When Content Creation Goes to Zero

Publisher’s note: This essay is an edited and revised version of my original essay on AI that I published last year. In it, I argue that the primary effect of AI will be that it pushes the cost of digital good creation to zero. The original showcased a variety of demos of new AI tools that I ended up cutting. Now, only six months later, all those demos look passé—we are far past them already. What does the world look like in a year? 10? How does a dramatically reduced COGS for code, text, email, etc., affect our world? 

If you enjoyed this post, I’m giving a presentation on it at Every’s conference Thesis, happening this Saturday. 

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The most significant consequence of the internet was that it pushed distribution costs to zero. 

The most significant consequence of AI is that it will push creation costs to zero. 

The atomic activity of any company can be boiled down to:

1. Create stuff
2. Acquire customer to buy stuff
3. Distribute that stuff

The internet broke the third category of distribution, and AI is going to break the first one. Innovations like GPT-3, DALL-E, and other AI tools will dramatically decrease the cost of producing goods with a digital component.

I don’t want to veer into hyperbole, but I’ve never been simultaneously so excited and scared by a technology category. Theoretically, I knew these changes were coming, but I have been stunned by how quickly they have occurred. In 5–10 years, the power dynamics of knowledge work will look radically different. 

For some categories of companies, AI tooling will be a disruptive innovation—one that renders their entire business obsolete. For other categories, it will be a sustaining innovation that can allow them to serve a similar set of customers at decreased costs. It’s unclear which type of company falls into the latter categories.

The biggest question is this: When acquisition is the only thing left to compete for, what does our economy look like?

Downstream impacts

It is intellectually lazy to point to technology as changing markets on its own. That isn’t the case: Truly disruptive technology companies pair novel tech with unique market conditions. Technology alone isn’t sufficient; a company needs to also have incredible marketing, beatable competitors, and the right team. If one of those things is missing, the whole enterprise will fail.

For most existing technology companies, these tools will only cement their market position. It will be easier for analytics tools like Tableau to put in a text prompt box than for a machine learning startup to build an entire visualization suite. So many of these models are based on academic papers and open-source software that a team with a large enough budget will probably be able to build a “good enough” product. AI startups will have to question whether their breakthroughs are defensible and revolutionary enough to justify replacing existing workflows. I don’t have a sufficient level of confidence to hazard a guess at what fields will be replaceable, but power consolidation is the most likely outcome.

I’m more bullish on startups that act as infrastructure providers for other companies. Whether that is API access like OpenAI or something else entirely, picks and shovels are a useful way to outsource risk. Of course, the most bullish use case is startups that can use AI to build stuff that was previously unimaginable. I’m excited to see what a talented class of entrepreneurs can come up with.

My biggest (and perhaps most controversial) hypothesis is that these tools will end up being more disruptive for individual workers than for companies. The disruption will happen in two broad categories:

Creation: We make stuff from scratch that entirely replaces products that previously would’ve required human input. 

Collaboration: Humans are paired with an AI tool to vastly improve and speed up their workflows.

As always in the technology sector, new innovations enforce a power law dynamic where power becomes concentrated in the hands of the elite. Top performers will no longer require support staff, as they can use AI for the easy stuff. For example, Github CoPilot is an AI tool that allows software engineers to have an AI write rote code for them. It’s nothing fancy or complex, but it allows an engineer to focus on writing differentiated code and not have to worry about monotonous work. This is good for individuals but bad for the community in aggregate. When a 10x engineer suddenly becomes a 100x engineer, you need fewer employees.

This cycle has always occurred with technology, but AI is different in how broadly applicable it is. AI reduces the cost of any good with a digital component. If this plays out the way I’m thinking it will, society will be remade in a way not seen since the invention of the silicon chip—and it will happen in the span of 10 years, not 80.

What if the medium isn’t the message?

Using the internet to distribute content instantly at zero cost altered every aspect of society. The initially scaled use cases happened in obvious categories. Software over the cloud, for instance, was predictable (and predicted by my peers of the day!). However, distribution costs being at zero had a greater impact on society than some niche technology categories.

The internet has altered how we coordinate physical labor, from peer-to-peer connections to marketplaces. Media companies’ geographic arbitrage—such as your local newspaper—evaporated. Politicians realized that Twitter points were more valuable than policy. There are now thousands of people earning six figures selling pictures of their feet. This shift occurred because once you build a digital good or coordination mechanism, you can essentially scale it for forever, for free, with only acquisition costs to worry about. 

Similarly, when AI automates content creation costs to zero, the effects will be far-reaching. More and more power will accrue in those companies that have novel acquisition methods that do no rely on any gatekeeper. In previous editions of this column, I’ve argued that “addiction will be the blood sacrifice required of consumers for businesses to win.” These tools will only exacerbate that dynamic.

I’ll also be watching to see how AI affects product design itself. Arguably, the winning products will be those that feed the best data into their AI models. This dynamic will reward the products that can be redesigned to have better training inputs. TikTok is the perfect example. Every single aspect of the app—the buttons available, the swiping motion, even the length of the content—is designed to better inform its recommendation algorithm (some people may include this algo in the AI bucket). 

In 1964, communication theorist Marshall McLuhan famously quipped that “the medium is the message.” I’m starting to wonder if this is outdated. If the algorithm is determining what medium is successful, who owns responsibility for the message?

The biggest impact of AI is that it will fundamentally change our relationship with content itself. What is real, what is fake, what is made just for us—distinguishing between them will be murkier than before. We haven’t even covered the ethics behind these tools. The disruption potential at both an individual and a societal level is beyond any other invention of the past. And these changes aren’t happening in some hypothetical, far-off future—they are happening right now. Buckle up.

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I’m giving a presentation on this idea at Every’s conference Thesis, happening this Saturday. I'll be there all day to answer questions and chat. You can purchase tickets at the link below.