Comment by scosman
1 month ago
Great essay. This is 100% right about the technical side, but I think it misses the “product” aspect.
Building a quality product (AI or otherwise), involves design and data at all levels: UX, on-boarding, marketing, etc. The companies learning important verticals and getting in the door with customers will have a pretty huge advantage as models get better. Both in terms of install base, and knowing what customers need. Really great products don’t simply do what a customer asks, but are built by taking to a ton of customers over and over, and solving their problems better than any one of them can articulate.
It’s true we will need less and less custom software for problems. But it isn’t realistic to say the software wrapper effort is going to zero when models improve.
Plus: a lot of software effort is needed for getting the data AI needs. This is going to be a huge area - think Google maps with satellites, camera cars, network effect products (ratings), data collection (maps, traffic), etc.
This all sounds very similar to the hundreds of excel/spreadsheet "killers" out there.
But excel math is easy to outperform, ChatGPT etc wont be.
Sure. But it also sounds very similar to every successful database-backed company where each tenant has < 1m rows (almost all of them).