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Introducing Sherpa: the most advanced fiction writing AI We accelerated from $250M in ARR to $500M because Sherpa helped increase content production by 1200% in 1 year Sherpa was trained on 5.5B hours of playtime with minute by minute dynamic retention data. 550K+ creators have produced 2.6M hours of...

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Rohan Nayak

13,463 subscribers

6,183,731 次观看 • 8 天前 •via X (Twitter)

艺术教育科学技术
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35 条评论

Not Jerome Powell 的头像
Not Jerome Powell8 天前

2024: “AI will replace writers” 2026: writers using AI to build $100M shows from their bedroom Plot twist of the century.

muku 的头像
muku8 天前

What a fuckin COOL videooo 🐐 Great one @PocketFM_App

kanav 的头像
kanav8 天前

HOLY SHIT THEY GOT RUSS HANNEMAN 😭😭😭

punit 的头像
punit8 天前

$250M -> $500M in 1 year

Vishal Singh 🥑 的头像
Vishal Singh 🥑8 天前

there's no subscription. that's the whole trick. you listen free until the episode ends mid-confession, and then you buy coins to unlock the next one. games have monetised like this for a decade. nobody had done it to fiction. huge opportunity window here.

James Camp 🛠,🛠 的头像
James Camp 🛠,🛠8 天前

This might be my favorite launch video to date

MAX 的头像
MAX8 天前

what a banger launch video

Tuki 的头像
Tuki8 天前

This is actually such a crazy shift. The idea that one person can now go from a simple concept to a fully produced, monetized fiction series is huge. AI is making the barrier to entry ridiculously low.

HOW THINGS WORK 的头像
HOW THINGS WORK8 天前

Turning storytelling into a real income stream for creators is the most epic part here! 🔥

Vision Surge 的头像
Vision Surge8 天前

The retention data might be the most interesting part of Sherpa. Most writing tools learn from text. This sounds like it learned from where actual listeners stayed, dropped off, or kept coming back.

CG 的头像
CG8 天前

congrats on the launch, banger launch video btw 🔥

B’3M3t 0R 的头像
B’3M3t 0R8 天前

cc @mnsibley O_o increase your content production by 1200%!!! you may get the book done by 2030 now. heh

Muhammad Ayan 的头像
Muhammad Ayan8 天前

someone is absolutely about to make a 700 episode soap opera with this 💀

AshutoshShrivastava 的头像
AshutoshShrivastava8 天前

curious if the retention weighting prioritizes mid-episode cliffhangers or character conflict density.

Dev Khare 的头像
Dev Khare8 天前

🎆 🎇 🔥

Fight With Memes 的头像
Fight With Memes8 天前

As a writer, I'm both apalled and fascinated. 👀

ashesh 的头像
ashesh8 天前

crazyyyyy launch 🤣🤣🤣🤣🔥

gargi palaskar 的头像
gargi palaskar8 天前

crazy launch video

Not Kevin Warsh 的头像
Not Kevin Warsh8 天前

AI went from stealing writers’ jobs to helping writers make $1M. character development.

Linus ✦ Ekenstam 的头像
Linus ✦ Ekenstam8 天前

As someone who worked on similar software for years, sherpa is absolutely nuts.

Markandey Sharma 的头像
Markandey Sharma8 天前

Looks promising to me

Kartik 的头像
Kartik8 天前

$250M -> $500M in 1 year wow 😳

Berry 的头像
Berry8 天前

What a legend these guys are, absolute masterclass on PMF - proving everyone wrong here.

Alok Kumar 的头像
Alok Kumar8 天前

1B+ tokens of Pocket FM stories is an incredible amount of data to build a storytelling.

Science girl 的头像
Science girl8 天前

This is honestly incredible 🔥 The possibilities for storytellers are huge. Definitely excited to see what people create with Sherpa!

Dan Carl 的头像
Dan Carl8 天前

@joeroganhq Hollywood watch out!

Vox 的头像
Vox8 天前

congrats on the launch! starting my 500 episode series tonight lol

Nawi 的头像
Nawi8 天前

First fiction AI that actually gets long-form serials. Hierarchical planner + knowledge graph is the unlock. Most models mush out after 30 eps. Curious what solo creators ship with this.

Harsshh aka Chole bhature 的头像
Harsshh aka Chole bhature8 天前

damnn fuckin cooolll launch video

Mahesh KMB 的头像
Mahesh KMB8 天前

if the prose engine learns from listener retention and the evaluators are benchmarked to match human reviewers, both signals come from what already works. what keeps the loop from optimizing toward the median and filtering out the story that breaks the pattern?

Wisdom 的头像
Wisdom8 天前

5.5B hours of playtime data is a pretty wild feedback loop. You're not just teaching the model what good fiction looks like, but what actually holds attention.

Rez Karim 的头像
Rez Karim8 天前

drop-off data is the underrated imo. knowing where people quit is more useful than knowing what they liked

Deepanshu Sharma 的头像
Deepanshu Sharma8 天前

you really made the enormous content machine, if it really works as mentioned, every one can be a engaging screenplay writer

D Iceman 的头像
D Iceman8 天前

I saw this guy in The Sticky, he’s good but wtf is he doing here LOL

Aaron 的头像
Aaron8 天前

Absolutely insane what you've done here. To think that this used to take a whole ass team and thousands of hours to do. Crazy

相关视频

Dean Koontz has published more than 140 novels, 74 works of short fiction, and sold more than 500 million books. Simply put, he’s one of the most prolific writers alive today. Some highlights from our chat: 1. Dare to love the English language. 2. Characters come alive when they're given free will. Instead of constraining them in an outline, let them go where they want. You know they’re alive once they start surprising you. He says: “I give the characters free will like God gave it to us.” 3. Everything a writer believes about life and death, culture and society, relationships and the self, God and nature will wind up in their books. A writer’s body of work, therefore, reveals the intellectual and emotional progress of its creator, and over time, becomes a map of their soul. 4. To think you understand the world is to be foolish in the extreme. The world is too complex for us to understand it. To see reality clearly is to be utterly enchanted by its staggering complexity. 5. Where should you look? Well, the supernatural enters the world in mundane ways, and rarely the great and glorious flashes of drama. 6. Dean writes his novels page-by-page, and doesn’t move onto the next page until he nails the existing one. There’s no messy first draft. Because of that, he’s basically done with his novels once he finishes the final page. 7. Where does a unique writing voice come from? Three places: style, perspective, and a philosophy of life. 8. Be skeptical of conventional wisdom. There’s an encyclopedia of common wisdom in publishing. All of it is common and none of it is wise. You have to become aware of that, go your own way, and just stick with it because there are so many ways you can be sent wrong based on "that's the way we always do it." 9. The aesthetic plainness of contemporary writing (and culture at large) is crushing our souls. 10. Contemporary fiction is suffering from plainness in particular. It started when writers started imitating Hemingway (who stripped his prose down but kept the mystery and underlying strangeness of the world by implication). But the imitations that came later stripped the prose down while also removing the underlying depth that made Hemingway so great. 11. Koontz Law of Writing #1: Never go inside more than one character's mind in a scene. Each one should come from a singular viewpoint. 12. Koontz Law of Writing #2: Metaphors aren't meant to dazzle readers, but to seduce them into a more intimate relationship with the story. 13. Koontz Law of Writing #3: Metaphors and similes describe a scene more colorfully than a chain of adjectives — while reinforcing the mood. The point is that you can create depth by describing things metaphorically instead of using blunt adjectives. That’s what poetry does: it uses words to say more than the word itself says, which creates a mood. 14. Great prose doesn't come from piling on adjectives. It comes from finding the perfect metaphor that does triple duty: describes the scene, reinforces the mood, and reveals something about the character. 15. The goal is for metaphors not to pop out like showmanship, but to flow into the music of the language. 16. Develop an ear for the musicality of language. 17. A book can succeed with a mediocre plot if the characters are compelling. Character is the center of good fiction. If the characters work, the story works. 18. From the afterword of his book, Watchers: “We have within us the ability to change for the better and to find dignity as individuals rather than as drones in one mass movement or another. We have the ability to love, the need to be loved, and the willingness to put our own lives on the line to protect those we love, and it is in these aspects of ourselves that we can glimpse the face of God; and through the exercise of these qualities, we come closest to a Godlike state.” I've shared the full conversation with Dean Koontz below. The YouTube video link is in the replies, and so are the links to Apple and Spotify.
1:47:18

Dean Koontz has published more than 140 novels, 74 works of short fiction, and sold more than 500 million books. Simply put, he’s one of the most prolific writers alive today. Some highlights from our chat: 1. Dare to love the English language. 2. Characters come alive when they're given free will. Instead of constraining them in an outline, let them go where they want. You know they’re alive once they start surprising you. He says: “I give the characters free will like God gave it to us.” 3. Everything a writer believes about life and death, culture and society, relationships and the self, God and nature will wind up in their books. A writer’s body of work, therefore, reveals the intellectual and emotional progress of its creator, and over time, becomes a map of their soul. 4. To think you understand the world is to be foolish in the extreme. The world is too complex for us to understand it. To see reality clearly is to be utterly enchanted by its staggering complexity. 5. Where should you look? Well, the supernatural enters the world in mundane ways, and rarely the great and glorious flashes of drama. 6. Dean writes his novels page-by-page, and doesn’t move onto the next page until he nails the existing one. There’s no messy first draft. Because of that, he’s basically done with his novels once he finishes the final page. 7. Where does a unique writing voice come from? Three places: style, perspective, and a philosophy of life. 8. Be skeptical of conventional wisdom. There’s an encyclopedia of common wisdom in publishing. All of it is common and none of it is wise. You have to become aware of that, go your own way, and just stick with it because there are so many ways you can be sent wrong based on "that's the way we always do it." 9. The aesthetic plainness of contemporary writing (and culture at large) is crushing our souls. 10. Contemporary fiction is suffering from plainness in particular. It started when writers started imitating Hemingway (who stripped his prose down but kept the mystery and underlying strangeness of the world by implication). But the imitations that came later stripped the prose down while also removing the underlying depth that made Hemingway so great. 11. Koontz Law of Writing #1: Never go inside more than one character's mind in a scene. Each one should come from a singular viewpoint. 12. Koontz Law of Writing #2: Metaphors aren't meant to dazzle readers, but to seduce them into a more intimate relationship with the story. 13. Koontz Law of Writing #3: Metaphors and similes describe a scene more colorfully than a chain of adjectives — while reinforcing the mood. The point is that you can create depth by describing things metaphorically instead of using blunt adjectives. That’s what poetry does: it uses words to say more than the word itself says, which creates a mood. 14. Great prose doesn't come from piling on adjectives. It comes from finding the perfect metaphor that does triple duty: describes the scene, reinforces the mood, and reveals something about the character. 15. The goal is for metaphors not to pop out like showmanship, but to flow into the music of the language. 16. Develop an ear for the musicality of language. 17. A book can succeed with a mediocre plot if the characters are compelling. Character is the center of good fiction. If the characters work, the story works. 18. From the afterword of his book, Watchers: “We have within us the ability to change for the better and to find dignity as individuals rather than as drones in one mass movement or another. We have the ability to love, the need to be loved, and the willingness to put our own lives on the line to protect those we love, and it is in these aspects of ourselves that we can glimpse the face of God; and through the exercise of these qualities, we come closest to a Godlike state.” I've shared the full conversation with Dean Koontz below. The YouTube video link is in the replies, and so are the links to Apple and Spotify.

David Perell

74,956 次观看 • 1 年前

Anthropic CEO Dario Amodei just gave THE MOST accelerated talk on how scaling will continue to make models exponentially more powerful for a long time to come — and that there is "NO WALL." 🔥 - From 'Alex Kantrowitz' YT Channel (Full Video link in comment) --- "The thing I think is real that I've said over and over again is the exponential. The idea that every few months we get an AI model that is better than the AI model we got before. And we get that by investing more compute in AI models, more data, more new types of training models. Initially, this was done by what's called pre-training, which is when you just feed a bunch of data from the internet into the model. Now we have a second stage that's reinforcement learning or test time compute or reasoning or whatever you want to call it. I think of it as a second stage that involves reinforcement learning. Now both of those things are scaling up together, as we've seen with our models and as we've seen with models from other companies. I don't see anything blocking the further scaling of that. There's some stuff about how do we broaden the tasks on the RL side of it. We've seen more progress on, say, math and code, where the models are getting pretty close to a high professional level, and less on more subjective tasks, but I think that is very much a temporary obstacle. So when I look at it, I see this exponential and I say, look, people aren't very good at making sense of exponentials, right? Like, if something is doubling every 6 months, then 2 years before it happens, it looks like it's only 1/16th of the way there. And so we are sitting here in the middle of 2025, and the models are really starting to explode in terms of the economy. If you look at the capabilities of the model, they're starting to saturate all the benchmarks. If you look at revenue, and you know, Anthropic's revenue every year has grown 10x. Every year we’re kind of conservative and we say, it can’t grow 10x this time. I never assume anything and actually always am very conservative in saying I think it's going to slow down on the business side. But we went from zero to $100 million in 2023, we went from $100 million to $1 billion in 2024, and this year, in the first half of the year, we've gone from $1 billion to, I think as of speaking today, it's well above $4 billion, it might be $4.5 billion. And so if you think about it, suppose that exponential continued for 2 years. I'm not saying it will, but suppose it continued for 2 years. You're well into the $100 billions. I'm not saying that'll happen. I'm saying the situation is that when you're on an exponential, you can really get fooled by it. 2 years away from when the exponential goes totally crazy, it looks like it's just starting to be a thing. And so that's the fundamental dynamic. We saw that with the internet in the '90s, right? Where it was like networking speeds and the underlying speed of the computers were getting fast, and over a few years it became possible to have to basically build a digital global communications network on top of all this when it wasn't possible just a few years ago and and almost no one except for a few people really saw the implications of that and how fast it." - Anthropic CEO Dario Amodei
2:26

Anthropic CEO Dario Amodei just gave THE MOST accelerated talk on how scaling will continue to make models exponentially more powerful for a long time to come — and that there is "NO WALL." 🔥 - From 'Alex Kantrowitz' YT Channel (Full Video link in comment) --- "The thing I think is real that I've said over and over again is the exponential. The idea that every few months we get an AI model that is better than the AI model we got before. And we get that by investing more compute in AI models, more data, more new types of training models. Initially, this was done by what's called pre-training, which is when you just feed a bunch of data from the internet into the model. Now we have a second stage that's reinforcement learning or test time compute or reasoning or whatever you want to call it. I think of it as a second stage that involves reinforcement learning. Now both of those things are scaling up together, as we've seen with our models and as we've seen with models from other companies. I don't see anything blocking the further scaling of that. There's some stuff about how do we broaden the tasks on the RL side of it. We've seen more progress on, say, math and code, where the models are getting pretty close to a high professional level, and less on more subjective tasks, but I think that is very much a temporary obstacle. So when I look at it, I see this exponential and I say, look, people aren't very good at making sense of exponentials, right? Like, if something is doubling every 6 months, then 2 years before it happens, it looks like it's only 1/16th of the way there. And so we are sitting here in the middle of 2025, and the models are really starting to explode in terms of the economy. If you look at the capabilities of the model, they're starting to saturate all the benchmarks. If you look at revenue, and you know, Anthropic's revenue every year has grown 10x. Every year we’re kind of conservative and we say, it can’t grow 10x this time. I never assume anything and actually always am very conservative in saying I think it's going to slow down on the business side. But we went from zero to $100 million in 2023, we went from $100 million to $1 billion in 2024, and this year, in the first half of the year, we've gone from $1 billion to, I think as of speaking today, it's well above $4 billion, it might be $4.5 billion. And so if you think about it, suppose that exponential continued for 2 years. I'm not saying it will, but suppose it continued for 2 years. You're well into the $100 billions. I'm not saying that'll happen. I'm saying the situation is that when you're on an exponential, you can really get fooled by it. 2 years away from when the exponential goes totally crazy, it looks like it's just starting to be a thing. And so that's the fundamental dynamic. We saw that with the internet in the '90s, right? Where it was like networking speeds and the underlying speed of the computers were getting fast, and over a few years it became possible to have to basically build a digital global communications network on top of all this when it wasn't possible just a few years ago and and almost no one except for a few people really saw the implications of that and how fast it." - Anthropic CEO Dario Amodei

Rohan Paul

74,406 次观看 • 1 年前

Eric Roth won the Oscar for Best Adapted Screenplay in 1994. He wrote the scripts for movies like Dune, Forrest Gump, and The Curious Case of Benjamin Button — and worked with directors like Spielberg and Scorsese. Some highlights from the interview: 1. God is in the details. 2. If the details aren’t vivid, the story won’t succeed. 3. If you get writer’s block, try changing the weather in your story. Will give you a fresh perspective. 4. Don't try to make your characters likable. Try to make them understandable. Great villain characters aren't great because we like them, but because we understand what makes them tick. 5. For major characters, you should have a clear answer to: What makes them tick? 6. A good movie is more than just a story. It has to be about something. When writing, ask yourself: What's this story really about? The writing gets easier once you have a clear theme. 7. The time of day in a scene should match (and enhance) the scene. 8. Great writing lives in the subtext. The most sophisticated writers don’t explain things too directly. Communicating through subtlety lets you achieve more with your words. You can convey information, share a lesson for life, and give the audience something to make sense of for themselves. 9. Dialogue can't just fill space. It has to carry weight. Every interaction has to move the story along. Avoid Shoe Leather (which is when you have an unnecessary scene where people are walking around in a way that doesn’t develop the story or the characters). 10. The first time you write something, it won't be right. That's just how it is. The work of writing something great happens in the rewriting. 11. Every screenplay will follow a 3-Act Structure. You can't escape it. The first act will state the problem, the second act will complicate it, and the third act will or will not resolve it. 12. "I start on page one every day." Reading the whole screenplay from scratch is how he stays close to the material and keeps the entire story consistent. 13. End each writing day with a scene you like so you don't have to worry about it over night. I've shared the full interview with Eric Roth below. If you'd rather watch on YouTube or listen on Spotify / Apple, check the reply tweets. I've added the links there.
1:35:00

Eric Roth won the Oscar for Best Adapted Screenplay in 1994. He wrote the scripts for movies like Dune, Forrest Gump, and The Curious Case of Benjamin Button — and worked with directors like Spielberg and Scorsese. Some highlights from the interview: 1. God is in the details. 2. If the details aren’t vivid, the story won’t succeed. 3. If you get writer’s block, try changing the weather in your story. Will give you a fresh perspective. 4. Don't try to make your characters likable. Try to make them understandable. Great villain characters aren't great because we like them, but because we understand what makes them tick. 5. For major characters, you should have a clear answer to: What makes them tick? 6. A good movie is more than just a story. It has to be about something. When writing, ask yourself: What's this story really about? The writing gets easier once you have a clear theme. 7. The time of day in a scene should match (and enhance) the scene. 8. Great writing lives in the subtext. The most sophisticated writers don’t explain things too directly. Communicating through subtlety lets you achieve more with your words. You can convey information, share a lesson for life, and give the audience something to make sense of for themselves. 9. Dialogue can't just fill space. It has to carry weight. Every interaction has to move the story along. Avoid Shoe Leather (which is when you have an unnecessary scene where people are walking around in a way that doesn’t develop the story or the characters). 10. The first time you write something, it won't be right. That's just how it is. The work of writing something great happens in the rewriting. 11. Every screenplay will follow a 3-Act Structure. You can't escape it. The first act will state the problem, the second act will complicate it, and the third act will or will not resolve it. 12. "I start on page one every day." Reading the whole screenplay from scratch is how he stays close to the material and keeps the entire story consistent. 13. End each writing day with a scene you like so you don't have to worry about it over night. I've shared the full interview with Eric Roth below. If you'd rather watch on YouTube or listen on Spotify / Apple, check the reply tweets. I've added the links there.

David Perell

88,706 次观看 • 1 年前

Today we’re announcing our $50M Series A! Over the last year, we’ve grown from a small group with a big idea into a platform powering AI for hundreds of millions of end users across image, video, audio, and more. Since Q3, we’ve grown revenue by 10x, placing Runware comfortably among the fastest growing companies in the world. 🚀 When Runware started, the mission was simple: build the fastest and most reliable multimodal inference platform on the planet and make it accessible to everyone. We built our own Sonic Inference Engine, our own GPU infrastructure, our own inference pods, and a set of optimizations that push the limits of what an AI provider can do at scale. 2026 will be the year we bring inference closer to users than ever. We’re deploying more than twenty Runware Inference Pods across major cities in Europe and the US, delivering sub-10ms latency AI. And we’re extending Runware to support every model on Hugging Face, running them faster, cheaper, and more reliably than anyone else. A special thank you to Dawn Capital for leading this round, alongside Speedinvest Comcast Ventures Insight Partners speedrun Zero Prime VC Alex Menn at Begin Capital and all our early backers who supported us long before Runware looked like it does today.
0:48

Today we’re announcing our $50M Series A! Over the last year, we’ve grown from a small group with a big idea into a platform powering AI for hundreds of millions of end users across image, video, audio, and more. Since Q3, we’ve grown revenue by 10x, placing Runware comfortably among the fastest growing companies in the world. 🚀 When Runware started, the mission was simple: build the fastest and most reliable multimodal inference platform on the planet and make it accessible to everyone. We built our own Sonic Inference Engine, our own GPU infrastructure, our own inference pods, and a set of optimizations that push the limits of what an AI provider can do at scale. 2026 will be the year we bring inference closer to users than ever. We’re deploying more than twenty Runware Inference Pods across major cities in Europe and the US, delivering sub-10ms latency AI. And we’re extending Runware to support every model on Hugging Face, running them faster, cheaper, and more reliably than anyone else. A special thank you to Dawn Capital for leading this round, alongside Speedinvest Comcast Ventures Insight Partners speedrun Zero Prime VC Alex Menn at Begin Capital and all our early backers who supported us long before Runware looked like it does today.

Runware

63,708 次观看 • 9 个月前

Want to write thrilling stories? Nick Bilton has the playbook. He's written for Netflix and The New York Times, and this episode is a tell-all class on how to create tension with hooks, cliffhangers, drama, and conflict. Highlights below: 1. Evil characters only work if readers care about them. 2. The best way to make readers care about an evil character is to humanize them. You can do that by focusing on simple details like how they lose their keys. Or, you can write about their mother because every murderer has a mother who loves them. 3. You can't look down on your characters. You have to look out with them. 4. Rule for writing screenplays: Get into the scene as late as you can, and get out of it as early as you can. 5. Fiction stories have the opposite shape as non-fiction ones. 6. In fiction, the kicker comes at the beginning and the summary comes at the end. In non-fiction, the summary comes at the beginning and the kicker comes at the end. 7. How’d Nick learn to tell better stories? By reading murder mysteries. 8. If the story's good enough, the book will fly off the shelves. Look at the Twilight series. The books sold like crazy even though the writing stinks. 9. How do you write good cliffhangers? Show people a little bit of the future, but don't reveal everything. 10. Ask the question at the end of one chapter and answer it shortly after. The answer doesn't need to come right away, but you have to answer it soon. 11. There are two kinds of stories that work: Big ones about something small, and small ones about something big. Stories in the middle are usually terrible. 12. Nick once asked the legendary journalist David Carr for advice. The response: “Keep typing until it turns into writing.” 13. You can tell a good story without knowing everything that happened, but you do need to know enough to make the reader feel like they're there. 14. Writers often over-describe their scenes. You only need three details. For example, if you're at a campground, you might only need the sight of the pine needles on the ground, the smell of a nearby campfire, and the sound of crickets in the distance. 15. We admire characters more for trying than their successes (this is rule #1 in Pixar's 22 Rules of Storytelling). That's just a little taste of what's in this episode with Nick Bilton. You can watch the full thing below. If you'd rather watch on YouTube or listen on Spotify or Apple, and I've shared those links in the reply tweets.
1:19:46

Want to write thrilling stories? Nick Bilton has the playbook. He's written for Netflix and The New York Times, and this episode is a tell-all class on how to create tension with hooks, cliffhangers, drama, and conflict. Highlights below: 1. Evil characters only work if readers care about them. 2. The best way to make readers care about an evil character is to humanize them. You can do that by focusing on simple details like how they lose their keys. Or, you can write about their mother because every murderer has a mother who loves them. 3. You can't look down on your characters. You have to look out with them. 4. Rule for writing screenplays: Get into the scene as late as you can, and get out of it as early as you can. 5. Fiction stories have the opposite shape as non-fiction ones. 6. In fiction, the kicker comes at the beginning and the summary comes at the end. In non-fiction, the summary comes at the beginning and the kicker comes at the end. 7. How’d Nick learn to tell better stories? By reading murder mysteries. 8. If the story's good enough, the book will fly off the shelves. Look at the Twilight series. The books sold like crazy even though the writing stinks. 9. How do you write good cliffhangers? Show people a little bit of the future, but don't reveal everything. 10. Ask the question at the end of one chapter and answer it shortly after. The answer doesn't need to come right away, but you have to answer it soon. 11. There are two kinds of stories that work: Big ones about something small, and small ones about something big. Stories in the middle are usually terrible. 12. Nick once asked the legendary journalist David Carr for advice. The response: “Keep typing until it turns into writing.” 13. You can tell a good story without knowing everything that happened, but you do need to know enough to make the reader feel like they're there. 14. Writers often over-describe their scenes. You only need three details. For example, if you're at a campground, you might only need the sight of the pine needles on the ground, the smell of a nearby campfire, and the sound of crickets in the distance. 15. We admire characters more for trying than their successes (this is rule #1 in Pixar's 22 Rules of Storytelling). That's just a little taste of what's in this episode with Nick Bilton. You can watch the full thing below. If you'd rather watch on YouTube or listen on Spotify or Apple, and I've shared those links in the reply tweets.

David Perell

81,036 次观看 • 2 年前

Introducing Immutable Audience: the growth engine for pre-launch Steam games. (btw we didn’t spend $50k on a viral launch agency - so if you think this is cool just share it for free i guess) Game marketing is broken. Every year PC studios spend billions to grow their games, and yet: - they don’t know which channels are actually working - only a fraction of wishlist sources can be tracked - of those people who DO wishlist games, the rate of those who go on to purchase is falling After 8 years building games ourselves, and working with over 700 studios, the need for something new was obvious. So, we built Audience. How it works: 1. Audience pulls in real time data from your players across Steam, social media, ad platforms, influencers and more 2. It stores this marketing data in your player CRM, and uses our Enhanced Attribution to identify the one channel driving 80% of your wishlists 3. Finally, it generates a custom growth audit, reviewing your real time data against winning strategies from hundreds of games to identify the most effective ways to get you wishlists each week During Audience’s beta we’ve already seen incredible results. We helped one game grow by over 300k wishlists in 2 months, and then more than *doubled* the rate of those players who converted into paying customers, compared to relying on Steam alone. For the last few months the team at Immutable has been heads down building. We’re incredibly grateful to our community for your support as we onboard the world. Slowly, then all at once. To celebrate the launch, we’re offering one month of Audience for free to any studio that signs up by commenting on this video. And for the first 100 studios that comment, we’ll create you a custom growth plan for free. Comment “Audience” and we’ll send it through.
1:35

Introducing Immutable Audience: the growth engine for pre-launch Steam games. (btw we didn’t spend $50k on a viral launch agency - so if you think this is cool just share it for free i guess) Game marketing is broken. Every year PC studios spend billions to grow their games, and yet: - they don’t know which channels are actually working - only a fraction of wishlist sources can be tracked - of those people who DO wishlist games, the rate of those who go on to purchase is falling After 8 years building games ourselves, and working with over 700 studios, the need for something new was obvious. So, we built Audience. How it works: 1. Audience pulls in real time data from your players across Steam, social media, ad platforms, influencers and more 2. It stores this marketing data in your player CRM, and uses our Enhanced Attribution to identify the one channel driving 80% of your wishlists 3. Finally, it generates a custom growth audit, reviewing your real time data against winning strategies from hundreds of games to identify the most effective ways to get you wishlists each week During Audience’s beta we’ve already seen incredible results. We helped one game grow by over 300k wishlists in 2 months, and then more than *doubled* the rate of those players who converted into paying customers, compared to relying on Steam alone. For the last few months the team at Immutable has been heads down building. We’re incredibly grateful to our community for your support as we onboard the world. Slowly, then all at once. To celebrate the launch, we’re offering one month of Audience for free to any studio that signs up by commenting on this video. And for the first 100 studios that comment, we’ll create you a custom growth plan for free. Comment “Audience” and we’ll send it through.

Robbie Ferguson | Immutable

24,819 次观看 • 1 个月前

We're starting to leave the territory where you'd test an LLM by e.g. "create an svg of pelican on a bicycle". As one idea to generalize it, I was interested what Opus 5 would do if I gave it the first paragraph of the Lord of the Rings, a 1M token budget (~$10) and asked for three js render of it. Opus went off for ~2 hours and wrote 5500 lines of code that (procedurally) rendered the story. It's kind of janky but fun. But it's a bit mindboggling that the LLM has to place and orchestrate various polygon assets in (x,y,z) coordinates and write code that animates it all, and that it even does anything at all. I also like this kind of examples because no one in their right mind would ever spend the time to write something this custom but LLMs have all the stamina and patience in the world, so it's an example where we go from "no one would ever do this" to "sure, why not, it's ~free". There might be a lot more. But I'm excited about creating hyper custom worlds that you can imagine dropping players into, e.g. here to participate in the LoTR story as a spectator NPC, or one of the characters, or etc. Something like an ephemeral GTA of X on demand. Last thought is that the domain of worlds/games exposes a weakness in LLMs: they can't easily audit their work because they aren't able to efficiently and natively perceive videos or play games within them. Here, Opus 5 had to very slowly and painstakingly take screenshots at different points, and it messed up a few times and created a bunch of jank. An example of raw capability (multimodal, gameplay) that I think is still quite lacking.
1:32

We're starting to leave the territory where you'd test an LLM by e.g. "create an svg of pelican on a bicycle". As one idea to generalize it, I was interested what Opus 5 would do if I gave it the first paragraph of the Lord of the Rings, a 1M token budget (~$10) and asked for three js render of it. Opus went off for ~2 hours and wrote 5500 lines of code that (procedurally) rendered the story. It's kind of janky but fun. But it's a bit mindboggling that the LLM has to place and orchestrate various polygon assets in (x,y,z) coordinates and write code that animates it all, and that it even does anything at all. I also like this kind of examples because no one in their right mind would ever spend the time to write something this custom but LLMs have all the stamina and patience in the world, so it's an example where we go from "no one would ever do this" to "sure, why not, it's ~free". There might be a lot more. But I'm excited about creating hyper custom worlds that you can imagine dropping players into, e.g. here to participate in the LoTR story as a spectator NPC, or one of the characters, or etc. Something like an ephemeral GTA of X on demand. Last thought is that the domain of worlds/games exposes a weakness in LLMs: they can't easily audit their work because they aren't able to efficiently and natively perceive videos or play games within them. Here, Opus 5 had to very slowly and painstakingly take screenshots at different points, and it messed up a few times and created a bunch of jank. An example of raw capability (multimodal, gameplay) that I think is still quite lacking.

Andrej Karpathy

5,409,558 次观看 • 1 个月前

RLM is the most import foundation of my Pi Harness (other than Pi of course). It's seeded with late interaction retrieval results (thanks to @lightonai for pylate). The Agent initiates it with query then.. 𝐒𝐞𝐭𝐮𝐩 A python REPL is created and seeded with: 1. Late interaction search to pre-filter. Instead of doing top 3/5/10, it's top hundreds of documents. This is set into a `context` variable. 2. Python functions are loaded in to do more searches if `context` variable isn't enough. And to make llm calls with cheaper models in parallel batches. 𝐈𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐨𝐨𝐩 From there, an LLM iterates in the REPL based on the query. It's just like exploring in a jupyter notebook. The LLM writes prose (like a markdown cell) and code to be run in the REPL each turn. This allows the LLM to sort, filter, and synthesize information. It can fan out and ask smaller models to summarize, combine, contrast, or do anything else to documents to help it understand the data. After several turns the LLM reponds with the final answer. Either because it found the answer, or hit the budget limit. Context as a Python variable, LLM as the programmer, REPL as the runtime. 𝐖𝐡𝐲 𝐃𝐨𝐞𝐬 𝐓𝐡𝐢𝐬 𝐖𝐨𝐫𝐤 1. Richer Shell. Agents (and subagents) work by intermixing code and prose/thinking. But they use static scripts or bash that run and exit and start over each tool call. That's not ideal for exploration and synthesis of data. For that, state is useful to continue building and exploring the data as you learn more. There's a reason jupyter notebooks have been popular with data scientists. 2. Keeps main agent context clean. The better context you have the better the agent will perform (duh!). This means three thing: better human input, less missing search results, and less incorrect search results. Letting the agent iterate allows it to synthesize just what is needed and nothing else. All bad paths or peeks at something that turns out to be irrelevant stays out of main agent context. 3. Stack the good ideas! People often compare late interaction search vs RLM. Or static vs dynamic languages. Or agentic search vs semantic search. But...You can just use them all together for what they're each good at. Use them all for the area they're really great for. Read the full post which has more detail about how and why.
3:43

RLM is the most import foundation of my Pi Harness (other than Pi of course). It's seeded with late interaction retrieval results (thanks to @lightonai for pylate). The Agent initiates it with query then.. 𝐒𝐞𝐭𝐮𝐩 A python REPL is created and seeded with: 1. Late interaction search to pre-filter. Instead of doing top 3/5/10, it's top hundreds of documents. This is set into a `context` variable. 2. Python functions are loaded in to do more searches if `context` variable isn't enough. And to make llm calls with cheaper models in parallel batches. 𝐈𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐨𝐨𝐩 From there, an LLM iterates in the REPL based on the query. It's just like exploring in a jupyter notebook. The LLM writes prose (like a markdown cell) and code to be run in the REPL each turn. This allows the LLM to sort, filter, and synthesize information. It can fan out and ask smaller models to summarize, combine, contrast, or do anything else to documents to help it understand the data. After several turns the LLM reponds with the final answer. Either because it found the answer, or hit the budget limit. Context as a Python variable, LLM as the programmer, REPL as the runtime. 𝐖𝐡𝐲 𝐃𝐨𝐞𝐬 𝐓𝐡𝐢𝐬 𝐖𝐨𝐫𝐤 1. Richer Shell. Agents (and subagents) work by intermixing code and prose/thinking. But they use static scripts or bash that run and exit and start over each tool call. That's not ideal for exploration and synthesis of data. For that, state is useful to continue building and exploring the data as you learn more. There's a reason jupyter notebooks have been popular with data scientists. 2. Keeps main agent context clean. The better context you have the better the agent will perform (duh!). This means three thing: better human input, less missing search results, and less incorrect search results. Letting the agent iterate allows it to synthesize just what is needed and nothing else. All bad paths or peeks at something that turns out to be irrelevant stays out of main agent context. 3. Stack the good ideas! People often compare late interaction search vs RLM. Or static vs dynamic languages. Or agentic search vs semantic search. But...You can just use them all together for what they're each good at. Use them all for the area they're really great for. Read the full post which has more detail about how and why.

Isaac Flath

42,620 次观看 • 5 个月前

Sora 2 has the capabilities to make an entire anime episode with time and effort. This is a turning point for generative AI models and it is terrifying to think what is next to come. The difference between Sora and Sora 2 is absolutely staggering. Yes, this looks cool. I put the time into it to make it as close to art as possible. This was not simple to make and not just prompting and throwing it in some editor. Every frame is generated of another scene and even the reference image for characters I used to start this project were AI generated. This was all created with 10 second clips pulled apart and chunked out into the final product. Regardless of the imagery you see, I did not directly use any artist's art for this video. This 10-minute video was generated over the course of a week from more than 700 text prompts. It was built on technology trained by scraping the uncredited, uncompensated contributions of countless human artists and animators. The creation of this single video consumed an enormous amount of energy and water, equivalent to powering a home for days and requiring hundreds of liters of fresh water for cooling. But that is nothing. In the 10 minutes you spend watching this, the global network of AI video generators will create over 6,250 more short videos. The combined energy required for that 10 minutes of global creation is enough to power an average household for nearly 2 years. - It's a double-edged sword. While AI uses immense amount of energy has clear immoral issues with scalping the hard work of artists, this also provides those a medium who have potentially spent their life attempting to draw out the ideas in their head and failing to grasp it. My sister is an artist, I grew up always attempting to draw but never could get the image in my head on paper, I've spent the better part of over 20 years to teach myself through watching videos and practice, however I don't have steady hands and frankly have just been unable to make any vision come to life. Which brings me to the conflict here. This would have been a dream of mine to be able to get frames created and flesh out the story in my head. To make this video professionally, it would be an absurd amount of money. A small studio by itself would be over a million dollars just to start up. To hire a studio would be most likely over ~200k. I would love to make this story I have in my head through legit and traditional means, I would love to start a Kickstarter to get funding and hire artists, voice actors, and a production team. However I know that would most likely be an impossible reach that would further fuel the hate. Regardless, I understand the worry this causes. The fear this produces. However, we can't just ignore where AI is currently at and just tell people not to use it or even worse threaten people who use it. People will always use the shiny new toy in front of them, so the real question is how do we either make it work for us and work along side it, or how do we ACTUALLY implement a method to protect art rather than tell people to not use it. Respect your artists. Review their ToS and don't upload their hard work to a model without permission.
10:33

Sora 2 has the capabilities to make an entire anime episode with time and effort. This is a turning point for generative AI models and it is terrifying to think what is next to come. The difference between Sora and Sora 2 is absolutely staggering. Yes, this looks cool. I put the time into it to make it as close to art as possible. This was not simple to make and not just prompting and throwing it in some editor. Every frame is generated of another scene and even the reference image for characters I used to start this project were AI generated. This was all created with 10 second clips pulled apart and chunked out into the final product. Regardless of the imagery you see, I did not directly use any artist's art for this video. This 10-minute video was generated over the course of a week from more than 700 text prompts. It was built on technology trained by scraping the uncredited, uncompensated contributions of countless human artists and animators. The creation of this single video consumed an enormous amount of energy and water, equivalent to powering a home for days and requiring hundreds of liters of fresh water for cooling. But that is nothing. In the 10 minutes you spend watching this, the global network of AI video generators will create over 6,250 more short videos. The combined energy required for that 10 minutes of global creation is enough to power an average household for nearly 2 years. - It's a double-edged sword. While AI uses immense amount of energy has clear immoral issues with scalping the hard work of artists, this also provides those a medium who have potentially spent their life attempting to draw out the ideas in their head and failing to grasp it. My sister is an artist, I grew up always attempting to draw but never could get the image in my head on paper, I've spent the better part of over 20 years to teach myself through watching videos and practice, however I don't have steady hands and frankly have just been unable to make any vision come to life. Which brings me to the conflict here. This would have been a dream of mine to be able to get frames created and flesh out the story in my head. To make this video professionally, it would be an absurd amount of money. A small studio by itself would be over a million dollars just to start up. To hire a studio would be most likely over ~200k. I would love to make this story I have in my head through legit and traditional means, I would love to start a Kickstarter to get funding and hire artists, voice actors, and a production team. However I know that would most likely be an impossible reach that would further fuel the hate. Regardless, I understand the worry this causes. The fear this produces. However, we can't just ignore where AI is currently at and just tell people not to use it or even worse threaten people who use it. People will always use the shiny new toy in front of them, so the real question is how do we either make it work for us and work along side it, or how do we ACTUALLY implement a method to protect art rather than tell people to not use it. Respect your artists. Review their ToS and don't upload their hard work to a model without permission.

LUͦʷCͦk

18,632 次观看 • 11 个月前

I've spent hours and hours thinking about how AI is going to change writing. This is a 90-minute distillation of everything I've learned. Some things I believe: 1. The combination of LLM-driven humor and image generation means that we're about to enter the golden age of memes. 2. The best writers will be fine. Robert Caro and Dostoevsky aren’t about to be disrupted by ChatGPT. 3. What are the different models like? ChatGPT is your friend who makes a lot of good points, but it’s kinda boring, Claude is your hippie friend who loves to get vulnerable but takes the whole “express yourself” thing a little too far, and Grok is your unhinged friend who leans a little too hard into tinfoil hat theories, but is always a trip to jam on ideas with. 4. People who say that AI writing is low-quality aren’t realizing that quality exists along two dimensions: (1) the absolute quality of the writing and (2) how tailored the writing is to your interests at the time. 5. I’ll tell you this: What writers are doing with AI behind closed doors is a long way ahead of what's publicly understood. I don't expect this to change anytime soon because of the social stigma associated with AI-enhanced writing. Because of that, if you want to see the cutting edge, you're gonna have to piece things together through private conversations and group chats. 6. If you want to follow what's happening in AI, remember this quote from William Gibson: “The future is here, it’s just not evenly distributed yet.” You can get a glimpse of the future by looking at how a small percentage of writers are already using AI. 7. I’m bearish on writers who are currently using AI to write for them, and bullish on writers who are currently using AI to write with them. 8. What kinds of writing will continue to be written by humans? Ones that speak to our humanity. People are interested in people. Their stories, their struggles, their emotions, their drama. 9. Almost all utilitarian writing, where the goal is to convey information, not do it beautifully, will be written by AI. 10. In some ways, AI is the end of slop. So many Google search results are slop. LinkedIn posts are slop. The way Twitter got taken over by Threadbois in 2021 was also slop. AI-generated writing is already better than all of those things, so why would you read them now? 11. AI will be tougher on writers than readers. Readers will be exposed to some slop, but the Internet will be good about filtering it out. Writers, though, are now competing against ever-improving LLMs, which are getting better and better by the month. 12. Humans will contribute with unique data or perspectives. The famous Peter Thiel interview question doubles as a good writing prompt: “What very important truth do few people agree with you on?” 13. New technologies breed new kinds of art. Ever notice how flat 13th or 14th century Medieval art looks? And how different that art looks from the Renaissance art created in the 15th and 16th centuries? Technical innovations like the camera obscura and perspective grids are behind this. Similarly profound changes will come to the writing world because of AI (credit to Justin Murphy for the idea here). 14. Satya Nadella says: “The new workflow for me is I think with AI and work with my colleagues.” When it comes to discovering ideas, I've also found that jamming with an LLM is more productive than doing it with most people I know (save for a few giga-brain conversationalists). 15. Thought experiment: Will AI-writing be more like music or chess? With music, we don't care how a song is made. We just want it to be good. With chess, there's a huge market for watching human beings play even though the computers are already better. I think non-fiction writing will go the way of music. People won’t care how it was made. They’ll just care that it’s good. 16. AI has flipped the rules of tech adoption. Seasoned managers usually drag their feet with adopting new technology, but the ones I know love AI, while frontline workers struggle to see the point. My theory is that AI matches how managers already operate. Management has always been a kind of prompt engineering: set a vision, delegate, give feedback, iterate. But LLMs remove the drama that used to come with having a team. No 1-on-1s. No emotional tangles. It's like management without the headache. For frontline employees, things are different. They aren't as accustomed to setting a vision and giving feedback, so LLM prompting is a daunting and unfamiliar kind of work for them. 17. AI editors are already quite good. Sure, they aren’t as good as the world’s best editors, but they’re a fraction of the cost, they’ll instantly give you 80th percentile feedback, and they work 24/7. As a novelist recently said to me: “Paying an editor to review my novel costs me $7,000 and a 4-6 week turnaround time, whereas Claude costs me $1.25 and gets me results a few minutes later.” The edits definitely aren’t as good, but there’s a virtue to speed (and this guy isn’t a chump writer). 18. The way AI-skeptics hate on LLMs while using old models is like driving a ‘92 Honda while hating on a self-driving Tesla. 19. AI-generated fiction makes people very upset. A friend insists it’s like having sex with a robot. Doesn’t matter how good it is. It ain’t human-generated, and there’s something uniquely repulsive about that. I’ve shared the full conversation below. It’s a solo-episode of me riffing on what I’ve learned about AI for ~90 minutes. If you’d rather watch it on YouTube or listen on Apple or Spotify, I’ve shared the links in the reply tweets. And if you have any questions, I’ll be extra active in the replies for this episode.
1:29:31

I've spent hours and hours thinking about how AI is going to change writing. This is a 90-minute distillation of everything I've learned. Some things I believe: 1. The combination of LLM-driven humor and image generation means that we're about to enter the golden age of memes. 2. The best writers will be fine. Robert Caro and Dostoevsky aren’t about to be disrupted by ChatGPT. 3. What are the different models like? ChatGPT is your friend who makes a lot of good points, but it’s kinda boring, Claude is your hippie friend who loves to get vulnerable but takes the whole “express yourself” thing a little too far, and Grok is your unhinged friend who leans a little too hard into tinfoil hat theories, but is always a trip to jam on ideas with. 4. People who say that AI writing is low-quality aren’t realizing that quality exists along two dimensions: (1) the absolute quality of the writing and (2) how tailored the writing is to your interests at the time. 5. I’ll tell you this: What writers are doing with AI behind closed doors is a long way ahead of what's publicly understood. I don't expect this to change anytime soon because of the social stigma associated with AI-enhanced writing. Because of that, if you want to see the cutting edge, you're gonna have to piece things together through private conversations and group chats. 6. If you want to follow what's happening in AI, remember this quote from William Gibson: “The future is here, it’s just not evenly distributed yet.” You can get a glimpse of the future by looking at how a small percentage of writers are already using AI. 7. I’m bearish on writers who are currently using AI to write for them, and bullish on writers who are currently using AI to write with them. 8. What kinds of writing will continue to be written by humans? Ones that speak to our humanity. People are interested in people. Their stories, their struggles, their emotions, their drama. 9. Almost all utilitarian writing, where the goal is to convey information, not do it beautifully, will be written by AI. 10. In some ways, AI is the end of slop. So many Google search results are slop. LinkedIn posts are slop. The way Twitter got taken over by Threadbois in 2021 was also slop. AI-generated writing is already better than all of those things, so why would you read them now? 11. AI will be tougher on writers than readers. Readers will be exposed to some slop, but the Internet will be good about filtering it out. Writers, though, are now competing against ever-improving LLMs, which are getting better and better by the month. 12. Humans will contribute with unique data or perspectives. The famous Peter Thiel interview question doubles as a good writing prompt: “What very important truth do few people agree with you on?” 13. New technologies breed new kinds of art. Ever notice how flat 13th or 14th century Medieval art looks? And how different that art looks from the Renaissance art created in the 15th and 16th centuries? Technical innovations like the camera obscura and perspective grids are behind this. Similarly profound changes will come to the writing world because of AI (credit to Justin Murphy for the idea here). 14. Satya Nadella says: “The new workflow for me is I think with AI and work with my colleagues.” When it comes to discovering ideas, I've also found that jamming with an LLM is more productive than doing it with most people I know (save for a few giga-brain conversationalists). 15. Thought experiment: Will AI-writing be more like music or chess? With music, we don't care how a song is made. We just want it to be good. With chess, there's a huge market for watching human beings play even though the computers are already better. I think non-fiction writing will go the way of music. People won’t care how it was made. They’ll just care that it’s good. 16. AI has flipped the rules of tech adoption. Seasoned managers usually drag their feet with adopting new technology, but the ones I know love AI, while frontline workers struggle to see the point. My theory is that AI matches how managers already operate. Management has always been a kind of prompt engineering: set a vision, delegate, give feedback, iterate. But LLMs remove the drama that used to come with having a team. No 1-on-1s. No emotional tangles. It's like management without the headache. For frontline employees, things are different. They aren't as accustomed to setting a vision and giving feedback, so LLM prompting is a daunting and unfamiliar kind of work for them. 17. AI editors are already quite good. Sure, they aren’t as good as the world’s best editors, but they’re a fraction of the cost, they’ll instantly give you 80th percentile feedback, and they work 24/7. As a novelist recently said to me: “Paying an editor to review my novel costs me $7,000 and a 4-6 week turnaround time, whereas Claude costs me $1.25 and gets me results a few minutes later.” The edits definitely aren’t as good, but there’s a virtue to speed (and this guy isn’t a chump writer). 18. The way AI-skeptics hate on LLMs while using old models is like driving a ‘92 Honda while hating on a self-driving Tesla. 19. AI-generated fiction makes people very upset. A friend insists it’s like having sex with a robot. Doesn’t matter how good it is. It ain’t human-generated, and there’s something uniquely repulsive about that. I’ve shared the full conversation below. It’s a solo-episode of me riffing on what I’ve learned about AI for ~90 minutes. If you’d rather watch it on YouTube or listen on Apple or Spotify, I’ve shared the links in the reply tweets. And if you have any questions, I’ll be extra active in the replies for this episode.

David Perell

257,480 次观看 • 1 年前

Nat Eliason’s (Nat Eliason) career arc is borderline absurd—but it works. He’ll spot a new tool or trend, master it, build a business around it, and move on. Nat’s pulled it off with the note-taking wave ($600k in sales from a Roam Research course), real estate (6x return flipping property in Austin), and crypto (published his insider story with Random House). Now it’s AI: he’s running a viral course on building apps with AI—$200k in pre-sales in just a week, 800 students and counting. I’ve known Nat for a long time and I think he has a great sense for where the puck is headed. He was one of the first guests I had on the podcast and I was delighted to have him on again. Here are a few takeaways from our conversation: - Coding with AI has become orders of magnitude easier for non-technical people over the last 2 years—Nat rarely has to help students fix bugs; they troubleshoot in Cursor on their own. - AI coding assistants are creating new behaviours in programming, like using a speech-to-text model to talk to an agent and having it write code for you. - The traditional learning curve of coding is flattening because AI tools let beginners build and iterate in faster feedback loops. - AI has given Nat leverage in spades—it increases his ability to be a creator while also building a robust business with as few people to manage as possible. He demos an AI book editor he coded for his sci-fi novel. - In the age of AI, software is becoming content and the barriers to create are lower than ever—but custom software for everything isn’t the answer. Nat’s model is that personalized tools make sense for that one thing you care the most about. - Nat believes that the future of writing with AI is a Cursor-style interface with a model that’s trained on your style and voice. This episode is a must-watch for writers, creators, and anyone interested in the future of product building. Watch below! Timestamps: Introduction: 00:01:45 The origins of Nat’s viral course on building apps with AI: 00:11:45 How coding with AI has evolved over the last two years: 00:18:46 Nat creates an app using Composer, Cursor’s AI assistant: 00:22:22 Tactical tips for coding with Cursor: 00:26:06 How coding with AI is creating new behaviours in programming: 00:29:06 What excites Nat the most about the future of AI: 00:32:41 A demo of Hubbard, the AI editor Nat built for his science fiction writing: 00:38:58 When does it makes sense to build custom software: 00:44:52 Nat’s take on the future of writing with AI: 00:49:18
1:00:52

Nat Eliason’s (Nat Eliason) career arc is borderline absurd—but it works. He’ll spot a new tool or trend, master it, build a business around it, and move on. Nat’s pulled it off with the note-taking wave ($600k in sales from a Roam Research course), real estate (6x return flipping property in Austin), and crypto (published his insider story with Random House). Now it’s AI: he’s running a viral course on building apps with AI—$200k in pre-sales in just a week, 800 students and counting. I’ve known Nat for a long time and I think he has a great sense for where the puck is headed. He was one of the first guests I had on the podcast and I was delighted to have him on again. Here are a few takeaways from our conversation: - Coding with AI has become orders of magnitude easier for non-technical people over the last 2 years—Nat rarely has to help students fix bugs; they troubleshoot in Cursor on their own. - AI coding assistants are creating new behaviours in programming, like using a speech-to-text model to talk to an agent and having it write code for you. - The traditional learning curve of coding is flattening because AI tools let beginners build and iterate in faster feedback loops. - AI has given Nat leverage in spades—it increases his ability to be a creator while also building a robust business with as few people to manage as possible. He demos an AI book editor he coded for his sci-fi novel. - In the age of AI, software is becoming content and the barriers to create are lower than ever—but custom software for everything isn’t the answer. Nat’s model is that personalized tools make sense for that one thing you care the most about. - Nat believes that the future of writing with AI is a Cursor-style interface with a model that’s trained on your style and voice. This episode is a must-watch for writers, creators, and anyone interested in the future of product building. Watch below! Timestamps: Introduction: 00:01:45 The origins of Nat’s viral course on building apps with AI: 00:11:45 How coding with AI has evolved over the last two years: 00:18:46 Nat creates an app using Composer, Cursor’s AI assistant: 00:22:22 Tactical tips for coding with Cursor: 00:26:06 How coding with AI is creating new behaviours in programming: 00:29:06 What excites Nat the most about the future of AI: 00:32:41 A demo of Hubbard, the AI editor Nat built for his science fiction writing: 00:38:58 When does it makes sense to build custom software: 00:44:52 Nat’s take on the future of writing with AI: 00:49:18

Dan Shipper 📧

27,207 次观看 • 1 年前

Grateful for the outpouring the past few days. I can’t tell you how motivating it is to have people care so much about Arc. The encouragement, the criticism, the confusion. Took it all in <3 As a thank you, I’d like to speak more plainly about what’s happening and why – we owe it to you: 1. Every person who joined or invested in our company did so to build products beloved by hundreds of millions of people. “We want to be to the browser what the iPhone was to the cellphone” has been our rallying cry since Day One. We knew chance of success was low but the ambition made us leap out of bed every morning. 2. Arc is beloved, popular, and growing (4x daily actives YoY). But it’s now clear that what most people love about the product *is also* what will prevent it from reaching hundreds of millions of people in our target demographic (people who spend hours in their browsers each day for their livelihood). Arc is a niche browser, even if we did not intend for it to be so. 3. Luckily, we architected this company – from company name to investors and technical architecture – to support multiple products since Day One. See Arc Search. Our favorite brands have multiple product lines in the same category too (Apple, Nike, Disney). Hence our realization: why keep trying to make Arc something it is not? Nobody who loved Arc wanted Arc Max. Arc members just want it to be more stable, secure, and performant. “Let’s just do that!” 4. With Arc as our beloved but niche browser #1, we asked ourselves a simple question: if we founded the company TODAY (in 2024), with everything that we know, what would the browser of the future look like for hundreds of millions of people? Let’s go build *that* product, alongside Arc. A second browser that is easier to use, more focused, and more powerful. All in order to live up to our founding mission (#1 above). 5. Yet none of this would’ve happened if it weren’t for the timing (market timing is most underrated startup ingredient). Mark my words: the Web is going to dramatically change in 2025 – much more than we all appreciate. Crazy new AI & computer-use models are incoming. I promise you that new browsers will be the story of 2025 (The Browser Company aside). Why? The browser layer is the obvious epicenter of AI & Agents because of its unique context, cookies, & apps. 6. To build a breakthrough consumer product (#1) – like truly breakthrough – you need a catalyzing innovation or technology. AI will be that for the next era of browsers, whether we win or someone else does. So why us (other than Arc is niche)? Our belief is that not only do you need the browser layer to win, but “the hard part” is nailing the interface, the interactions, the storytelling. That’s our bread & butter. That’s the expertise of our team. Now you can see how these puzzle pieces fit together… We built something people love (in Arc) and we intend to stick by it. But we also won’t lose sight of why our team poured so much blood, sweat and tears over the past 4 years into this company: the mission to build a new interface to the internet used by hundreds of millions of people every day. It truly feels like the moment we were waiting for is here and we won’t miss it. Everything we’ve done up until this point was for this type of window, even if we couldn’t have predicted it would play out exactly this way. We’re hopeful that more of you will understand why we’re building this second product soon. I feel confident you will once we can show you more of what we’re dreaming up, and once more of the things we’ve heard and seen in the industry reveal themselves soon. Candidly, we wanted to wait on this announcement but random stuff was leaking and it seemed wrong for you to hear from anyone except us first. We’ve always been at our best when we’re open & honest. We’ll continue to be. Finally, THANK YOU, again, for the love & tough love. We don’t take it for granted. We can’t wait to ship, ship, ship in early 2025!
0:57

Grateful for the outpouring the past few days. I can’t tell you how motivating it is to have people care so much about Arc. The encouragement, the criticism, the confusion. Took it all in <3 As a thank you, I’d like to speak more plainly about what’s happening and why – we owe it to you: 1. Every person who joined or invested in our company did so to build products beloved by hundreds of millions of people. “We want to be to the browser what the iPhone was to the cellphone” has been our rallying cry since Day One. We knew chance of success was low but the ambition made us leap out of bed every morning. 2. Arc is beloved, popular, and growing (4x daily actives YoY). But it’s now clear that what most people love about the product *is also* what will prevent it from reaching hundreds of millions of people in our target demographic (people who spend hours in their browsers each day for their livelihood). Arc is a niche browser, even if we did not intend for it to be so. 3. Luckily, we architected this company – from company name to investors and technical architecture – to support multiple products since Day One. See Arc Search. Our favorite brands have multiple product lines in the same category too (Apple, Nike, Disney). Hence our realization: why keep trying to make Arc something it is not? Nobody who loved Arc wanted Arc Max. Arc members just want it to be more stable, secure, and performant. “Let’s just do that!” 4. With Arc as our beloved but niche browser #1, we asked ourselves a simple question: if we founded the company TODAY (in 2024), with everything that we know, what would the browser of the future look like for hundreds of millions of people? Let’s go build *that* product, alongside Arc. A second browser that is easier to use, more focused, and more powerful. All in order to live up to our founding mission (#1 above). 5. Yet none of this would’ve happened if it weren’t for the timing (market timing is most underrated startup ingredient). Mark my words: the Web is going to dramatically change in 2025 – much more than we all appreciate. Crazy new AI & computer-use models are incoming. I promise you that new browsers will be the story of 2025 (The Browser Company aside). Why? The browser layer is the obvious epicenter of AI & Agents because of its unique context, cookies, & apps. 6. To build a breakthrough consumer product (#1) – like truly breakthrough – you need a catalyzing innovation or technology. AI will be that for the next era of browsers, whether we win or someone else does. So why us (other than Arc is niche)? Our belief is that not only do you need the browser layer to win, but “the hard part” is nailing the interface, the interactions, the storytelling. That’s our bread & butter. That’s the expertise of our team. Now you can see how these puzzle pieces fit together… We built something people love (in Arc) and we intend to stick by it. But we also won’t lose sight of why our team poured so much blood, sweat and tears over the past 4 years into this company: the mission to build a new interface to the internet used by hundreds of millions of people every day. It truly feels like the moment we were waiting for is here and we won’t miss it. Everything we’ve done up until this point was for this type of window, even if we couldn’t have predicted it would play out exactly this way. We’re hopeful that more of you will understand why we’re building this second product soon. I feel confident you will once we can show you more of what we’re dreaming up, and once more of the things we’ve heard and seen in the industry reveal themselves soon. Candidly, we wanted to wait on this announcement but random stuff was leaking and it seemed wrong for you to hear from anyone except us first. We’ve always been at our best when we’re open & honest. We’ll continue to be. Finally, THANK YOU, again, for the love & tough love. We don’t take it for granted. We can’t wait to ship, ship, ship in early 2025!

Josh Miller

189,216 次观看 • 1 年前

Hi Amazon MGM Studios, Many of us now work in filmmaking because of shows like Stargate SG-1. It inspired us with its rich lore, believable character interactions, human drama, and its grounded military science fiction setting. It showed the progress of humanity from its first baby steps through an unknown portal into a space-faring species. The show was hopeful, human, and naturally diverse. It showed the world and mankind coming together despite our differences to create something better. Indeed, that is what the core of Stargate is and always has been. We are from around the world. We are men, women, fathers, mothers, grandparents, grandchilren, and proud of the values Stargate has always stood for. It's rare for a franchise that appeals to people across a political divide, but Stargate always has. It has always stood for the message that we are stronger together. These are the fans. Martin Gero, Joe Mallozzi, Brad Wright, and everyone else involved have had decades to understand this. There is no better team to trust than the ones who've been there with us the longest. It's a symbiotic relationship. I, and every Stargate fan, urge you to reconsider during this Window of Opportunity. The writing team was in the middle of their backswing during the cancellation announcement. At least let them finish a season. We are worth taking a chance on! I'm Emerald May, and I work in visual effects in Atlanta and I'm proud of shows like Stargate SG-1, Atlantis, and Universe that helped steer my career into a place where we make worlds come true. Thank you.
1:44

Hi Amazon MGM Studios, Many of us now work in filmmaking because of shows like Stargate SG-1. It inspired us with its rich lore, believable character interactions, human drama, and its grounded military science fiction setting. It showed the progress of humanity from its first baby steps through an unknown portal into a space-faring species. The show was hopeful, human, and naturally diverse. It showed the world and mankind coming together despite our differences to create something better. Indeed, that is what the core of Stargate is and always has been. We are from around the world. We are men, women, fathers, mothers, grandparents, grandchilren, and proud of the values Stargate has always stood for. It's rare for a franchise that appeals to people across a political divide, but Stargate always has. It has always stood for the message that we are stronger together. These are the fans. Martin Gero, Joe Mallozzi, Brad Wright, and everyone else involved have had decades to understand this. There is no better team to trust than the ones who've been there with us the longest. It's a symbiotic relationship. I, and every Stargate fan, urge you to reconsider during this Window of Opportunity. The writing team was in the middle of their backswing during the cancellation announcement. At least let them finish a season. We are worth taking a chance on! I'm Emerald May, and I work in visual effects in Atlanta and I'm proud of shows like Stargate SG-1, Atlantis, and Universe that helped steer my career into a place where we make worlds come true. Thank you.

Jilted Valkyrie

60,070 次观看 • 3 个月前

I miss building simple, working software. At some point, we decided to complicate everything for no reason. Today, people can't build anything without using three frameworks, 17 libraries, and a swarm of microservices. And here is a funny paradox: To understand how these complex systems work, we've had to build systems and tools that generate data we can later analyze. But the more data we produce, the harder it is to process and make sense of it. We are in the middle of an observability crisis. The tools we have are inefficient, and we don't have enough people to keep systems running. A few weeks ago, I met the team Resolve AI, and they have built a fundamentally new approach to observability and incident management: Instead of depending on humans to run a system, Resolve built a Production Software Engineer who runs the system using AI while letting people supervise. And it's not only crazy, but I think this will fundamentally change how we monitor and maintain systems in production for years to come. I recorded a quick video to showcase a simple example of how Resolve works behind the scenes. There are two main things I'd like you to notice: 1. The tool can correlate data across logs, metrics, and traces coming from different systems. You don't have to do any work to get the information that matters right in front of you. 2. (This is the big one!) The tool can diagnose what's happening and give you instructions on how to solve it. It can produce causal relationships across the entire system stack. Resolve is backed by investors like Replit's founder Amjad Masad, Reid Hoffman, Jeff Dean, Fei Fei Li, Andy Price, among others. They are currently working with a select number of companies and want to onboard a few more. If you are interested in trying them out, go to this link: Honestly, this is one of the most impressive uses of AI I've seen.
5:18

I miss building simple, working software. At some point, we decided to complicate everything for no reason. Today, people can't build anything without using three frameworks, 17 libraries, and a swarm of microservices. And here is a funny paradox: To understand how these complex systems work, we've had to build systems and tools that generate data we can later analyze. But the more data we produce, the harder it is to process and make sense of it. We are in the middle of an observability crisis. The tools we have are inefficient, and we don't have enough people to keep systems running. A few weeks ago, I met the team Resolve AI, and they have built a fundamentally new approach to observability and incident management: Instead of depending on humans to run a system, Resolve built a Production Software Engineer who runs the system using AI while letting people supervise. And it's not only crazy, but I think this will fundamentally change how we monitor and maintain systems in production for years to come. I recorded a quick video to showcase a simple example of how Resolve works behind the scenes. There are two main things I'd like you to notice: 1. The tool can correlate data across logs, metrics, and traces coming from different systems. You don't have to do any work to get the information that matters right in front of you. 2. (This is the big one!) The tool can diagnose what's happening and give you instructions on how to solve it. It can produce causal relationships across the entire system stack. Resolve is backed by investors like Replit's founder Amjad Masad, Reid Hoffman, Jeff Dean, Fei Fei Li, Andy Price, among others. They are currently working with a select number of companies and want to onboard a few more. If you are interested in trying them out, go to this link: Honestly, this is one of the most impressive uses of AI I've seen.

Santiago

82,074 次观看 • 2 年前

Big Tech's $1 trillion AI moat just got DESTROYED by a free Chinese download. Microsoft, Amazon, Google, and Meta are pouring fortunes into chips and data centers because they have been told that whoever builds the biggest model wins, and that lead becomes a fortress no one can cross. Last week a lab called Zhipu - it trades in Hong Kong as Knowledge Atlas Technology - released a model called GLM-5.2 and destroyed that idea in a single afternoon. It's open weights under an MIT license, which means anyone on earth can download it and build on it for free. On the coding and design benchmarks that actually matter, it went toe to toe with the best models America has - matching even Anthropic's Mythos-class work and beating OpenAI's flagship outright on the coding test everyone watches. And it does the work at roughly one-sixth the price. ONE-SIXTH And barely a year and a half ago a model called DeepSeek did the same thing and wiped the better part of $600 billion off Nvidia in a single session. This was only the first chapter. You cannot dig a moat around something your competitor is happy to give away. If 95% of frontier capability is free, open, and runs at a fraction of the cost, then the hundreds of billions being spent to defend the last 5% is NOT a moat. And now for the irony: The company that just proved the moat is worthless is itself the single most absurd valuation I have seen in a long career of watching absurd valuations. Zhipu did about $105 million in revenue last year and lost more than 4x what it took in. This week the market handed it a value of roughly $128 billion - at the peak, north of a 1,000x sales - on a float so thin that barely 4% of the stock actually trades. THINK about this... A company drowning in losses, doing 9 figures of revenue, priced like it does hundreds of billions, with almost nothing available to sell. So we now have a bubble in China detonating the entire justification for a bubble in America. Two manias pointed straight at each other. This is the lesson I've spent 45 years trying to beat into people. You can ignore valuation for a long time but you cannot ignore it forever. A moat story sold a trillion dollars of spending, a free download just exposed it, and the company that exposed it is priced for a fantasy of its own. When the picks-and-shovels crowd loses its monopoly on the picks, you want to be very careful what you are paying for the shovels. Numbers don't lie. Shoutout to Limitless - they were onto this story before almost anyone on Wall Street. One of the sharpest AI shows out there.
0:46

Big Tech's $1 trillion AI moat just got DESTROYED by a free Chinese download. Microsoft, Amazon, Google, and Meta are pouring fortunes into chips and data centers because they have been told that whoever builds the biggest model wins, and that lead becomes a fortress no one can cross. Last week a lab called Zhipu - it trades in Hong Kong as Knowledge Atlas Technology - released a model called GLM-5.2 and destroyed that idea in a single afternoon. It's open weights under an MIT license, which means anyone on earth can download it and build on it for free. On the coding and design benchmarks that actually matter, it went toe to toe with the best models America has - matching even Anthropic's Mythos-class work and beating OpenAI's flagship outright on the coding test everyone watches. And it does the work at roughly one-sixth the price. ONE-SIXTH And barely a year and a half ago a model called DeepSeek did the same thing and wiped the better part of $600 billion off Nvidia in a single session. This was only the first chapter. You cannot dig a moat around something your competitor is happy to give away. If 95% of frontier capability is free, open, and runs at a fraction of the cost, then the hundreds of billions being spent to defend the last 5% is NOT a moat. And now for the irony: The company that just proved the moat is worthless is itself the single most absurd valuation I have seen in a long career of watching absurd valuations. Zhipu did about $105 million in revenue last year and lost more than 4x what it took in. This week the market handed it a value of roughly $128 billion - at the peak, north of a 1,000x sales - on a float so thin that barely 4% of the stock actually trades. THINK about this... A company drowning in losses, doing 9 figures of revenue, priced like it does hundreds of billions, with almost nothing available to sell. So we now have a bubble in China detonating the entire justification for a bubble in America. Two manias pointed straight at each other. This is the lesson I've spent 45 years trying to beat into people. You can ignore valuation for a long time but you cannot ignore it forever. A moat story sold a trillion dollars of spending, a free download just exposed it, and the company that exposed it is priced for a fantasy of its own. When the picks-and-shovels crowd loses its monopoly on the picks, you want to be very careful what you are paying for the shovels. Numbers don't lie. Shoutout to Limitless - they were onto this story before almost anyone on Wall Street. One of the sharpest AI shows out there.

George Noble

71,531 次观看 • 3 个月前

As many of you know, for the last five months I've been working full-time on my next big thing. The challenge was to invent something new and implement it entirely using LLMs for writing code. The first stage of the project is now complete: the web application, which I called is now online and accepting users. You can see a short demo in the video. 100% of the code of the app was generated by LLMs (mostly Gemini and Claude, maybe 10% of ChatGPT). I haven't written a single line of code. The tech stack is TypeScript, React, and Supabase/Postgres which was (and still is) fully new to me. During these five months, I implemented from scratch three versions of the software. It started as a Markdown editor to help me with my book writing and ended up as an AI-assisted reading and self-learning platform. What makes ChapterPal unique is a novel reading experience where the user can use the keyboard keys to reveal or "unreveal" the content and ask questions at any moment. (Mouse wheel, touchpad, smartphone screen, and voice input are also supported.) The LLM receives the entire content of the chapter and tries to answer questions based on the chapter's content, which reduces the chance of hallucination to the minimum. (Though not to 0%, of course, but near it.) This way of content consumption is known as **active reading,** a strategy for engaging with a text to improve comprehension and retention by consciously interacting with the material. The goal is to move beyond passive reading to a deeper understanding of the text and to remember key information more effectively. The registration on ChapterPal is via the waiting list. This is to avoid unexpected load spikes and cloud charges. Usually, it takes less than 24 hours for me to activate a user. Give it a try and let me know what you think. The next stage is finishing the content ingestion pipeline, which will automatically convert high-quality content from sources like HTML, PDF, and LaTeX into Markdown. Obviously, only those pieces whose licenses allow creating copies. ChapterPal has its own collection of textbooks and articles on AI, machine learning, and data science topics. If you don't find a piece of content you would like to read in ChapterPal's collection, a Chrome extension, ChapterPal Uploader, allows you to upload any PDF or HTML page to ChapterPal in one click. The content is only available for you to read to avoid the possibility of copyright infringement. I hope you enjoy using it as much as I enjoy building it.
3:41

As many of you know, for the last five months I've been working full-time on my next big thing. The challenge was to invent something new and implement it entirely using LLMs for writing code. The first stage of the project is now complete: the web application, which I called is now online and accepting users. You can see a short demo in the video. 100% of the code of the app was generated by LLMs (mostly Gemini and Claude, maybe 10% of ChatGPT). I haven't written a single line of code. The tech stack is TypeScript, React, and Supabase/Postgres which was (and still is) fully new to me. During these five months, I implemented from scratch three versions of the software. It started as a Markdown editor to help me with my book writing and ended up as an AI-assisted reading and self-learning platform. What makes ChapterPal unique is a novel reading experience where the user can use the keyboard keys to reveal or "unreveal" the content and ask questions at any moment. (Mouse wheel, touchpad, smartphone screen, and voice input are also supported.) The LLM receives the entire content of the chapter and tries to answer questions based on the chapter's content, which reduces the chance of hallucination to the minimum. (Though not to 0%, of course, but near it.) This way of content consumption is known as **active reading,** a strategy for engaging with a text to improve comprehension and retention by consciously interacting with the material. The goal is to move beyond passive reading to a deeper understanding of the text and to remember key information more effectively. The registration on ChapterPal is via the waiting list. This is to avoid unexpected load spikes and cloud charges. Usually, it takes less than 24 hours for me to activate a user. Give it a try and let me know what you think. The next stage is finishing the content ingestion pipeline, which will automatically convert high-quality content from sources like HTML, PDF, and LaTeX into Markdown. Obviously, only those pieces whose licenses allow creating copies. ChapterPal has its own collection of textbooks and articles on AI, machine learning, and data science topics. If you don't find a piece of content you would like to read in ChapterPal's collection, a Chrome extension, ChapterPal Uploader, allows you to upload any PDF or HTML page to ChapterPal in one click. The content is only available for you to read to avoid the possibility of copyright infringement. I hope you enjoy using it as much as I enjoy building it.

BURKOV

81,258 次观看 • 10 个月前

I'd like to introduce you to Creator Buddy, the greatest AI content tool ever made It's 8 AI tools in one to help you come up with endless bangers, explode your engagement, and grow your network faster than you can imagine It's going to change the way you use X forever Over the last 3 years I've grown from 0 to 260,000 followers on X I did this completely organically. No bots or retweet groups. All through banger content and reply guying I took every system and strategy I used to get to 260k and 6 figures of revenue on X and put them in this tool Then I powered it all by AI so it's 10x smarter and easier to use This isn't your mother's AI either. This is an AI trained on millions of X posts. Trained on what works and what doesn't This AI will create better content than you've ever seen in your entire life I'm not kidding. BANGERS only It's also everything I wanted Grok to be but never was It's an AI that knows your post history so you can ask it questions like: • What topics get me the most engagement? • What hooks get me likes? • What time of day does my audience engage with me? • What calls to actions get me clicks? • I have no idea what to write about. Based on my past successful posts give me a template It will seriously change the way you create content forever. No more writer's block. No more flopped posts. No more posting into the void. And that's not even 10% of the functionality: • It also has an AI trained on the entire X algorithm so you know if your post will be algo friendly BEFORE you post • A reply guy tool that will help you be the LOUDEST reply guy on X • An AI account researching tool that is basically your own spy on X • A chrome extension that allows you to save posts directly from X and repurpose into your own voice with AI • A brain dumping tool that allows you to take whatever is on your mind and INSTANTLY turn it into content This is my life's work. I truly believe this will take your X game to the next level If you're taking X seriously, you HAVE to get Creator Buddy I truly believe moving forward there will be 2 groups of people on X: those with Creator Buddy and those without. Trust me, you want to be in the group with it I've worked endlessly the last 7 months on building this by myself. No help whatsoever Every line of code, every video, EVERYTHING was done by me. 0 help. I sacrificed everything for this tool Hit the link below and start working with your own personalized AI content coach now! And if I've ever provided you even a tiny bit of value over the last 3 years, all I ask for is a simple like and RT on this post! With love, Alex (link to Creator Buddy on next post!!!)
3:56

I'd like to introduce you to Creator Buddy, the greatest AI content tool ever made It's 8 AI tools in one to help you come up with endless bangers, explode your engagement, and grow your network faster than you can imagine It's going to change the way you use X forever Over the last 3 years I've grown from 0 to 260,000 followers on X I did this completely organically. No bots or retweet groups. All through banger content and reply guying I took every system and strategy I used to get to 260k and 6 figures of revenue on X and put them in this tool Then I powered it all by AI so it's 10x smarter and easier to use This isn't your mother's AI either. This is an AI trained on millions of X posts. Trained on what works and what doesn't This AI will create better content than you've ever seen in your entire life I'm not kidding. BANGERS only It's also everything I wanted Grok to be but never was It's an AI that knows your post history so you can ask it questions like: • What topics get me the most engagement? • What hooks get me likes? • What time of day does my audience engage with me? • What calls to actions get me clicks? • I have no idea what to write about. Based on my past successful posts give me a template It will seriously change the way you create content forever. No more writer's block. No more flopped posts. No more posting into the void. And that's not even 10% of the functionality: • It also has an AI trained on the entire X algorithm so you know if your post will be algo friendly BEFORE you post • A reply guy tool that will help you be the LOUDEST reply guy on X • An AI account researching tool that is basically your own spy on X • A chrome extension that allows you to save posts directly from X and repurpose into your own voice with AI • A brain dumping tool that allows you to take whatever is on your mind and INSTANTLY turn it into content This is my life's work. I truly believe this will take your X game to the next level If you're taking X seriously, you HAVE to get Creator Buddy I truly believe moving forward there will be 2 groups of people on X: those with Creator Buddy and those without. Trust me, you want to be in the group with it I've worked endlessly the last 7 months on building this by myself. No help whatsoever Every line of code, every video, EVERYTHING was done by me. 0 help. I sacrificed everything for this tool Hit the link below and start working with your own personalized AI content coach now! And if I've ever provided you even a tiny bit of value over the last 3 years, all I ask for is a simple like and RT on this post! With love, Alex (link to Creator Buddy on next post!!!)

Alex Finn

1,582,771 次观看 • 1 年前