Limiting OpenAI’s token usage isn’t merely desirable because it is cheaper and faster, but also because it increases the size of the overall context. OpenAI caps this at 8.000 tokens for most models with a possibility of up to 32.000 tokens (if you are lucky to get invited, presumably). I haven’t seen anybody offering 32K tokens computations nor showcasing it. So in the meantime optimizing the token usage makes even more sense.

While I was building aihelperbot.com I did what I imagine many developers do: I used an ORM for everything database related. I used ORM to handle migrations, define schemas, insert data, update data, select data, etc. I didn’t think much about it.

It was only later while building aihelperbot.com I started to wonder if I really needed an ORM? Using AI more and more I started to realize that I could do most of the things I did with an ORM directly with SQL. And that I often could do it quicker because I didn’t have to lookup ORM specific syntax. I could just write SQL queries directly.