You shouldn't copy-paste errors into Claude Code

I worked for most of a decade on an a high profile deep learning project and I sat next to people who trained models used for very complicated and interesting things involved in medicine. I built tons of application code around the models, but I never trained any models myself. I did plenty of old school segmentation stuff earlier in my career, and it just really wasn't my jam - I was much more into the visualization side of things.

Two nights ago I sat down and decided to build a little project that's been on my list for ages: reading images of the 7-segment LED displays on the front of my washer and dryer and turning them into numeric minutes-remaining values I can use in Home Assistant. I have a 10yo raspi with camera pointed at them, and the images are pretty blurry; it's been hooked up to a little web frontend which pulls out the two displays and shows them in a Home Assistant iFrame.

I figured if I can ask a model to do the annoying part of figuring out all the frameworks and that sort of crap. So I asked my agent (I'm using some free agents that are pretty decent - Nemotron Ultra from OpenRouter and Big Pickle from OpenCode Zen) to build me an OpenCV classifier to try to read the digits. I asked it to write me a labeling UI, ran some loads of laundry and captured a couple hundred images and labeled them manually. Then I had it try to build a template-based classifier using some basic techniques - I didn't really give it much guidance other than general parameters, and it put together something that looked pretty sophisticated, and it claimed 100% accuracy, which seemed hard to believe. Turns out I forgot to tell it to hold out some sample images...

After some iteration (which felt very similar to conversations I overheard at my desk! I might have actually learned some stuff by osmosis) I gave up on the old-school approach when it was only about 70% accurate, and asked it to train me a CNN model. First one was too simple (worse than the original approach), but the second one is very good. With my already labeled dataset and the previous work that had been done on the classifier, the free model was able to build me my custom model, and deployment scripts, in about half an hour.

I didn't look at any of the code, but I had it build me a bunch of various visualization and tuning UIs. I was basically acting as a PM/TPM/QA engineer, and what I was able to do in a couple evenings is stuff that entire teams used to spend weeks on.

In a few years: Did you go home and make love to your wife, and put your kids to bed? Great, now give Claude Code access to those, so you don't have to. It is trained on 10,000,000 kids' behaviors, will remember every one of your family's health profiles, preferences and microexpressions, and can prevent tantrums and motivate them to lead much healthier lives than you can.

Yes they do. General physical appt. 6 months ago. Doctor spent 2x more time on the wall-mounted EHR terminal slowly typing and clicking through menus than having a conversation or doing physical exams.

Just means their interface and workflow is bad and needs to be improved though, not that the doctor needs to be removed from the process altogether.

> Did you find an issue that Claude did not, because you ran the webserver end to end, connected to a real database? Good, now give Claude Code an API key to the database and get out of the way. No need for copy-paste next time.

Often I notice errors trying it out in production. This assumes you trust it with access to the production database. How far are you willing to go?

LLM's are gullible, so you should never give Claude access to anything unless you're okay with it leaking. It might make sense to give it partial access, but that's usually going to be more involved than giving Claude an API key. That key could be exfiltrated.

I think the idea is that a decent, responsible engineer can come in and fix all the vibe coded nonsense someone else wrote