I think there is lock-in, despite those things - for containerization, you're still a lot of the times beholden to the particular runtime that provider prefers, and whatever weird quirks exist there. Migrating can have some surprises. K8s, usually you will go managed there, and while they provide the same functionality, AKS != EKS != GKE at all, at least in terms of managing them and how they plug into everything else. In terraform, migrating from AWS provider to GCP provider will hold a lot of surprises for you for what looks like it should be the exact same thing.

My point was, I don't think it mattered much, and it feels like an ok comparison - cloud offerings are mostly the exact same things, at least at their core, but the ecosystem around them is the moat, and how expensive it is to migrate off of them. I would not be surprised at all if frontier AI model providers go much the same way. I'm pretty much there already with how much I prefer claude code CLI, even if half the time I'm using it as a harness for OpenAI calls.

There's a tiny amount of friction. Enough that I'll be honest and say that I spend the majority of my time with one vendor's system, but compared the to the fiction of moving from one cloud to another, eg AWS to GCP, the friction between opening Claude code vs codex is basically zero. Have an active subscription and have Claude.md say "read Agents.md".

Claude Code routines sounds useful, but at the same time, under AI-codepocalypse, my guess is it would take an afternoon to have codex reimplement it using some existing freemium SaaS Cron platform, assuming I didn't want to roll my own (because of the maintenance overhead vs paying someone else to deal with that).