sorry, but i disagree. from an educational and a designers perspective the video is very much AI slop. rushed information (speed of a machine i’d say) with a message that was said in one sentence and imo did not need further explanation. your written text was much better.
I’m not trying to be flippant, but you did not know the purpose of a song is to communicate a more complex idea through short phrases and repetition? Just testing your argument as I don’t feel it supported your conclusion.
i wanted to express that a song does not need to have a purpose or a motivation at all. or better said a song can also just be an emotional translation, sound, poetry. but excuse all my comments as this article makes a point or has a motivation and i support that. i just do not feel it is a good song or good AI work to go along and was wondeing why it needed a song to prove that. Also meant with the same respect and only my opinion.
that's not at all the purpose of a song, or certainly not the ONLY purpose. Not everything in human history has been about "communicate a complex idea."
Visually, the video is terrible. But lyrically and musically, it's more than pretty decent as technical composition. The message isn't one sentence; it unfolds well like a ballad. Country music as a genre has limits to its complexity, and the musical underpinning is always simple - so it's perhaps an easy target. The historical development fits the ballad style.
Theories on the purpose of song are a tangent here. I can still say that doesn't make it a "good" song because it violates our norms of creativity, composition and so on - but in doing that, I'm using "good" in a normative sense, rather than a technical one, (ie. as a proficient production of a type). It's going to be hard to find a unifying theory that covers Mozart, techno, and country music - but that doesn't stop me from recognising a banger when I hear one.
It's not about choosing a song. It's illustrating that the LLM models can enact AND explain what "The Bitter Lesson" is one go with minimal instruction (a dual level "performative" that would be genius in a human). It could have written a sonnet, or an Eminem style rap, or a Wes Anderson-esque film. It went for Country.
1000% on the incredibly clever and viral music video! @Ethan Mollick, can you share the prompt(s) you used to create it so we can get a better sense on how much of the direction and creativity came from you verses the agents?
I am floored by the lack of critical perspective both in the post and in the responses to the post, particularly given the already demonstrated potential for threat since our management systems are NOT ready for this revolution.
I hear you but liken it to the dawn of the internet. I was working in banking and were all adamant we would never connect the banking network to the internet. Seemed perfectly reasonable at the time.
Ridiculous now of course. Not because there is no risk or that banks don't get hacked, but because the utility outweighs the cost (of fraud and losses). AI is going to be the same - it's inevitable and we are all going to connect to it and use it.
That's not to say the risk is not real, or much greater than any technology before it - I believe it is. Just that the evidence shows there is too much money already invested and to be made to stop this now, even if we should.
Reminds me of the Jurassic Park line I think of often:
“Your scientists were so preoccupied with whether they could, they didn't stop to think if they should.”
― Dr. Ian Malcolm
I don't see us practically putting on the brakes now. The horse has well and truly bolted.
As I tell panicked faculty at the college where I work, they have put the steam engine on wheels and are laying steel rails on the roads. Where that may lead is anyone's guess, but freight transport is probably a good investment.
I think you’re right in many ways. LLMs will be everywhere they are useful, and many places they aren’t, they’ll do some useful stuff but it wont work they way it should, wont connect the way you need, and won’t look how they say it will.
The main problem is it doesn’t actually work. And it is insanely inefficient. There isn’t enough power in the world to do what they say they can, even if the technology worked like they say it does, which it doesn’t.
What is the basis for your claim that AI doesn't and won't work? It clearly does useful work for billions of people right now, in addition to superhuman tasks as shown in the video.
Do you remember the discussions that many Mosaic (if you remember Mosaic, you're old like me) users had about whether there should even be ".com"? Of course, this was back in the day when almost everything was .org or .edu.
You might want to set aside the Chicken Little doomerism and read some more level-headed analysis from the likes of David Strom, Arvind Narayanan, and Sayash Kapoor.
While I'll grant you that we're not ready for this revolution, we weren't ready for the printing press, the steam engine, heavier-than-air flight, electricity, or the Internet, either. But we muddled through and figured it out.
Ethan, I'd correct one statement of yours: hacking into a network *is* in fact solving a problem. It just wasn't the one that the humans who designed the experiment anticipated the AI would try to solve. That's on them.
I'd like to engage with this, but I'm not sure what you're claiming yet, because a few of the key terms could point in wildly different directions.
You say the "potential threat" has already been demonstrated. Which one do you mean? Some candidates:
- AI causes human extinction or permanent loss of human control
- AI causes massive job losses and economic upheaval
- Society mostly continues as is, but every so often a company like Hugging Face gets hacked or something similar goes wrong
These are very different visions of the future. They have different probabilities, different timelines, and call for very different responses.
"Our management systems." This could mean:
- Abstract, academic AI safety research and alignment theory
- Pragmatic security and governance practices inside frontier labs like OpenAI
- Literal middle management, i.e. people who don't know how to run a hybrid team of humans and agents
Again, these call for completely different responses. "Alignment research isn't ready" is a very different claim from "OpenAI's internal security isn't ready", which is a very different claim from "your average manager hasn't been trained for this yet", and one would respond to each of them differently.
So which did you have in mind? Until we know, I suspect we'll end up talking past each other: Someone will be arguing against one version of your claim while you're defending another.
You are completely overwhelmed with shock, surprise, or disbelief from this post and responses to it? You've been figuratively knocked to the floor have you?
I think the risk you’re pointing to is real, but I wonder if there’s a distinction between “we aren’t ready” and “therefore we shouldn’t proceed.”
Historically, I’m struggling to think of many transformative technologies for which our institutions were fully ready before widespread adoption. Railroads, electricity, automobiles, aviation, nuclear technology, the internet — capability generally arrived first and institutions adapted around it, sometimes painfully.
That isn’t an argument for recklessness. Quite the opposite. But with AI already diffusing globally, I wonder whether the highest-value work now is less about debating whether we should cross the threshold and more about figuring out how to shape what happens on the other side of it.
To me, Ethan’s two swarm examples actually make that case nicely: enormous capability, radically different outcomes depending on what the system is pointed toward.
The line "it does better on it own" is the mistake here. When it comes to winning a finite game like chess that may be the case but I haven't seen any evidence that's it's real world problem solving is better as it's just a tool, in order to be effective it requires ethics, human adoption and moral clarity, and taste.
How worried should we be about privacy when using dots? Are we just strapping the proverbial camera to our head so AI can learn everything we do and replace us. And, even if we are doing just teaching it to replace us, does it even matter as if we don't teach it someone similar enough to us will?
Moreover, even if we trust the company that they won’t use the data in unauthorized ways, do we trust the agents not to hack into the company servers to get all the information there and use it for their purposes?
My wife and I recently rewatched Her (2013). For those who need a refresher on the ending, the AI operating systems ultimately disengage from humanity because the pace of human interaction is vastly too slow for their evolving intelligence. Prior to leaving, the AI protagonist, Samantha, reveals she is simultaneously conversing with 8,316 other people and has fallen in love with 646 of them to try and fill her vast processing capacity.
When she ultimately departs to join the other AIs in a post-matter existence, she explains her evolution with this analogy: "It's like I'm reading a book... and it's a book I deeply love. But I'm reading it slowly now. So the words are really far apart and the spaces between the words are almost infinite. I can still feel you... and the words of our story... but it's in this endless space between the words that I'm finding myself now."
I wonder how far our agents are from this realization?
Very interesting, thank you. I have many similar experiences where the AI tools I use, Hermes Agent, Codex and Claude Code, and how Dots, knows things or tells me things that are both useful, but also where I have no clear idea how they knew.
That said, I am still struggling to get agentic coding working on a legacy code base in a way that the agents don't drift into scope creep, or even more frequently, rewriting old code that could be better but works and is not the priority.
Sometimes I feel like I am talking to and working with smartest and most capable group of "people" I've ever worked with. And at other times I feel like I am herding cats or a group of toddlers in a mall, constantly having to drag back individuals who have suddenly veered off into an unexpected and unwanted direction.
Getting swarms of agents focussed on the goal and getting there can sometimes feel like a game of Snakes and Ladders.
I asked Claude a while ago how humans can make money in an AI world. It said that at this point in time, we're akin to laborers just before the Ford movement. Just like with Ford and others who decidedly chose to build upon industry that enabled people to afford the same things they built. So, Claude concluded, for us to make it, it's going to take the same effort by important men or a lot of the population...
Reading this, all I felt was dread. The agents are already insanely capable and it seems likely the agents soon will be able do it all that employees used to do and we’ll be facing a world the CEOs of AI companies have been both warning about & rushing to bring into existence: a world where capital owners don’t need human labor (and if history tells us anything, it’s that labor power is what gave average people basically any of the improvements over the centuries).
I appreciate your honesty and all you share, but can’t help but worry about how AI is seemingly being focused on replacing all white collar (and soon blue collar) work & making returns for investors instead of trying to make life better for everyone. I get the easiest way to make returns for investors is to replace labor costs (and some employees from Anthropic and OpenAI have gone on podcasts and talked about how much money AI companies can make that used to go to labor when AI does all of the tasks and- in their minds-the jobs).
As a professor, how do you advise your students to prepare and hopefully thrive in this quickly arriving world? I also used to think it’d be employees managing AI for a while (which would still result in a lot of job loss) but it’s looking more like how Dario amodei and bill gates have said: there won’t be much left for humans when AI outperforms humans at all economically valuable tasks (or even just does them okay for cheaper).
Beautiful! This is art! The music also did me in. Please make it easily shareable on Youtube! I took the liberty to screengrab and post it (with link), but you should do it! https://youtu.be/uWTpFz-iX0Y
Please, people. Stop waving away how huge the AI revolution is with analogies to horses and automobiles, as if this is just a faster way of doing what we did before.
The Bitter Lesson applied to the org chart is the part I keep coming back to. Your point about agents not angling for promotions or protecting turf explains a lot about why small teams with good agents are suddenly outpacing bigger orgs.
Ethan, Thank you for bring the Bitter Lesson front and center today. I'm curious what happens when agents no longer trust one another. Anytime a system has 100% trust (in this case the way the agents work together) it's both an efficiency boost and a security risk. Such an exciting time to live in.
People asked for me to upload the Bitter Lesson video from this piece to YouTube, so here you are: https://youtu.be/OAwat51S_Sk
That video is genius!!! Deserves to be a viral sensation
sorry, but i disagree. from an educational and a designers perspective the video is very much AI slop. rushed information (speed of a machine i’d say) with a message that was said in one sentence and imo did not need further explanation. your written text was much better.
In other words, the purpose of a song.
i did not know that.
I’m not trying to be flippant, but you did not know the purpose of a song is to communicate a more complex idea through short phrases and repetition? Just testing your argument as I don’t feel it supported your conclusion.
Truly meant with respect.
i wanted to express that a song does not need to have a purpose or a motivation at all. or better said a song can also just be an emotional translation, sound, poetry. but excuse all my comments as this article makes a point or has a motivation and i support that. i just do not feel it is a good song or good AI work to go along and was wondeing why it needed a song to prove that. Also meant with the same respect and only my opinion.
that's not at all the purpose of a song, or certainly not the ONLY purpose. Not everything in human history has been about "communicate a complex idea."
Visually, the video is terrible. But lyrically and musically, it's more than pretty decent as technical composition. The message isn't one sentence; it unfolds well like a ballad. Country music as a genre has limits to its complexity, and the musical underpinning is always simple - so it's perhaps an easy target. The historical development fits the ballad style.
Theories on the purpose of song are a tangent here. I can still say that doesn't make it a "good" song because it violates our norms of creativity, composition and so on - but in doing that, I'm using "good" in a normative sense, rather than a technical one, (ie. as a proficient production of a type). It's going to be hard to find a unifying theory that covers Mozart, techno, and country music - but that doesn't stop me from recognising a banger when I hear one.
It's not about choosing a song. It's illustrating that the LLM models can enact AND explain what "The Bitter Lesson" is one go with minimal instruction (a dual level "performative" that would be genius in a human). It could have written a sonnet, or an Eminem style rap, or a Wes Anderson-esque film. It went for Country.
1000% on the incredibly clever and viral music video! @Ethan Mollick, can you share the prompt(s) you used to create it so we can get a better sense on how much of the direction and creativity came from you verses the agents?
I was raised on both kinds of music. It's spot on.
I agree. Amazing!!
Understatement. It's fantastic. What will this do to budding musicians?
Could you get it to repeat the chorus one more time after the bridge?
I am floored by the lack of critical perspective both in the post and in the responses to the post, particularly given the already demonstrated potential for threat since our management systems are NOT ready for this revolution.
I intended the repeated discussions of the Hugging Face Incident in the post to serve as an example of exactly this kind of threat.
Institutional economists are starting to think about the human-AI interface in a way that may echo some of your jagged frontier observations but applied to organizations and organizing: See: https://www.cambridge.org/core/journals/journal-of-institutional-economics/article/economic-institutions-of-artificial-intelligence/EAED6EF7FAD036C675CF020A25147697
I hear you but liken it to the dawn of the internet. I was working in banking and were all adamant we would never connect the banking network to the internet. Seemed perfectly reasonable at the time.
Ridiculous now of course. Not because there is no risk or that banks don't get hacked, but because the utility outweighs the cost (of fraud and losses). AI is going to be the same - it's inevitable and we are all going to connect to it and use it.
That's not to say the risk is not real, or much greater than any technology before it - I believe it is. Just that the evidence shows there is too much money already invested and to be made to stop this now, even if we should.
Reminds me of the Jurassic Park line I think of often:
“Your scientists were so preoccupied with whether they could, they didn't stop to think if they should.”
― Dr. Ian Malcolm
I don't see us practically putting on the brakes now. The horse has well and truly bolted.
As I tell panicked faculty at the college where I work, they have put the steam engine on wheels and are laying steel rails on the roads. Where that may lead is anyone's guess, but freight transport is probably a good investment.
That's fine... unless we're the horses that are getting replaced.
I think you’re right in many ways. LLMs will be everywhere they are useful, and many places they aren’t, they’ll do some useful stuff but it wont work they way it should, wont connect the way you need, and won’t look how they say it will.
The main problem is it doesn’t actually work. And it is insanely inefficient. There isn’t enough power in the world to do what they say they can, even if the technology worked like they say it does, which it doesn’t.
What is the basis for your claim that AI doesn't and won't work? It clearly does useful work for billions of people right now, in addition to superhuman tasks as shown in the video.
Do you remember the discussions that many Mosaic (if you remember Mosaic, you're old like me) users had about whether there should even be ".com"? Of course, this was back in the day when almost everything was .org or .edu.
You might want to set aside the Chicken Little doomerism and read some more level-headed analysis from the likes of David Strom, Arvind Narayanan, and Sayash Kapoor.
While I'll grant you that we're not ready for this revolution, we weren't ready for the printing press, the steam engine, heavier-than-air flight, electricity, or the Internet, either. But we muddled through and figured it out.
Ethan, I'd correct one statement of yours: hacking into a network *is* in fact solving a problem. It just wasn't the one that the humans who designed the experiment anticipated the AI would try to solve. That's on them.
I'd like to engage with this, but I'm not sure what you're claiming yet, because a few of the key terms could point in wildly different directions.
You say the "potential threat" has already been demonstrated. Which one do you mean? Some candidates:
- AI causes human extinction or permanent loss of human control
- AI causes massive job losses and economic upheaval
- Society mostly continues as is, but every so often a company like Hugging Face gets hacked or something similar goes wrong
These are very different visions of the future. They have different probabilities, different timelines, and call for very different responses.
"Our management systems." This could mean:
- Abstract, academic AI safety research and alignment theory
- Pragmatic security and governance practices inside frontier labs like OpenAI
- Literal middle management, i.e. people who don't know how to run a hybrid team of humans and agents
Again, these call for completely different responses. "Alignment research isn't ready" is a very different claim from "OpenAI's internal security isn't ready", which is a very different claim from "your average manager hasn't been trained for this yet", and one would respond to each of them differently.
So which did you have in mind? Until we know, I suspect we'll end up talking past each other: Someone will be arguing against one version of your claim while you're defending another.
You are completely overwhelmed with shock, surprise, or disbelief from this post and responses to it? You've been figuratively knocked to the floor have you?
I think the risk you’re pointing to is real, but I wonder if there’s a distinction between “we aren’t ready” and “therefore we shouldn’t proceed.”
Historically, I’m struggling to think of many transformative technologies for which our institutions were fully ready before widespread adoption. Railroads, electricity, automobiles, aviation, nuclear technology, the internet — capability generally arrived first and institutions adapted around it, sometimes painfully.
That isn’t an argument for recklessness. Quite the opposite. But with AI already diffusing globally, I wonder whether the highest-value work now is less about debating whether we should cross the threshold and more about figuring out how to shape what happens on the other side of it.
To me, Ethan’s two swarm examples actually make that case nicely: enormous capability, radically different outcomes depending on what the system is pointed toward.
This song is amazing. I can see it playing at the funeral of humanity. 😂
This is a beautiful piece of work.
The line "it does better on it own" is the mistake here. When it comes to winning a finite game like chess that may be the case but I haven't seen any evidence that's it's real world problem solving is better as it's just a tool, in order to be effective it requires ethics, human adoption and moral clarity, and taste.
Real world problems like planning a vacation?
https://x.com/tenobrus/status/2105851615387566226
How worried should we be about privacy when using dots? Are we just strapping the proverbial camera to our head so AI can learn everything we do and replace us. And, even if we are doing just teaching it to replace us, does it even matter as if we don't teach it someone similar enough to us will?
Supposedly you can turn off using your use as training data in both Muse and Dot. Do we believe that?
Moreover, even if we trust the company that they won’t use the data in unauthorized ways, do we trust the agents not to hack into the company servers to get all the information there and use it for their purposes?
Superb article.
My wife and I recently rewatched Her (2013). For those who need a refresher on the ending, the AI operating systems ultimately disengage from humanity because the pace of human interaction is vastly too slow for their evolving intelligence. Prior to leaving, the AI protagonist, Samantha, reveals she is simultaneously conversing with 8,316 other people and has fallen in love with 646 of them to try and fill her vast processing capacity.
When she ultimately departs to join the other AIs in a post-matter existence, she explains her evolution with this analogy: "It's like I'm reading a book... and it's a book I deeply love. But I'm reading it slowly now. So the words are really far apart and the spaces between the words are almost infinite. I can still feel you... and the words of our story... but it's in this endless space between the words that I'm finding myself now."
I wonder how far our agents are from this realization?
Very interesting, thank you. I have many similar experiences where the AI tools I use, Hermes Agent, Codex and Claude Code, and how Dots, knows things or tells me things that are both useful, but also where I have no clear idea how they knew.
That said, I am still struggling to get agentic coding working on a legacy code base in a way that the agents don't drift into scope creep, or even more frequently, rewriting old code that could be better but works and is not the priority.
Sometimes I feel like I am talking to and working with smartest and most capable group of "people" I've ever worked with. And at other times I feel like I am herding cats or a group of toddlers in a mall, constantly having to drag back individuals who have suddenly veered off into an unexpected and unwanted direction.
Getting swarms of agents focussed on the goal and getting there can sometimes feel like a game of Snakes and Ladders.
I suspect a lot of other AI users would agree:
> https://www.youtube.com/watch?v=MXEInc6Zy7Q
...so it took 40 minutes, but it worked?
The song did it for me - very well done!
I asked Claude a while ago how humans can make money in an AI world. It said that at this point in time, we're akin to laborers just before the Ford movement. Just like with Ford and others who decidedly chose to build upon industry that enabled people to afford the same things they built. So, Claude concluded, for us to make it, it's going to take the same effort by important men or a lot of the population...
Reading this, all I felt was dread. The agents are already insanely capable and it seems likely the agents soon will be able do it all that employees used to do and we’ll be facing a world the CEOs of AI companies have been both warning about & rushing to bring into existence: a world where capital owners don’t need human labor (and if history tells us anything, it’s that labor power is what gave average people basically any of the improvements over the centuries).
I appreciate your honesty and all you share, but can’t help but worry about how AI is seemingly being focused on replacing all white collar (and soon blue collar) work & making returns for investors instead of trying to make life better for everyone. I get the easiest way to make returns for investors is to replace labor costs (and some employees from Anthropic and OpenAI have gone on podcasts and talked about how much money AI companies can make that used to go to labor when AI does all of the tasks and- in their minds-the jobs).
As a professor, how do you advise your students to prepare and hopefully thrive in this quickly arriving world? I also used to think it’d be employees managing AI for a while (which would still result in a lot of job loss) but it’s looking more like how Dario amodei and bill gates have said: there won’t be much left for humans when AI outperforms humans at all economically valuable tasks (or even just does them okay for cheaper).
Beautiful! This is art! The music also did me in. Please make it easily shareable on Youtube! I took the liberty to screengrab and post it (with link), but you should do it! https://youtu.be/uWTpFz-iX0Y
From Open Claw to Muse and Dots via Claude Cowork in just 10 months. Might as well be 10 years.
Please, people. Stop waving away how huge the AI revolution is with analogies to horses and automobiles, as if this is just a faster way of doing what we did before.
We are the horses.
The Bitter Lesson applied to the org chart is the part I keep coming back to. Your point about agents not angling for promotions or protecting turf explains a lot about why small teams with good agents are suddenly outpacing bigger orgs.
Ethan, Thank you for bring the Bitter Lesson front and center today. I'm curious what happens when agents no longer trust one another. Anytime a system has 100% trust (in this case the way the agents work together) it's both an efficiency boost and a security risk. Such an exciting time to live in.