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​Podcast, YouTube, Blog​

Dear founder,

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We live in a world where new technology is booming, and those booms are heard loudly, like the AI explosion on everyone's mind lately – developers, entrepreneurs, and more. It's hard not to want to join the AI movement. Many of us worry that if we don't start using AI or building AI businesses, it will leave us behind.

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I want to discuss the straight-line bias, this fear of things slipping away from us and not being able to keep up. “If this tech keeps developing as fast as it does right now, will I ever be able to catch up?” is a question on my mind and the minds of many founders I’ve been talking to recently.

Over the past few weeks, I've realized that as tech enthusiasts, we're at the heart of every new development. When something new comes out, we know about it right away. We follow the right people on Twitter and see any new development within minutes.

This often creates a sense of urgency. When we encounter something new that we don't understand, we dive in. But information about new things can be scarce and incomplete. It's hard to fully grasp what's happening and where it might be going — these new developments point to an unwritten future that even the experts that make it happen can’t foresee.

But we can dream.

We tend to have high expectations for technology, which can sometimes be overblown. We expect it to keep growing and surprising us with new magical features forever, and we forget that most tech eventually matures at a slower rate. This slower pace allows mainstream users to catch up and integrate it into their lives without feeling overwhelmed.

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So why do entrepreneurs and founders experience such strong FOMO with AI? — a fear that often leads to over-investing in choices involving this new technology?

AI is a recent technology that has become very popular, and it feels like if we don’t jump on it, we might lose out to everyone else. I’m trying to think of other recent technologies with a similar impact, like no-code platforms or building a multimedia personal brand. These things make us feel like if we don’t do the same as others, we’ll be left behind. However, over time, the novel developments in these fields slow down and become more research-driven and stable.

Take online payments as an example. In the beginning, there were many experimental providers for online credit card payments and things like invoicing or billing. But over time, this has consolidated into something much more stable. Payments now rely on bigger players, and developments in this field are less frequent.

If you were one of Stripe’s first customers when they were called /dev/payments, you might have had a harder time integrating their services because their early APIs changed a lot. Now, it’s much more mature.

I believe that in the world of AI, we are at a point where everything is still new and constantly changing. So, let’s discuss some things related to AI that might keep accelerating or slowing down.

One big aspect of AI I’ve been experiencing lately is the capacity to own the technology. We will likely continue to see big language models like GPT-5 or whatever Anthropic comes up with in the future being deployed on massive machines. For example, NVIDIA recently announced the B200 which costs between $30,000 and $40,000. The cost of a single B200 graphics card, or GPU, is so high that it’s comparable to buying a car or truck. It’s quite mind-blowing. These powerful graphics cards allow us to run very advanced language models in the cloud. But at the same time, more and more people are using large language models on affordable consumer hardware in local settings.

If you visit the huggingface.co website and see which models are being released, you’ll find that hundreds of language models are updated every day. They become more specific and improved, and you can download and run them on consumer hardware. While they might not be as capable as GPT-4 or GPT-5 or other models like Claude from Anthropic, they don’t need to be. Local AI is often good enough.

Big models rely on complex infrastructure. When you use an API for a large language model like GPT or chat GPT, the platform handles multiple calls to its backend systems to provide the best possible answer. Running it locally is different; it’s more like a server-client setup. But that’s okay because we can achieve about 80% of the capacity on our own hardware.

I believe we’ll see AI moving to edge computing devices like our phones, laptops, and personal servers. By default, these devices will be able to run AI systems. Currently, many AI tools rely on APIs provided by bigger companies, but we’ll see a shift towards local AI – owned AI rather than rented AI.

Owned AI may not be as up-to-date as rented AI, but it’s personal, private, and more secure because we can run it on our own systems without sharing data with others or having our input used as training data for future versions of the AI. When you use a public API, your data becomes training material for new and improved versions of the software.

So what I see as an interesting development in this space is that AI will move closer to us, just like devices have. In the past, we’ve seen a trend where technology moves closer to us. First, we had room-sized computers, then desktops, laptops, mobile phones, tablets, and now wearable devices. AI is following this same path. Currently, AI is in someone else’s data center, but soon it could be in our own or even on our personal devices. Apple is already working on local AI systems for the iPhone.

As AI continues to advance, we’ll see another interesting consolidation: human-AI interaction. Right now, AI is often used as a tool. For example, we might ask an AI to help write an article by suggesting a title or drafting paragraphs. Many people are using AI as part of the creative process rather than just for input-output tasks.

Eventually, there will be a balance between backend AI systems and those that interact with humans. Some tools will simply process data and produce results, like OpenAI Sora, which can generate videos from scripts. However, I believe many people will have an AI co-writer or research assistant to collaborate with in real time. The magic here isn’t just in the video creation: even writing the script in the first place will be heavily AI-assisted.

Anyone working on complex things will, by default, have an AI companion.

Researchers and developers will benefit from having an AI partner to help with decision-making and data analysis. As a software developer myself, I work with an AI co-developer daily. The AI systems in place for PodScan know more about the software than I do and are highly capable of building features and integrations. I can do so much more with my AI companion in less time than if I did it alone.

And to many of us, that is a big threat.

Lately, there’s been talk about AI taking over our jobs, especially with AI companions like Devin. But I don’t believe AI will replace us. Instead, it’ll become more like a companion that helps us in our work.

AI will be connected to us and our devices, involved in every professional process. It’ll be more than just a tool; it’ll be a companion with both tool and reasoning abilities.

In my own business, I use AI a lot, but I don’t sell AI services. My company, Podscan, monitors podcasts for brand mentions. While AI makes this possible, I still sell notifications about people discussing brands. AI facilitates human connection.

And it always should.

AI is becoming the norm in many industries, like customer service. Often, the first interaction between customers and businesses is an AI system that filters or sorts complaints. This is a moderating task that determines whether communication with a human is necessary or if an automated reply will suffice.

Because it’s easy and practical, AI will continue to be integrated into our daily lives and work processes as a helpful companion rather than a replacement for human workers.

AI has become the new baseline, acting as a first point of contact and a judge of relevance for human communication. It’s essential to understand that AI works best as an addition to a service, like customer service, and not a full replacement.

The goal of customer service isn’t just solving problems; it’s also about building relationships with customers and your brand. Relying solely on AI-based communication might hinder that potential. By focusing on human interaction, you can stand out in a world dominated by AI-centric systems.

Think about robotics and delivery services. While it’s exciting to imagine drone deliveries, there’s still value in having a person hand you a package or picking it up yourself. The human element shouldn’t be lost in the pursuit of automation.

AI is a great tool for process automation, but it should never completely replace human connection. You don’t have to keep up with every AI trend to succeed. In fact, you can stand out by not doing so. Focus on being present and giving time to the people you interact with, making AI a side dish rather than the main course.

For independent businesses and entrepreneurs not selling AI tools, it’s crucial not to make AI the primary focus. By consciously using AI as an additional tool and emphasizing your real presence and commitment to serving people, there’s no need to fear falling behind in technology development.

As AI becomes part of the mainstream, its volatility will slow down, and it becomes an expectation, allowing you to stand out meaningfully by prioritizing genuine human connections.

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I'll share a few updates about my SaaS on the pod, and I'd love to know what you think about them! Please leave a voice message at podline.fm/arvid 🥰

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And if you want to track your brand mentions on podcasts, check out podscan.fm!

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