Longer-form posts about whatever I'm exploring.
I had a bike commute where I happened to join the 2026 May 3rd 5 borough bike tour1. I was curious how much overlap I had. The below is an overlay output from a vibe coded ChatGPT session, extracting the overlay data using gpx from my strava data and gpx from the bike tour that looks like is here2. So in my mind it felt like 5 miles. And looks like it was about 5.92 miles.
Recently, myself and the rest of NYC went through a cold spell and news outlets reported2 the 13 day stretch of sub-zero weather, ending Feb 6th, was not longer than a 16 stretch in 1881. And this was shorter than a 1963 stretch, but tying a 2018-01-13 streak. But this recent winter sure felt extreme. I know there is a recency bias, but I figured, why not also compare the area under the curve too. So I ranked the coldest 14-day stretches, using available data of the past decade. And then tried to visualize the spans of the coldest years too.
Email forwarding mystery solved Feeling several facepalms now that my michal@piekarczyk.xyz email finally forwards to my hey.com email inbox. After several sessions of tweaking, the answer was low tech! Registrar forwarding Originally, I setup mail forwarding on my domain registrar. Only $5 a year, okay why not. After proving to my registrar I owned my hey email, I was all set, but tests yielded silence. I spent several chat sessions with a support engineer at my registrar. He pointed out I was missing SPF and DKIM records for my custom domain and so he added those. Those have nothing to do with delivering mail to my address and only help to authenticate mail sent from my domain, but I figured what the heck let’s try something. That did not work.
Life’s a garden, can you dig it? That is what a colleague of mine had said very often when we worked together, about how you need to put time and effort into stuff. You know, get your hands dirty ! Picking up my shovel Today I finally took a first step to trying out this digital gardening concept on Maggie Appleton’s blog0. I came across back on haha I don’t know why but on 2025-07-04 , I guess it was a kind of independence day in my brain, from the march of chronology.
Came back from a flight from New Delhi , Monday morning, that left New Delhi just after midnight and 16 hours later arriving in New York around 5:30 am. And so far today, Thursday morning, I feel kind of fine, not really jet lagged, in the sense of wanting to wake or sleep at odd hours. The specific strategy I did in attempting to align meal time and sleep time with the destination time zone was to fast the day of the flight until lunch time arrival at my destination. It would have been ideal if I was able to sleep during the red eye though not doing so was also perhaps fine since by the time I crashed on Monday at around 19:00, I had about 16 + 16 + 12 = 44 hours of sleep pressure in the tank. And then when I slept for basically 12 hours, waking at 7 am on Tuesday, and getting the morning sun, I was basically back in my rhythm. And so far, sleep on Tuesday night and Wednesday night was pretty okay.
Fleeting notes and thoughts that might take shape later.
I had a coworker who left our team less than a year in because we would not cut down our development loops. By development loop, here I mean, if you want to write some new feature in a code base, can you test it locally, deploy it somewhere, test it closer to its real running conditions, and then make it live. But you typically need to do this many times, REPL style, because typically cannot predict statically if some patch has the intended outcome. So that’s why it’s a loop. This is also the itch of the Continuous Delivery [1] author, Jez Humble. I recall when my coworker was there, most of our code base was scattered across code islands, water gapped, through ship captains who could island hop you from one island to another. Testing was often impossible because of various databricks dependencies. Deploying to staging was sludgy, you know, slow and kludgy; you had to know about undocumented steps. Jiggle the keys in your ignition to start your car just right without shearing them off, after hearing your starter struggle-rattling. She’s still seaworthy, after a few attempts, you hear the car starts. My coworker’s frustration came to a head when he started his first and possibly last support rotation. When things failed and he found much of the team was perfectly fine with the inadequate pace to Jez-Humble a patch to a bug through to production, that led him to discuss this with the team. He had a few good approaches to help get some of our systems to be more, turnkey. But there was too much resistance to change and he left. Maybe I am more masochistic when it comes to tolerating slow and painful change.
I don’t know what this is about yet, but that’s the point. I’m reading in [1] Rose Horowitch “The Age of Reading is Over”, a sentiment I have encountered also through Sam Harris too, but it is a good reminder to see it again. She writes that writing is the space where you realize what you actually think. She also says it is how you share this with others. This kind of also reminds me of Daniel Dennett’s thought pump but also of Socrates’s method, which elevate thoughts into reasoning. But coming back to the beginning of this idea, it’s almost like you are the first person you are trying to convince. And how is it that you don’t know what you think until you write it? Do you literally not know yet how to put it into words or are you improvising on the spot? And maybe the answer to that is in the realm of philosophy or psychology, but I think until you linearize your thought, either by speech or pen, you are only deluding yourself if you think you really know. This is very much like the Feynman line,
I’m sure recommendations from a coding harness will vary in quality with the parameters of the model and the context available, but if these are not quite right, there will likely always be some room for error. Several interesting issues today with my semantic notes search project. I was using opencode with GPT 5.5 Fast recently and I ended up with pod memory monitoring that was not taking advantage of kubernetes capabilities and a parallelism split that did not align with my cluster node cardinality.
an interlude to having better grasp of an unwieldly photo situation
This project is a reboot of an earlier project predicting bicycle ride share riders destinations.
This is a simple personal time tracker built with clojure, aws lambda and dynamodb, inspired by Laura Vanderkam’s “168 Hours” book
