AI is taking the world by storm. There’s nowhere on the internet you can go without stumbling into it. They call it the revolution of our time, the greatest invention since the Industrial Revolution. Be you supporter or skeptic, it’s hard not to get swept up by the wave of enthusiasm. But is it just the next worthless fad or does it actually live up to the hype?
That has been a difficult question for me to try to answer. I’ve been sitting on this post for about 3 months trying to explain my feelings on it, but in summary, I can’t answer with a yes or no. I believe AI is currently under-utilized for its current capabilities while also being overhyped for what people want it to be able to do. I expect where AI is being under-utilized, the gap will eventually be filled in as experimentation continues, but the latter case is wishful thinking.
I think there is a real danger in AI, not because I fear a superintelligence that will wipe out humanity, but because overly ambitious hype men, like Sam Altman, will drive everyone into making sky-high promises about multiplying developer productivity tenfold, diverting trillions of dollars away from other, better investments, while only yielding a fraction of the promised results.
Most often, the AI conversation is centered around what we want AI to do and not grounded by its actual capability. AI is magic fairy dust that can be sprinkled anywhere to solve all of our problems. It is not only the silver bullet that solves all our problems in one domain, but the one that solves all problems in all domains.
A few months ago, Tebra hosted a company event focused on AI, which was my primary motivation for this post. With our teams, we sat down and listed the current problems we were facing – a useful exercise that we had not done before. However, we then had to turn around and decide how we could use AI to solve those problems. This is what brings out the magic thinking. It’s actually rather akin to AI hallucinations. The LLM knows you want an answer, but an answer does not exist. How do you satisfy the requirements to provide an answer without data to support it? You make it up. How do you solve issues with AI while having no known way of doing so? You make it up.
This doesn’t stop at the developer level though. CEOs make promises to boards and boards make promises to their investors that they will enhance productivity and company valuations in the same way and money flows to those who can make the most convincing sale. Those wanting more immediate effects will cut their workforce and demand their remaining workers increase productivity to cover the difference. 10x productivity becomes an expectation, a demand.
I have yet to even discuss the actual capabilities of AI, because I think no matter how good they get, expectations and demands will far outpace reality. As we saw with the recent release of GPT-5, modest improvement is now a failure. These companies demand more of our expensive power and more of our increasingly dwindling water supply to meet the impossible expectations of their userbase. It’s hard not to see the parallels to cryptocurrency.
Despite my scathing criticism, you may be surprised to find that I actually like AI. I read Anthropic’s paper on Claude Opus / Sonnet 4 and I’ve been using Claude Code a lot on my own projects. It’s been quite fun to experiment, but that’s because there’s no demand for maximum productivity, no expectation to fit it where it doesn’t belong. So, I often stand with the AI skeptics, not because I always agree with them, but because they’re the ones who still make me feel sane and grounded in reality.
Here’s my prediction – nothing has changed fundamentally about the business of software. Success continues to be defined by our ability to deliver value to customers by fulfilling their needs. In all but the newest companies, it has never been predicated on speed of delivery, but instead an understanding of what to deliver. Using AI to deliver more is only meaningful if it meets the needs of the customer, thus it only widens the gap between top companies and the rest, assuming it does what it claims to do. Companies who already fail to deliver value will not find AI to be the savior they wish it to be.
But if you’ve been tuning out the AI news because you see a valueless hype bubble, check again. The ground has shifted and these tools are more than chatbots now. It’s worth experimentation, even with valid skepticism.
In the end, I believe AI will not be the differentiator of success, but merely the amplifier. It will eventually settle to become another tool in the toolbox, but the core fundamentals remain the same.
Adam Lif 