of paper-to-physical transformation is the gap you need to close. Like drawing a design of a chip or A-bomb, versus actually make one. You have, and can add more checkpoints and guardrails all over this long chain of paper to physical transformation. Fear mongering is not well founded, and mostly emotional manipulation.
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Anyone else sending markdown text in emails to make them agent readable? What's best practice here?
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Wow, the anti-scam offering from companies house looks so scammy
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Ben Fletcher retweeted
When your whole thing is being a growth agency it’s pretty exciting when two of the 15 clients you worked with last year made it to onto the Times Top 100 Fastest Growing Brands list Huge well done to MOTHER ROOT ✸ and Tilly Sveaas Looking forward to seeing what % of our roster makes the 2027 list 😊
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Sometimes you see a demo and you’re like ‘wow, the future is here’. This is not that demo…
We taught two F.03 robots to clean a room and make a bed in under 2 minutes - fully autonomous.
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Holy shit… are you paying minimum wage? You have an entry level position, and that person works a ‘normal’ week - 9-5 plus an hour or two of extra work per day. 48 hours per week is £31,746 I think some startups have people working longer hours on less money…
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Ben Fletcher retweeted
This is what a properly built persona system looks like in practice. 3 micro personas. 4 angles each. 4 vehicles each. 48 genuinely distinct ads from a single macro persona. Take one macro persona: "The Conscious Parent." On paper, one audience. In reality, completely different people with completely different fears, motivators, and trigger points. That's the micro persona layer. And it's where most creative strategies stop being strategic. P1.1, P1.2, and P1.3 sit inside the same macro. Same broad demographic. But each one needs a different hook, a different setup, a different cognitive bias tapped to actually convert. An ad built for one will not land the same way with another. If you're writing to all three with the same message, you're reaching none of them properly. Here's what building to that level of specificity actually unlocks. Each one a different signal. Each signal giving Andromeda something new to work with. Each piece of creative capable of reaching a person the last one couldn't. That's how incremental reach actually grows. Not by producing more, but by covering more psychological territory with what you produce. Most accounts have far more creative territory available to them than they realise. The personas are there. The angles exist. They just haven't been mapped and briefed against each other yet.
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I built an app today on Lovable, launched it 10 mins ago and I have 5 companys signed up....
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25 companies now. And first customer issue: the pay me money button wasn't working...
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Ben Fletcher retweeted
There’s a well-known phenomenon in the facial aesthetics literature whereby “average faces” (that is, faces formed by superimposing many faces atop one another) tend to be more attractive than the average person. This may be counterintuitive, but it makes sense when you consider the following: Individual faces are all slightly flawed, from a beauty perspective, in idiosyncratic ways. And when you average lots of faces, you average out all of these minor issues. So, an “average face” is errorless and looks quite pleasant as a result. However, another thing you’ll notice about these “average faces” is that none of them could be models. They’re more attractive than the average human, yes, but less attractive than the most attractive humans. This is because extremely attractive faces tend to have certain features that are, mathematically, extreme. (For example, male models tend to have lower-set brows and larger jawbones than you would see in any average face.) Recently, I have begun to wonder if LLM-writing faces a similar challenge. It’s always “more attractive than average,” because all of the flaws of normal human writing have been averaged out. But it's also missing the unusual taste and style of the best human writers I've read. In my experience, it's only ever 85%-good; like an "average face," it's never flawed, but equally, it's never exceptionally beautiful.
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Do you think at some point, saying you use ChatGPT will be like having a Hotmail email address?
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Depends on the company
Selling 8% of your company for $125k is insane
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But also, why not 4:0? Because you could probably spend more on marketing, at a higher CAC and have higher overall profit. Ps. LTV isn’t revenue, it’s CM2 (revenue less costs of goods and delivery.
Why 3.0 LTV:CAC? Lots of people have heard they need to shoot for 3:1 in their LTV:CAC ratio but few seem to understand why. This is the explanation 👇 - At 1.0 LTV:CAC, you are just breaking even and not really creating incremental EV from getting the Nth customer, pretty much just recycling cash. - At 2.0 LTV:CAC, buying one customer returns 2× what you spent. The surplus is the “fuel” that can fund additional growth so acquiring customers actually starts to compound. - At 3.0 LTV:CAC, buying one customer creates 2× CAC of surplus. If payback is reasonable, growth begins to compound in a durable way, and EV can start scaling rapidly. More insights in newsletter
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Ben Fletcher retweeted
Why 3.0 LTV:CAC? Lots of people have heard they need to shoot for 3:1 in their LTV:CAC ratio but few seem to understand why. This is the explanation 👇 - At 1.0 LTV:CAC, you are just breaking even and not really creating incremental EV from getting the Nth customer, pretty much just recycling cash. - At 2.0 LTV:CAC, buying one customer returns 2× what you spent. The surplus is the “fuel” that can fund additional growth so acquiring customers actually starts to compound. - At 3.0 LTV:CAC, buying one customer creates 2× CAC of surplus. If payback is reasonable, growth begins to compound in a durable way, and EV can start scaling rapidly. More insights in newsletter
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Ben Fletcher retweeted
I flip cards of a randomly shuffled 52-card deck over one by one. At any point you can say "STOP" and you win if the next card flipped is black. What's your probability of winning? It turns out the answer is 50%. It feels like waiting to collect info should help but it doesn't - eg if you wait til the last card you will know for sure what it is, but it will still only be black 50% of the time. The analogy in startups is: waiting longer makes you more likely to know if you're right. But not more likely to be right. Just do things!
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I really loved the idea of the iPhone asking cold callers why they are calling. But no one leaves a meaningful one.
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