I have a keyboard I bought in 2020 called the Makerdiary M60 keyboard. It runs Python, and over the years I've coded in various functions. But it was somewhat buggy, and the upstream firmware was never upgraded.

I love the hardware because it's the only keyboard I've been able to find that keeps a live Bluetooth connection and lets you toggle back and forth between USB and Bluetooth instantly using only a keyboard shortcut. That means you use two computers, and switch back and forth as fast as you can type. Years ago I also added a feature that changes the backlight color based on the active connection, so you can instantly tell which computer your typing will go to. I haven't been able to find any other keyboard that's quite as nice.

Lately I've spent weeks using an LLM to update the extremely old keyboard firmware to the latest firmware of its components (e.g., Circuitpython, the BLE firmware, the boot loader) and implementing all of my dream keyboard features that I never had the gumption to spend hours implementing pre-LLM. I finally resolved years-old bugs, and I added things like layer-based backlighting (so that the individual keys with relevant functions are lit), a better battery gauge, better sleep/suspend timing, backlight calibration, better debounce, and so on.

I've also upgraded the hardware and added batteries to each of the keyboards (I have three of these, one at home, one in the office, and one for travel).

It has been a very satisfying project, finally scratching a years-old itch.

I lead development on Pindigo (https://pindigo.app), a social score-tracking and ranking app for pinball players.

Most of my time lately has gone into Flippd, its successor, which we recently soft-launched. We’ve also released a tech demo that uses custom computer-vision models to identify a pinball machine from a photo and extract the player’s score.

You can try it here: https://flippd.gg/scan

Hi, i have been working on https://myvivaldy.com, it's my clinic/business OS in healthcare industry (is this what the cool kids say nowadays?), Id say it is like SAP made just for this clinic OS. Especially since the Claude Boom at Dec 2025, I intensely improve this clinic from simple reservation/encounter services into full-fledged clinic OS. Users are mostly employees and patients. mostly report positive feedback. and since this industry is highly regulated (Hi FHiR v4), with the help of AI I can fulfill any major concern and whip up PoC. I can also experiment with features which was previously not feasible due to time/energy/skill constraint. Whatever make sense for user experience imaginable is a few prompts away now.

Love to help others if one wants to build their own business OS especially if you're in medical/healthcare industry.

We’re building Deckhand (https://getdeckhand.dev), an AI assisted, human in the loop platform for shipping and operating mobile apps.

We have built a few apps recently and what we observe is that while building the app has gotten dramatically faster with AI, everything around it still takes a surprising amount of human effort - testing, debugging, reviewing, store submissions, releases, monitoring, and keeping things running.

Deckhand is our attempt to make that entire loop faster, while keeping humans in control. Would love to hear how others are shipping and operating mobile apps.

I'm building a program that should help golf courses and golf course architects design better courses. I've been writing about it on my blog. My goal is to start a golf architecture consulting company, and help design/redesign courses that are better.

The general thesis on identifying architecturally interesting areas on the golf course: https://golfcoursewiki.substack.com/p/i-spent-the-last-month...

Identifying dynamic golf design so you get more interesting play on the same course: https://golfcoursewiki.substack.com/p/friday-pins-vs-sunday-...

Measuring the addition and removal of hazards and how it dynamically affects different skill levels, and how to measure that: https://golfcoursewiki.substack.com/p/measure-2000-times-cut...

How I created a golf dispersion pattern generator -- which I made open source -- so that it can be improved, because the golf analytic companies already have the data and almost certainly won't share it: https://golfcoursewiki.substack.com/p/how-to-bake-a-dispersi...

I've been resuming work on a Zig library for developing N64 homebrew¹. Previous milestone was getting a framebuffer onto the screen, and after achieving that I took an overly-long break.

Current goal, which I've been working on for a bit more than a week now, is to add support for controlling the RDP (the part of the N64's GPU that actually does all the rasterization), such that programs can actually draw triangles. I'd already implemented the control registers, so the current work is defining all the RDP commands, along with documenting what they do and how to use them — which means that I need to fully understand what they do and how to use them, and that's been a fun rabbit hole to explore.

I'm currently about halfway to two-thirds of the way through defining packed structs for all the RDP commands, then the plan is to build a CommandList struct with methods to build RDP command lists and validate that they make sense (make sure all the triangle/rectangle rendering commands have all their subcommands in the right order, make sure you ain't calling them without there being a framebuffer defined as the rendering target, make sure the needed synchronization commands are in place where needed, etc.). Then that should hopefully be enough for Zig64 to draw its first triangle :)

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¹: https://fsl.yellowapple.us/zig64

I’m working on Digest: https://usedigest.com

It lets you combine the things you already follow like RSS, Hacker News, Reddit, YouTube, X, newsletters, weather, stocks, etc. into one personal email delivered on your schedule.

Recently I’ve been working on AI summaries for incoming newsletters. The interesting product problem is that once you combine this many sources into an email, there is a challenge to keeping the results finite and useful.

I've been building replaypics.com. After an event, photos are scattered amongst phones and whatsapp. Difficult to search and retrieve. Creating memories on Google Photos requires some amount of effort. Started working on it after a family vacation - we had more than 400 photos across 4 phones and we had not looked at them after returning home

Replaypics allows a person to create an event and upload pictures, optionally invite others to upload their pictures. It selects the best and makes 4 collages and 2 videos (portrait and landscape). The videos are set to music that is selected as per the mood of the photos, cuts synced to the beats.

Trying a different monetisation method: Albums are free to create, users pay only to get the share link. Curious whether people will pay at the share moment.

I'm (solo) spinning off the internal agent knowledge and observability layer used at Motion (YC W20, series C, ~40 devs). It was born out of a need to lift all devs using heterogeneous models, harnesses, and prompting styles to a higher level of consistency and quality while surfacing the visibility to see what's working and what's not. The knowledge layer is integrated into the code review layer and all of it tied together with telemetry to the document section level to see how each piece of context is affecting code generation.

Open source repo (.NET 10 + C# + Postgres): https://github.com/zeeq-ai/zeeq-app

Docs and more info: https://zeeq.ai