Copasetic Flow

 I've seen a few posts in the last week that talk about engineer's loosing their time to think because they're too busy watching what their LLM agents are doing. Anthropic's models, even under GasTown, have decide to spontaneously fork and find other ways to farm work out to subagents, occasionally causing agent storms on my project in the last week, so I can sympathize a bit more now that I did at the start of the week. There are a few solutions I'd like to propose for this issue. Here goes. How to Get Your Thinking Time Back First, if you're agents are doing marginally what you want, this is pretty simple. Stand up, back away from your desk, and leave . If it makes you feel better, setup a notification so the agent messages you when it's done. Perhaps, something like this If you don't trust your agents for the moment, still don't watch them. Come up with metrics to know if they worked or not and control your agents or modify their activities AUTOM...

 I'm still tracking down what makes some agents find a Nikola Tesla research finding and why others do not. Today, that's led me into investigating Claude CLI's forking harness. A few notes from me. Forking looks pretty spectacular! The agent kicks off a subagent that automatically has a copy of the parent's context. The subagent doesn't add to the parent's context until it's done. So, it seems to make things cheaper, at least for my passenger manifest research. The agent that used forking made the Tesla association. The other two agents with the same inputs and the same model did not use forking and did not find the Tesla assocation. This is important. It seems that agents that don't fork lack the persistence to look for more than one "really good" finding. They make that one good finding, and then kind of take any results for the rest of the passengs as good enough. Each forked subagent is looking for its own "really good" finding ...

 More instances of variance in research results, this time around Isidore Nobel. Also, saving tokens by keeping conversations short. Missing Isidore Nobel This was probably due to a misspelling on the British manifest of Nobel's last name as Noble. The U.S. manifest has it as Nobel.  Another midweek usage reset I would say this was caused by the introduction of fable yesterday, but my usage numbers didn't reset until late last night. Yesterday, my limits were at about 21% and set to renew on Saturday. What do ticket number clusters reveal in the sorta solved Hedy Lamarr mystery? First, an update. Hedy Lamarr aka Hildegard Mandl is present on the English version of the manifest. You might remember she is not present on the United States side. No answers yet as to why. However, the English manifest has ticket numbers and people traveling together seem to have similar ticket numbers, so this is a reminder to look for something there. Why we sometimes want substrate-mediated pro...

I started my lab book entries when I was a physics graduate student. It's kind of amusing and kind of cool how far I've come. I have the equivalent of a grad student, (aka Claude Opus 4.7), working for me now. I spent some time over the weekend setting up an OCR framework for a book research project of mine. I've been coming up to speed on evals, so I decided to run one to determine which model was the most accurate and cost effective for doing OCR on travel manifest pages. I stepped the eval along rather than automating it and talked the results through with Opus as I went.  First, it turns out that Opus at low effort is the most accurate and the most cost effective choice! That was a surprise. The result has to do with Opus' ability to look at higher res images which means it needs to think less for OCR vs. Sonnet. Second, at the end of the eval, as I was preparing to write up my results it occurred to me that I could ask my grad student to do it instead. Here's...

 Image quality compare from Simon Willison and Claude! One of the many aspects of Simon Willison's blog that I've enjoyed is the set of posts about coding tools with LLMs (AIs.) The latest one was handier than most for me. It takes an image and downsizes more and more, presenting the different version on a web page so you can judge which one will work best for your website's view while cutting down on the amount of data your web site serves for that image. So, here's the faster version of this blog's occasional header Chosen from a variety of options: You might wonder if I went meta on this and used the tool to reduce the size of the screenshot of the tool, and I aboslutely did!  Cool stuff!