325: Indie Hackers' Myopic View of AI

This episode discusses the overhyped trend of AI within the indie hacker community, exploring how it impacts founders and the tools they create.

1. AI is often misperceived and misused within the indie hacker community, leading to a flood of redundant and shallow tools.
2. There's a split among founders—some overembrace AI due to its popularity, while others reject it entirely, seeking traditional business routes.
3. Effective use of AI in businesses often goes unnoticed; its true value lies not in overt features but in its backend capabilities.
4. Kahl advocates for a balanced understanding and application of AI, emphasizing its potential to support businesses beyond just being a user-facing feature.
5. Founders should focus on creating value through AI, not just using it to attract attention with flashy applications.

1: Introduction

Kahl introduces the topic of AI's inflated presence and its superficial application in the indie hacker community. Arvid Kahl: "AI has an image problem among founders."

2: AI's Impact on Founders

Discussion on how the AI trend affects founders' decisions and business models, highlighting the polarization in their responses. Arvid Kahl: "Either you're building an AI product or ignoring AI altogether."

3: The True Value of AI

Exploration of AI's potential beyond the hype, with examples of how AI supports businesses without being at the forefront. Arvid Kahl: "AI can extract meaningful data for businesses invisibly and effectively."

4: Recommendations for Founders

Advice for founders to leverage AI responsibly and effectively, focusing on its utility rather than novelty. Arvid Kahl: "Look for boring applications of AI that do the heavy lifting behind the scenes."

5: Conclusion

Summary of the discussion with a call to action for founders to rethink their approach to AI in business. Arvid Kahl: "Make AI a workhorse, not a dancing poodle."

1. Recognize the true capabilities of AI beyond the hype—focus on backend processes that enhance business operations.
2. Avoid jumping on AI trends without considering the actual needs and goals of your business.
3. Evaluate AI tools critically—assess whether they offer superficial features or genuine value.
4. Explore AI applications that improve efficiency and data analysis without necessarily being user-facing.
5. Consider AI as a tool to augment your business operations, not as the centerpiece unless absolutely necessary.

"Everyone and their mother are talking about AI. Every founder releases their 500th GPT wrapper."
"AI is all hype, no substance."

Or is it? What if our collective perspective is really skewed, and our gathering places are to blame? Here's my take on why indie hackers have a dangerously biased view on what AI businesses are and should look like.

People

Arvid Kahl

Companies

Podscan

Books

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Content Warnings:

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Arvid Kahl
AI has an image problem among founders, particularly indie hackers, and within our online communities that we as indie hackers and founders frequent. In this builder community, we are constantly inundated with shallow copies of the same kinds of tools day in, day out. There are GPT wrappers and social media, auto repliers, AI starter kits, boilerplates, AI search, AI coding tools, PDF inspection, AI, AI, AI, AI. And frankly, half of the products on the product hunt front page have AI in their name, let alone the subtitles or descriptions of these things. Like AI is everywhere, everyone is building AI tools.

And from within the indie hacker community right now, this looks like a massive gold rush where everybody is trying to pedal shovels to the ambitious miners looking for AI gold. It feels like almost a Ponzi scheme like quality of just how tools for AI founders are being built by other AI founders that are a couple months ahead, courses are being released on AI topics by people who just barely scratched the surface of their own exploration of AI. And from inside a community that is usually very protective of its members. This feels like it's a problem, so let's talk about it today. This episode is sponsored by acquire.com comma, not an AI company by the way, more on that later.

Maybe it's an overblown hype that we perceive here with this whole topic of artificial intelligence, but it feels like there's something going on. Whenever I go to Twitter, whenever I go on any social media site or even forums and news pages, AI is so prevalent it appears like an outsized interest in a niche topic. At this point, like a year ago, we talked about a lot of things, and AI may have been one of them, but now it feels like every single thing is about AI. Everybody's talking about AI all the time, me included right now. And consequentially, a lot of our software founders who are trying to build a lifestyle business and bootstrap it, which is overwhelmed by all of it.

And I don't think this can be good. This AI avalanche causes too potential reactions in founders, and they're quite polarized. Either you're one of the founders that say, well, I don't care, I'm going to build an AI product because that's what everybody is currently doing. Everybody's selling and people are buying this. This is what consumers are looking for, and that's what my peers built.

I want to be part of this wave, so I built one too. And on the other hand, on the other side of the spectrum, you'll see founders who say, let's go back to traditional software as a service businesses. Let's completely ignore this whole AI thing and let's step away from it. Kind of a signal of contrarianism to actively pursue, not AI as a response to everybody building something with AI and it being so incredibly popular. And I feel both approaches feel a bit reductive at this point.

Right? They are so polarized that they must be missing a lot in the middle. I think we're looking at all of this through a very particular bubble in our community. And that's unfortunate, because obviously there is value out there in building with AI technology, otherwise it would just be a niche thing. But it's not.

There are a lot of people who think it's a really useful thing, and it is popular beyond the indie hacker community as well. Clearly even our parents are talking about this and they have no idea what it is about. So yeah, what, what is there? Is there value in AI out there that can be meaningful for us as an entrepreneur, to inform what businesses we should build without falling prey to this hype, without buying shovels all day long? So let's start with becoming aware of our own biases.

What kind of myopic lens do we currently have as indie hackers in the community? That seems to distort how the reality of AI actually is? Why are we so upset with the hype? What are we not seeing? The first stumbling block is that we see AI as this hyper modern trend, this super current, super recent thing.

But AI didn't start with chat GPT, right? It got a lot of attention from that, clearly. And when OpenAI started to release the large language models and it was something new, we witnessed a technology breakthrough at this point, both in the capacity and the availability of AI. For founders, particularly solo founders, that is new. And for many of us, AI then is something that started somewhere in late 2022 or early 2023 with GPD three or even GPD four.

That is our first popular point of contact with AI. But obviously artificial intelligence has been a research subject for decades before this, and many technologies existed long before LLMs were ever conceptualized thinking of neural networks and machine translation and prediction systems. There was a lot of cool tech around when LLMs eventually hit the scene. It was already there. I actually used a machine translation system called Moses back in 2017, and back then it was already quite old.

If you look at the website for this thing, it looks like it's from like 2003, 2004, maybe even older. And we use this for my previous software startup, feedback panda. We were creating an automated its system to turn text written from a male perspective, using words like he did his car, they gave him those pronouns to a female perspective. She did her car, they gave her, and vice versa. That was the idea we needed to allow our customers to write one version and have the other one auto generated.

Auto created by a system. And building this system took me several months, even just figuring out machine translation. It was all quite academic at this point, and it was hard. It was hard to understand how to do these things. You needed to set up complicated systems.

I had to build, like, Docker containers around the training set, and then run these training for any given experimental version of this, just within, like, a margin of error that we were comfortable with, took over 24 hours for every single experimental version. So that explains a couple months that I worked on this. It was a lot of work. And GPD four can do this out of the box in under a second now if you prompt it right. And I think that this is both the amazing novelty of this tech and the reason we have such a skewed perspective on AI.

We forget that a lot of these technologies, the old ones plus the new ones, are silently powering a lot of businesses behind the scenes. Yet all we see when we look at the front page of product hunt or hacker news or whatever, are AI front and center. B, two c and b, two B applications. Chat with your documents, create copy within 50 milliseconds of typing whatever you want, render a video right in the browser from a prompt. All of this super flashy.

We see AI as interface, as the first point of contact between us and a service. AI is flashy. It's right there, it's in your face. And I think this causes our indie hackers myopic lens. When we think of how we should use AI within a product or as a product, we think of AI as the thing working right now in front of us to create some kind of magic, because that's what we see.

And the more tools like this are released, where AI is such an outstanding part of the software, such a visible thing, the more we consider that this is how we should be building tools in the AI space, because we then kind of extrapolate the expectations of our future customers to be this too. They want to chat with this, right? They want to have some kind of immediate click, and then there's an effect and an image pops up. That's what they want, right? Well, is it, though?

Meanwhile, there are systems out there that look like they were built in the nineties, that have powerful AI algorithms working in their backends on their databases and reporting and data analysis stores, which are surfacing. Massively impactful business information, like the stuff that people pay money for. And you can chat with none of those. No cool prompts, no on the fly image generation, nothing in their yells. Current bleeding edge AI systems powered by OpenAI or anything like this.

But everything in there is an artificial intelligence, crunching massive amounts of data to produce so much value that they can charge hundreds if not thousands of dollars per subscription per month for these kind of things. And I'm seeing this myself right now with Potscan. The actual magic of this tool is something completely invisible to my customers. It's the ability to extract data from audio that is meaningful and impactful for the businesses that are using my product. I scan every podcast out there, and I look for host names, guest names, and sponsors, advertisers.

What are the main topics? Is the tone of the episode friendly? Is it aggressive? Are people kind to each other? This is what my customers need, and AI systems can give it to them.

Because AI works reliably enough at scale, it gives the people who use Podscan for their businesses meaningful information that they couldn't get anywhere else. Because their question, their core question is not, can I chat with this tool? It is actually, is there a podcast that I want to advertise on, or is this one particular podcast one that I want to pitch my client on? This is how they make money, by getting enough information about things so they can pitch it so that their clients can get onto this podcast that fit their profile, and then they get paid. And to be able to do this job, they need to have information that is uncollectible by individual people, but can be easily collected and aggregated and extracted by completely non flashy AI systems.

And nothing in my interface suggests this. It's just a list of things, a table. It's a search bar where people can search something and then results come up. I mean, there is AI behind this, but it's not there. You don't chat with it.

It just gives you results. There's nothing different between the interface of Potscan and all the software tools of the last 20 years. Other than that, it maybe looks a little bit more modern because I use tailwind and it's a good design and all of that kind of stuff. Functionally, there is no difference there. And when it comes to how you use it, my AI is not in the interface at all, but it is powering data collection.

Twenty four seven. I have multiple dozens of servers doing nothing but data extraction. Data analysis, transcription, question answering on large text documents, that kind of stuff, storing those documents, searching these documents all in the background, no chat, completely invisible to my users. The only visibility they have are the good results that they see that were collected and maybe even generated by the AI. You know, when it comes to summaries, that kind of stuff, there is generation generative AI in there as well.

But that is not part of a process that they trigger, it just happens behind the scenes. And this has nothing to do with creating content for social media or automatically replying to posts and all these hyped up tools that we find in our social feeds. And I think our problem is that indie hackers just see the wrong tools that are getting so popularized because they're easily adopted by the likes of us and the peers around us. Like the AI tools we see are AI tools that facilitate social media exploration and audience building. Because we see these tools in the context of social media, and that is a problem because monkey see, monkey do right, we end up building similar things that miss out on this deep but invisible power of AI that actually creates massive value that people are willing to pay for, but only behind the scenes.

And we can't really see that. I mentioned this several times over the last year. AI businesses are risky. Like AI centric businesses, the riskiest businesses that are merely leveraging AI while they are less risky. Still risky, though, there's still platform dependency when you're relying on some OpenAI API or using any of their competitors, just somebody else's platform.

Still platforms, right? Local LLMs solve this kind of problem, like running a llama three or something like this locally, but that will cost you. And then the OpenAI API becomes more interesting when you're getting started, and dependency risk still kicks in. And even then, this technology changes so fast that the flashier it gets, the quicker it also loses its appeal with the people who go for flashy. So look for the boring applications of AI.

Make it a workhorse, not a dancing poodle. Don't try to get people's attention on the AI. Get people's attention on how great the results of the AI are, how impactful they are, not what magical technology you use to make them happen. And then pay attention to the founders who use this kind of technology without mentioning it at every single sentence of the sales copy. When in doubt, instead of wondering, what AI business can I build, think what boring business can I build that leverages invisible AI behind the scenes, because that's really where the value is.

And that's it for today. I will now briefly thank my sponsor, acquire.com, a marketplace where people are actually selling a lot of AI businesses at this moment, mostly because they hit some kind of ceiling or something. They found something else they want to build, which is a common problem in the AI world. And that generally is a problem for you if you're a founder, AI or not, right? If you have a SaaS product, you have customers, and you generating consistent monthly recurring revenue, you're supposed to live the dream.

But you sometimes feel like, oh, this is not for me anymore, for some reason, right? Might be because you don't know where to go, you don't want to do it anymore. Your life changed, you have kids or something happened that you want to get out of. You want to make sure that you get value out of the business, but you don't want to keep it running, the business itself. So that is when you want to look at a platform like acquire.com dot, because they will help you list this business so that other people who might not have these kind of problems and challenges that you have can find it, pay you a lot of money to get your value out of the business.

They exchange it for money, which is kind of how an acquisition works. And you find the right people to keep your business going while you finally have the opportunity to do something else, because you have financial windfall and that tends to be very, very useful. So too many times at that point when you could make this decision to sell, people become complacent and the story ends up being one of inaction or stagnation, and that kind of damages the business. It becomes less and less valuable and over time, completely worthless because you're not putting in any effort anymore and your competitors take over. So if you find yourself here at this point already, or you think you might actually be headed into this direction, consider going to acquire.com.

go to try dot acquire.com arvid and see for yourself if this is the right option for you. They have helped hundreds of founders already. It's going to be really good just to even check it out to see what your options are for the future. Thank you so much for listening to the Bootstrap founder today. You can find me on Twitter at avidkall.

A I v I d k a h l. Guess I'm supposed to say you can find me on x, but I will never. Or maybe, who knows? And you find my books on my Twitter course tattoo. If you want to support me on this show, please subscribe to my YouTube channel, get the podcast, and your player of choice and leave a rating and a review by going to ratethispodcast.com founder.

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