Dear founder,
I saw something on LinkedIn the other day that stopped me mid-scroll. It was a post—clearly AI-generated, you could tell from the cadence, the slightly off phrasing, the generic inspirational tone—and underneath it were dozens of comments. Enthusiastic comments. Supportive comments.
And every single one of them was also AI-generated.
Bots responding to bots. A whole conversation happening, and not a single human being was involved. But every part of that exchange was designed to look like it came from a real person.
I found this both tragic and hilarious at the same time.
Tragic, because deep inside of me is this wish for interactions to be genuine and authentic. And hilarious, because having lived through the development of automated systems—and having participated in using these systems myself to get what I needed—I realize we're kind of responsible for this.
This is what people call the dead internet theory. And I think it's worth talking about, because we as software founders and entrepreneurs are quite likely to use AI tools to build our businesses. The output of these tools is often AI-generated content and AI-generated data. So in some way, at the very least, we might be contributing to a network that's increasingly filled by AI systems talking to other AI systems.
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Now, the dead internet theory isn't about the useful kind of machine-to-machine communication. APIs, remote procedure calls, systems that are supposed to interface with other systems to fetch data, push data, and create actions for us—that's fine. That's what machines are built to do.
What we're seeing now is something different. It's machines creating content that pretends to be human, being engaged with by other machines that also pretend to be human. LinkedIn is the worst for this, and Twitter isn't far behind. Whole conversations are happening where not a single authentic human thought is present, but everything is carefully crafted to look like one is.
So let's talk about the potential risks here. What happens when founders contribute to an internet where only machines communicate with each other, and humans are left out of the equation? And more importantly, how can we instead build tools that make it easier for actual human beings to connect with each other?
The first thing that comes to mind is this: if you know that your product can be used to generate slop—content that spams forums, email inboxes, and screens, content that only exists to elicit a commercial action but does nothing to facilitate human connection—maybe you should rethink how much of this you put into your application. Or at the very least, consider how much you try to prevent your users from misusing it right out of the box.
Here's an example. Take cold email generating tools. These are probably the target of a lot of scorn by people on the receiving end of cold emails. Me included. But even a tool like this can be useful. Even a cold email can be a wobbly but still valuable first step toward building a relationship with a potential customer.
The question is: how does it happen?
Does the cold email tool completely draft your email, then just send it, hoping to catch a potential customer? Or is it a first draft generator? A tool that helps you write an email template, fills in specifics for each customer, but then requires you to review it? To put your personal spin on it before anything gets sent?
Is it really that important—or that smart—to automate all of this away? Or could the tool take the first step, while leaving steps for the human to complete?
I know this might be wishful thinking. A lot of people buy these tools specifically because they automate everything away. But maybe that's the bottom of the barrel that you don't want to be part of. If you have the capacity to create AI as a guiding system instead of AI as a pure generating system, you're probably helping the internet not become a worse place.
And that, I think, is the core of the idea.
Whenever you use generative AI, use it not as the end, but as the means. Don't use it as the output. Use it as the guardrail around the transformation from input to output.
If you want to implement AI in your software business, in your tooling, find a way for it to be additive, not replacing. How can it multiply the thing that you or your customer is working on? How can it amplify without taking away the act of creative work?
This is a pretty relevant question. And personally, I've found that my use case for AI in all my products should always be in the background. It should make the data that comes into the system—that users work with in the system—more usable by human beings. But it shouldn't replace the work that human beings would do with that data.
Case in point: Podscan. Whenever Podscan pulls in a podcast episode, it tries to extract from the full transcript the main themes and topics, the main people who are talking, the main people who are talked about. And it makes all of that data available. But we don't do anything with it beyond that. We just extract it—which is where AI is best, finding meaning in data. But what to do with that meaning is still on my customers.
I don't auto-generate emails from this data to be sent somewhere. I don't think that's what this should be for. People should find that data, look at it, and then think about how to use it. Not make it part of a process that's completely automated and abstracts away every single ounce of humanity.
There are other use cases for AI that are a little bit closer to where the user is. One of my favorites in Podscan is the list similarity generation feature.
Let's say someone has a list of 20 podcasts they've identified—maybe 20 of their favorite shows, or 20 shows that cover a particular topic. Now the question is: how can we find 100 more? 200 more? How can we make this list bigger without all the manual research?
That's when AI becomes this background research agent. It can figure out what's similar between the shows already on the list. Do we have similar shows in our database? Are shows connected through the charts? What surrounds each of these podcasts?
That's a lot of data acquisition. A lot of value judgment on a broader, more general level. That's what AI is really, really helpful for.
In a way, it's a generative feature—we're generating a list of similar shows. But that list doesn't then get condensed into a newsletter, or an article for a blog with "The Top 100 Shows." That's not what my product is supposed to do. People can export the list and do that themselves if they want. But what I want AI to do is make the job of constructing the list easier—not to turn that list into a finished piece of content.
If you can use AI to augment, to guard, to gate, to guide—I feel that will make it a little more human and a little less disastrous.
So that's my short exploration of the dead internet theory. How we as founders could potentially be contributing to it. And how we might step away from this, make it less of a nuisance, less of an annoying and inauthentic thing.
The choice is ours, really. We can build tools that replace human thought and connection entirely, adding to the noise of machines talking to machines. Or we can build tools that give humans superpowers—that augment their capabilities while keeping them firmly in the driver's seat.
I know which side I want to be on. And I hope you find this at least a little bit valuable as you think about where AI fits in what you're building.
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