AI is eating the world.
People are underestimating what will happen to software as a result of AI.
Most are focused on how it'll make creating software incrementally easier, faster, cheaper. Few are discussing just how vast the universe of software becomes when this happens.
We will have 100x more software (at a... See more
Michael Mignanox.comPeople are tool-builders with an inherent drive to understand and create, which leads to the world getting better for all of us. Each new generation builds upon the discoveries of the generations before to create even more capable tools—electricity, the transistor, the computer, the internet, and soon AGI.
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"If you do average work for average pay, AI is going to be able to do it cheaper than you."
— Seth Godin
Tim Ferrissx.comOnce again: demand for a product increases when the price of its complements decreases. In general, a company’s strategic interest is going to be to get the price of their complements as low as possible. The lowest theoretically sustainable price would be the “commodity price” — the price that arises when you have a bunch of competitors offering... See more
The best startup AI Engineers I've met are all building their own agents.
I know it's a buzzword that's now a bit past the wave of peak hype (thanks @zachtratar), but I can think of no better way to immediately, viscerally, run into all the SOTA problems of Prompt Engineering, RAG, Evals, Tool use, Code generation, Long... See more
swyx @aidotEngineer NYCx.comThe classic software startup writes code to solve users' problems. If AI makes writing code more of a commodity, understanding users' problems will become the most important component of starting a startup. But it already is.
Paul Grahamx.com
Here are three observations about the economics of AI:
1. The intelligence of an AI model roughly equals the log of the resources used to train and run it. These resources are chiefly training compute, data, and inference compute. It appears that you can spend arbitrary amounts of money and get continuous and predictable gains; the scaling laws that... See more
1. The intelligence of an AI model roughly equals the log of the resources used to train and run it. These resources are chiefly training compute, data, and inference compute. It appears that you can spend arbitrary amounts of money and get continuous and predictable gains; the scaling laws that... See more
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