Textlog for me is a meditation to slow down.
It somehow nudges me towards working on my penmanship.
Any conversation
ive been rocking my thinkpad 460s since 2018 or so, but ive just recently yolo purchased a chunky t420 for 80โฌ. I gotta say this is the best laptop ive ever used, keyboard/io is unmatched and it still runs super snappy on omarchy right now, even with only 4 gigs of ram :D AND this thing has a cd drive!
ai coding feels like it has reached diminishing returns for me. luna is my default orchestrator, routing work by complexity. in practice, usage lands around 16% luna, 48% sol, 30% astra, and 6% terra. at this point, i care less about each new frontier release. the system already finds a capable model for the job. the frontier is moving beyond my day-to-day work, so iโm happy to settle into predictable models for a while.
Judgement, taste and quality were always precious skills. In the world of , I have become more aware of the fact that it is often hard to put in words why something is good, great or amazing - or just looks good, but is average.
A lot of the professional content I see feels like most Netflix series. They have all the elements - but the overall experience is still meh.
Quality is still hard to achieve.
Really glad to be using Haskell for work - especially in today's climate with agentic coding.
Our team uses containers to keep our development environment consistent across team members, though, and most agent sandbox approaches want to either offload your work fully to the cloud or they want to sandbox the agent harness process itself.
We're not ready for full cloud based development (yet?) and sandboxing just the agent doesn't work for us when the agent needs to run docker.
I read
Still trying to figure out the boundaries of these tools' strengths without outsourcing important thinking, problem-solving, and the collective building-up of a mental model of the systems we're developing.
The shape of LLM tools as toolsโfit for a purpose, ergonomicโis becoming clearer, and human patterns of behavior with them that do more harm than good are also becoming easier to recognize.
signals. thinking about shifting my mental framework to identify signals instead of waiting for concepts to be assembled. exploring the amount of energy and opportunities for distractions through the operations of processing what just happened and what is happening to short circuit latent and unnecessary systems. cut through the assembly processes and identify the raw signals. recognizing that naming these "raw signals" is misleading. maybe, shifting observability lower in the stack.

