I have been noticing a pattern in a lot of AI products. The demos look great, but the moment you try to use them inside a real workflow they fall apart. It feels like we built an arcade of impressive tricks instead of tools that can survive real constraints. I wrote a longer piece about why this is happening and why so many AI products are stuck in demo mode. The short version is that we keep optimizing for the thing that looks good in isolation instead of the thing that works when it has to deal with state, dependencies, and long running tasks. If you build systems for a living, this will probably feel familiar.

The AI industry is completely unlike an arcade in that arcade machines weren't run at a loss while trying to lock-in users and drive all the other machines out of business. Arcade owners expected the machines they bought to start paying for themselves from the get-go.

P.S. This article felt like it was written by an AI, or just really needs to be edited for redundancy.