AI isn't a stable building block
If you spend all of five seconds in the tech world right now, you know everyone is talking about AI. AI has been around for decades in various forms, but the specific innovation taking the world by storm is generative AI. It seems to be single-handedly keeping the tech sector afloat, as many software companies both small and large had been struggling of late. With layoffs and lack of funding becoming the norm, just saying you are building with AI could be your saving grace. Everyone is trying to get a piece of the pie though. It’s basically the wild west, and boy are things evolving rapidly. Many of the big players in the space can kill a bunch of startups with a swipe of their hand by just building a single feature (looking at you OpenAI custom GPTs).
From an engineering perspective, it’s almost impossible to keep up. You cannot build anything before the next thing comes in and makes it obsolete. You end up on version 5 of the same feature, just because there is a new pattern that generates better results, or a new LLM (large language model) comes out that is cheaper. There’s Gemma, Llama, Mistral, GPT (OpenAI), Grok, and that’s just what I can name from the top of my head as of today (there are countless others). And each of those has numerous versions of their models with different numbers of parameters, different training data, and different algorithms. Also, that doesn’t count all of the other generative AIs for other media types like images (DALL-E, Midjourney, etc.), video (Sora, VideoPoet, etc.), voice (ElevenLabs, Resemble, etc.) and others. The possibilities are endless, which is really cool (and also terrifying, but that’s a different blog post). The real question becomes, which of these will be around tomorrow? Which ones will be ceremoniously killed by one of the big companies deciding to build a single feature that does everything their startup does?