Your thermostat and non-standard battery are examples of LLMs being helpful.

As for the rest, that is a lot of tokens burned to keep a fridge stocked.

It doesn't burn that many tokens, as most of the code is deterministic.

Receipt emails are in a predictable format, so codex built scripts to parse the emails. If there is a receipt email it doesn't recognise, it will use an LLM to build a parser for that kind of email once.

The agent also "self improves", so after asking once to get items to restock, it wrote a skill with the query it used in, so it doesn't burn tokens figuring it out again.

I was impressed that after it logged into my supermarket account, it inspected the network traffic and discovered a GraphQL API, and used that (instead of screen scraping); much more economic.

I've averaged 2.6 cents a day in token costs over the last month.