This diagram tries to illustrate the how modern AI, Claude AI in particular, compares to traditional computing paradigm. Models more or less are processors, Agents are more or less the operating system and Applications are more or less Skills. It’s interesting, but I’m wary about agents because they open up too many pandora boxes.
I made two important changes this morning for my automation-related operating environment:
My first bad experience: the code generated by Claude Code made my dashboard unresponsive in my browser. Eventually, the data stopped updating. After a ten-minute debugging session, I asked Claude Code to revert the change, and it did so promptly. But then I started getting execution failure notices on Discord. A lot of notifications. Then I started investigating…
It appears the browser was making frequent refresh requests to one of my workflows, which depleted my Claude pay-per-use credits. Bummber. Looking at my n8n dashboard, I saw that one of my workflows was failing because of that. Logs were confirming the problem with the interaction with Claude AI. As shown on the graphs below, my instance CPU usage went through the roof. Ouch. Now I know what happened, and the problem was fixed. Now, I should find a way to rate-limit this type of behaviour. That’s for tomorrow, I guess. 😅
I’m making good progress on my personal dashboard idea. While people may criticize LLMs and enjoy coding for fun, for me, it opens up possibilities I couldn’t have imagined before.
One of the frustrating aspects of LLMs is their lack of consistency unless you develop specific skills, which can take time to implement effectively. For example, I wanted to generate documentation for my most recent n8n automation workflow, but Claude was unable to do it, and I can’t remember the prompt that finally made it possible. I should have saved it somewhere for easy retrieval. I’m wasting precious credits. 🤦🏻♂️
Simon Willison on AI-assisted programming:
The more time I spend on AI-assisted programming the less afraid I am for my job, because it turns out building software - especially at the rate it’s now possible to build - still requires enormous skill, experience and depth of understanding.
In today’s world, with LLM, Claude Code, etc., is Apple’s Swift Playground still relevant, even for younger aspiring coders? A few years ago, it seems we were hearing much more about it than today.
I’m building a Dashboard. 😎
Apparently, people are barely using Stack Overflow to ask questions, thanks to LLMs and AI. I expect a similar trend among people in a community like this one on Micro.blog. Some questions would be super easy to answer by asking ChatGPT or the like. I do understand that many people still want this human touch, though.
Something is about to happen. Again. 🤗🫣
