One potential angle: automating software won’t be worth very much if multiple players can do it and profits are competed to zero. Look at compilers—almost no one is writing assembly or their own compilers, and yet the compiler writers haven’t earned billions or trillions of dollars. With many technologies, the vast majority of value is often consumer surplus never captured by producers.
In general I agree with your point. If evidence of transformative AI was close, you’d strategically delay fundraising as late as possible. However, if you have uncertainty about your ability to deliver, investors’ ability to recognize transformative potential, or uncertainty about competition, you might hedge and raise sooner than you need. Raising too early never kills a business. But raising too late always does.
This is a key point for a different discussion: job loss and effect on economies. Supposing writing software is almost all automated. Nobody is going to get the trillions currently spent on it. If just two companies, say Anthropic and OpenAI have agents that automate it, they’ll compete and drive the prices down to near the compute costs (or collude until others make systems that can compete...)
Now those trillions aren’t being spent on writing code. Where do they go? Anticipating how businesses will use their surplus as they pay less wages is probably something someone should be doing. But I don’t know of any economists taking seriously claims like AI doing all coding in a few years let alone a few months.
I’m afraid we’re going to get blindsided because economists aren’t taking the possibility of unprecedented rapid job loss seriously.
So, I certainly wouldn’t expect the AI companies to capture all the value; you’re right that competition drives the profits down. But, I also don’t think it’s reasonable to expect profits to get competed down to zero. Innovations in IT are generally pretty easy to replicate, technically speaking, but tech companies operate at remarkably high margins. Even at the moment, your various LLMs are similar but are not exact substitutes for one another, which gives each some market power.
One potential angle: automating software won’t be worth very much if multiple players can do it and profits are competed to zero. Look at compilers—almost no one is writing assembly or their own compilers, and yet the compiler writers haven’t earned billions or trillions of dollars. With many technologies, the vast majority of value is often consumer surplus never captured by producers.
In general I agree with your point. If evidence of transformative AI was close, you’d strategically delay fundraising as late as possible. However, if you have uncertainty about your ability to deliver, investors’ ability to recognize transformative potential, or uncertainty about competition, you might hedge and raise sooner than you need. Raising too early never kills a business. But raising too late always does.
This is a key point for a different discussion: job loss and effect on economies. Supposing writing software is almost all automated. Nobody is going to get the trillions currently spent on it. If just two companies, say Anthropic and OpenAI have agents that automate it, they’ll compete and drive the prices down to near the compute costs (or collude until others make systems that can compete...)
Now those trillions aren’t being spent on writing code. Where do they go? Anticipating how businesses will use their surplus as they pay less wages is probably something someone should be doing. But I don’t know of any economists taking seriously claims like AI doing all coding in a few years let alone a few months.
I’m afraid we’re going to get blindsided because economists aren’t taking the possibility of unprecedented rapid job loss seriously.
So, I certainly wouldn’t expect the AI companies to capture all the value; you’re right that competition drives the profits down. But, I also don’t think it’s reasonable to expect profits to get competed down to zero. Innovations in IT are generally pretty easy to replicate, technically speaking, but tech companies operate at remarkably high margins. Even at the moment, your various LLMs are similar but are not exact substitutes for one another, which gives each some market power.