Sep 2025
(Based on a Boab Ventures AI Talk)
“It hurts when you realize you aren’t as important to someone or something as you thought you were. But something is never taken away from you without being replaced with something greater. You may have to wait for it however.”
– Kate Mcgahan, Grief Councillor
“When you do physical labor, you end up being no longer useful when your physical condition deteriorates. However hard I work, however dependable I am, when my body grows old then no doubt I too will be a worn-out part, ready to be replaced, no longer of any use to the convenience store.”
– Sayaka Murata, Author of Convenience Store Woman
I had this strange experience in my software career. Back in 2012, I was a PHP programmer and what I knew was cutting edge. I had job offers at Facebook, had built apps that were the most popular in the country and I could build apps faster and better than anyone I knew. Instead of taking the job offers, I started a startup instead where I wasn’t writing a lot of code anymore. For about 5 years of not writing much code at all, by 2017, I noticed how much better everyone around me was. And it occurred to me now that I was worse at building apps than just about everyone I knew.
In 5 years of trying my hand at being a founder instead of engineering, I went from an upper quartile engineer to a lower quartile engineer. This experience has always lived in my head rent free and slightly rubbed me the wrong way because of a) how quickly the field changed and b) how fast you fall behind if you’re not constantly up to speed. A doctor or lawyer or accountant that works 1/10th of their usual hours for 5 years doesn’t suddenly become completely obsolete. But in technology, that’s exactly what happens. If you stop writing production code for really any amount of time, you just about stand still while the whole industry moves at warp speed away from you.
But then this funny thing happened where the industry came full circle. AI coding or Agentic coding or Vibe coding essentially means that nobody writes production code anymore. The engineer is now sitting above an additional abstraction layer where they design an application. But then the AI agent LLM does the actual code writing and execution of the tasks. You pick the tools you want to use but the AI is already an expert and proficient at everything.
The software engineer just outlines and plans the app and tells the LLM what code to write to build the software of the application but the AI does the work. The time input has switched from actually writing code to debugging code already written. Because the AI writes code so rapidly, often you don’t even bother debugging, it’s faster to throw it all away and run it again in a different way. You just need to understand how software applications work and be able to read code not actually write it anymore.
Because now you can code in English, what this did for people like me is it made me cutting edge again, seemingly out of knowhere. I still understand how software applications work and can design them. I just wasn’t well versed on the best practices coding and frameworks anymore or how best to use them for actually building. So I went from cutting edge to obsolete to cutting edge again.
“The hottest new programming language is English” according to Andrej Karpathy and he’s right. All you now need is to describe to an AI tool what you want and then suddenly it can build it for you in front of your eyes. But what this does for regular people is it removes the alien language of code, which is the abstraction layer that was always hard to understand and just made it all in English. So anyone can effectively become a software engineer, instantly. You can point an AI LLM at another software application and tell it just to copy that and it will, to an astonishingly high standard.
So the barrier for writing software has come down dramatically and the hurdle of expertise required to do it has all but evaporated. What that will likely do is 10X or 100X the whole software industry if everyone can create production ready software applications with a few paragraphs of English as the prompts. But at the same time destroy the market for your average software engineer since the complexity of building software is no longer the barrier.
It used to be in software that we’d design a one size fits all model where you’d just have to deal with the edge cases that didn’t work for you. But that paradigm is now over. We’re entering the paradigm where everybody will get a different piece of custom built software that fits them exactly perfectly. Almost anything anyone dreamed of is able to be created without a software engineer needed to build it, so I think we’re going to see this explosion in hyper specific applications that are designed and built just for 1 person or 1 businesses specific workflow or usage. Often they could probably build that software themselves then get rid of it when they’re done.
For great software engineers, I suspect this turbocharges them even further. It used to be a 10X discrepancy between the best engineers and the average engineer. Then a lot of frameworks exacerbated that to a 100X difference. I think with these new AI tools, that is now a 1,000X differential between the best and the average. What these AI LLMs feel like is a formula 1 racing car but for the masses. If you’re an excellent driver, the car will allow you to drive as fast as you possibly can. But if you’re an average driver, you’re almost certainly going to crash.
We can now do a lot more with a lot less but the question on a society level will be does the job growth of the industry writ large outpace the job losses from the people getting replaced by AI. I think the answer to that is yes because of a phenomena described in this essay as Jevon’s Paradox. As the cost of something goes down the demand for it goes up resulting in more jobs from all that growth rather than less jobs from the cost of creating that thing going down.
As harvesters made farming more efficient and more food could be produced per farm. The demand for food went up and therefore more farms were needed to meet that demand. As each farm required less farmers to operate, lots of farmer jobs were lost but the overall number of farmer jobs actually went up eventually as there were a lot more farms being created to meet the demand for more food production. So a technology that made farmers jobs reduntant counterintuitively resulted in the creation of more farmer jobs. That’s Jevon’s Paradox in action.
I think something like that is going to happen with AI too as businesses start adoping AI at scale. At first they’re going to let a lot of people go as businesses won’t need as many staff to achieve the same thing. But it will result in the overall creation of more businesses, as each new business can start and grow and do more with less. So a lot more businesses will get started. That greater number of overall businesses which was enabled by AI will go out and hire lots of people. Causing overall employment to increase eventually after decreasing at first. But in the near term everything is going to change.
In fact the whole internet seems like it’s probably going to change. Why bother searching for anything when you have a superhuman wizard that just tells you everything you want to know. That used to be Google but that’s going to become an AI tool and everyone is going to pick the one they like the most and use that. Because what AI already does so much better than search is context, feedback and elaboration. It tells me straight away the things it thinks I will want to know in addition to what I just searched for. And each has their own strengths and weaknesses.
I like Claude by Anthropic for all things research and writing but ChatGPT by OpenAI for all things design, images and tasks. I think Claude is better at text but ChatGPT is better at images. This feels like we just entered the first new technology paradigm in my lifetime. I was a kid in the 90s so I don’t remember what a world with large website directories like Yahoo that everyone visited was like. Before they could search to find what they were looking for. Then we entered the search paradigm where people would search first, then find the websites they wanted. Now we’re in the AI paradigm where we ask for what we want and then the AI tries its best to give it to us.