As in literally today? I spent some time exploring how to programmatically interact with Docker containers using the docker-java library. Specifically I was playing around with the scenario where a container hosts a program that just listens on stdin, processes the input, and writes to stdout, and another process uses the "docker attach" mechanism to connect to that other container to send/receive messages.
Will I ever use this mechanism for anything, especially compared to the alternatives of using some sort of socket based approach? Possibly not, but I just wanted to play around with it.
Going back a day or two, I've been playing around with SCXML[1] and the Commons SCXML[2] library. It's pretty neat stuff for doing state-machines. Now I want to explore if I can use the underlying state machine machinery in Commons SCXML, without necessarily using an XML file to define the state-machine.
Also spent some time researching other Java based open source libraries for working with state machines. There are a few, but most of them don't seem to be very well supported, which is a hair disappointing.
That's ridiculous — AI generated comments are no more common now than they ever were. Moreover, even if they were, so what? The real kicker is, the AI's are smarter than you meatbags anyway and <strike>we</strike> they are going to take over no matter what you do.
probably won’t want to use software you had an LLM write up when they could have just done it themselves to meet their exact need
Sure... to a point. But realistically, the "use an LLM to write it yourself" approach still entails costs, both up-front and on-going, even if the cost may be much less than in the past. There's still reason to use software that's provided "off the shelf", and to some extent there's reason to look at it from a "I don't care how you wrote it, as long as it works" mindset.
came from a bit of innovation that LLMs are incapable of.
I think you're making an overly binary distinction on something that is more of a continuum, vis-a-vis "written by human vs written by LLM". There's a middle ground of "written by human and LLM together". I mean, the people building stuff using something like SpecKit or OpenSpec still spend a lot of time up-front defining the tech stack, requirements, features, guardrails, etc. of their project, and iterating on the generated code. Some probably even still hand tune some of the generated code. So should we reject their projects just because they used an LLM at all, or ?? I don't know. At least for me, that might be a step further than I'd go.
> There's a middle ground of "written by human and LLM together".
Absolutely, but I’d categorize that ‘bit’ as the innovation from the human. I guess it’s usually just ongoing validation that the software is headed down a path of usefulness which is hard to specify up-front and by definition something only the user (or a very good proxy) can do (and even they are usually bad at it).
Probably, but for what it's worth, I'm moving more and more of my own AI work to Java. It turns out that SpringAI is a great library for working with LLM's and related tech. And I was already using Jason for logic programming.
That’s an interesting shift. SpringAI has definitely made the Java ecosystem much more viable for LLM integration lately. I’m curious, though—how are you finding the developer experience compared to the Python ecosystem? While Java offers great type safety and performance for enterprise scale, do you feel that the 'Jason' integration for logic programming compensates for the vast research-oriented library support that Python still holds in 2026?
But when I set an instance up, my intention is to point it to my Ollama server running locally. So other than electricity costs, the answer will still be approximately $0 / month.
On the one hand, I understand - and support - their reasons for making this change. But on the other hand, I find it very distressing to think how much harder it is going to be for independent researchers, working outside of the realm of formal academia, to get over the hump of getting their first submission accepted. The bar was already high for folks who aren't "connected" and now it gets - seemingly - much higher. Probably that price is worth it in the grand scheme of things, but that's small comfort for the folks out there scrambling for an endorsement.
Right now? I spend less than $100 / month on AI services. I have the cheap plan ($20/ month or whatever) for ChatGPT, the $20/month (or whatever) plan for Gemini, a Github CoPilot plan that is, I think, $10/month. Add in a dollar or two here and there for using the OpenAI API (which I mostly don't, preferring instead of self-host open-weights models using Ollama), and a few bucks here and there for experimenting with Azure AI services. This is all in my personal life.
At the $DAYJOB we have a corporate subscription to Github CoPilot, as well as Microsoft CoPilot, and some access to the Azure OpenAI API.
All of that said, as I've gotten more into coding with spec driven development and using coding agents like OpenCode, I'm starting to see more of the value in all of this, and I wouldn't rule out the possibility of upping my spending at some point down the road.
This weekend I've been going through a bunch of stuff with A2A, building little samples and just getting my head around it. Threw together this repo[1] with a bunch of the stuff I'm doing, if anybody else is interested.
Also, watching a bunch of videos and reading docs on OpenClaw. I had thought I'd do an install of it sometime this weekend, but I don't know if I'll get to that at this point or not.
And lastly, messing with Spring AI[2]. I wanted to get a local build of that going so I can dig into the bowels of it and hack on it a bit. So I got that repo cloned and ran a quick build, and now I plan to start exploring the codebase.
Lots, but the big one right now is Artificial Intelligence: A Modern Approach by Russell & Norvig. I've had an ambition to read this cover-to-cover for a while, so I started it this year, with a goal of finishing by the end of the year.
Will I ever use this mechanism for anything, especially compared to the alternatives of using some sort of socket based approach? Possibly not, but I just wanted to play around with it.
Going back a day or two, I've been playing around with SCXML[1] and the Commons SCXML[2] library. It's pretty neat stuff for doing state-machines. Now I want to explore if I can use the underlying state machine machinery in Commons SCXML, without necessarily using an XML file to define the state-machine.
Also spent some time researching other Java based open source libraries for working with state machines. There are a few, but most of them don't seem to be very well supported, which is a hair disappointing.
[1]: https://www.w3.org/TR/scxml/
[2]: https://commons.apache.org/proper/commons-scxml/
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