I have never heard the phrase "belt-and-suspenders" before last week but Opus 4.7 finds an opportunity to use it multiple times per day.

Another AI pattern I'm really digging lately is managing my home server with Cursor + ansible. I run a few dozen docker containers and I've always managed the server with SSH, vim, and docker CLI. I don't want an AI agent mucking around on the machine and uploading who-knows-what as context to foreign servers.

But for recent containers I have started a repo locally on my Mac where I have Claude or Composer write ansible scripts to deploy compose files and start the services. This feels like the best of both worlds to me: AI can blast out changes much faster than I can, but it doesn't have any access to the actual server and I can easily see exactly what it's going to do before I execute the playbook myself. This has allowed me to layer on additional functionality like creating a zfs dataset and ACL for every container which was too much work to do manually.

I spent some time over the weekend setting up a hermes AI agent on my old gaming PC. It took a lot of fiddling but I finally have some models running locally on it that make it feel like a slower slightly stupider version of claude. It feels so good to finally have a fully local stack.

There are a lot of boring chores in my life that I want AI to do and that it's probably capable of, but up until now I have refused to share much personal information with any of the big companies. I'm hoping that I can build up trust with a local agent and gradually make it more useful over time. I gave it an email address and already have it submitting some receipts for reimbursement (after approval by me) which feels like a good start.

Instead of waiting for an app developer to fix the bug I reported I just one-shotted a replacement app with Opus. Achievement unlocked?

Every couple months I do a race where I have some agents go off and build a feature or fix a bug while I do it myself in Cursor. The time I spend reviewing and fixing the agent's work always end up being longer and more painful, which is I haven't switched over to an "agent command-center" style of software dev.

I do kick off worktree agents here and there throughout the day to make minor changes that come up while I'm working on a larger branch. But those are side quests while I work on the main thing.

Cursor's Composer 2 model is performing much worse for me than Composer 1 :( I feel like Composer 1 really hit a sweet spot for me between speed and quality.

For me the bottlenecks for coding with AI are:
- understanding all the code that the model wrote
- testing changes

Composer 1 really helped with the first because it could blast out small amounts of code that I could quickly review without my brain getting bored and context switching to something else. I feel like I'm an outlier in that I'm trying to stay heavily involved in the dev flow rather than having a multiple agents work on long tasks and then coming back in cold to review their work. Is anyone else using smaller quicker models in this way?