A modern SQL client for web devs. Deeply integrated with your workflow (vscode, drizzle, supabase, etc), a nicer more schema-aware GUI (think Airtable), and smarter ways to save queries and export/share them.

A lot planned, not much built. Just started so follow along if it sounds useful! Also see my prior thoughts on the topic here: https://news.ycombinator.com/item?id=41286912

Sqratch - https://github.com/jkcorrea/sqratch

I am working on Navi, an open source digital twin that helps you review the digital notes you've taken in the past week:

https://github.com/Melvillian/navi

Checkout out the README; it gives you a straightforward idea of how Navi works. Currently only works for Notion, but the idea is to make any notetaking tool (Obsidian, Evernote, Google docs, etc...) be ingestable by Navi.

Next steps are to make an SRS plugin, and to make a HTMX-based website so it's useable beyond just the CLI.

I'm adding zsh shell completion to my CLI framework ( https://github.com/bbkane/warg/tree/bbkane/the-flattening-2-... )!

I'm writing bigger CLIs with it now and I want to tab through their subcommands and flags, as well as allow customization - suggest values for the current flag based on previous flags' values.

It's been a lot of work (9 months of quite limited side project time)- I had to rearchitect significant parts of the parsing to keep more state around, and learn how I want to approach communication with zsh, but I just need to add some tests and an option or two more and it'll be good enough for most CLIs I wrote.

Oddly enough, I'm procrastinating actually finishing it. I've really enjoyed the "grind" for this feature, and I'm also taking the time to clean up the API if I think of better versions. Being able to noodle around with no pressure (except internal) to deliver keeps the joy in programming going for me.

But, after this is done and integrated into my CLIs, I plan to take a left turn and try to add really good OTEL tracing and visualization to my CLIs- I think I can outut OTEL traces to log files and then embed logdy.dev subcommands for really nice searching and visualization.

Currently, when my brain lets me, I am working on redoing my entire home network infrastructure. My network cupboard is a mess, and I've been slowly CADing and test-printing parts for a 8.5 inch server rack system. I've managed to get some nice side rails, and I'm currently doing some test prints for a mount for a Lenovo M700 computer, which I like for lightweight server stuff (the one I have is currently running my homeassistant and a couple of other docker things, and I'm going to be buying another to use as a NAS). I'm also slowly working on rewriting my website backend to pull projects off external drives, reformat them into blog pages and automatically update my website to use them. Currently I'm still at the early testing stage, and I have quite a way to go, but the basic parts are there.

The 8.5 inch racking system was inspired by Jeff Geerling's video about 10 inch rack, but shrunk even further to allow me to fit it on my 3D printer bed (8.6 inch square). I currently have parts for the top and bottom of the rack, as well as 1U and 2U expansions that you can slot together to make the rack as tall as you want. I'm also thinking about making a side attachment system so you can clip fans onto the side or similar. Once I have a working rack with several units in it, I'll probably end up publishing the parts and a writeup about it

A JVM written in go. [0] We're committed to a high-quality implementation that works reliably--so our test code is > 2.x the size of our production code. We can already run lots of classes, but the finished product won't be ready for alpha testing until, we hope!, end of this year.

[0] jacobin.org

I recently made the leap from product management to coding, with a lot of help from GPT-4 (it basically taught me how to code). I’ve been obsessed with LLM workflows and kept running into the same pain: constant context resets, tool-switching, and token limits that kill flow mid-task.

So I built Slate — an AI-powered workspace that supports long-context reasoning (up to 1M tokens), persistent memory, and lets you work with multiple models (OpenAI, Claude, Gemini, etc.) in a Notion-like interface.

It’s still early, but live. If anyone here experiments with long-context LLM use cases or AI tooling, I’d love your feedback — and I’m currently giving away credits to try the Gemini models because I’ve got $300 worth that expire in 48 hours. No catch, just want it used and tested.

First time building and launching something on my own — excited but also a bit overwhelmed. Appreciate any thoughts!

https://gitlab.com/actions3/actions3 - desktop application for displaying AWS metrics and CloudWatch Logs.

I'm doing it for my personal use, but maybe someone will find it useful too ;)

Want to build a platform to alleviate chronic suffering that can't be understood by one's local doctor.

Suggestions by this platform wouldn't interfere with treatment protocol straight away; it wouldn't ask the patient to stop medicines their doctor has prescribed, or itself prescribe scheduled drugs.

It will suggest complementary interventions. Case in point: anxiety, depression, brain degeneration & other related diseases - there's Rhonda Patrick's protocol of HIIT exercises to breach the blood-brain barrier & deliver positive effects; there's Dr Chris Palmer's method of looking at metabolism & mental health jointly & benefits of a keto diet to solve such issues.

Likewise, there can suggestions from Yoga-Pranayama where deep breathing can solve insomnia & hence other diseases downstream such as hypertension in many cases.

After being on such complementary protocols, the patient's suffering will be reduced, but also the body will heal enough to an extent that their local doctor could reduce/stop medication.

The tech is in the platform, combing through wisdom of all such complementary protocols for a start. If it gains traction, we could start involving experts have system route some queries specifically to them.

I have experience building the ML-LLM part. Anyone wants to join me and build the full stack part?

I’ve been building https://lowlow.bot, it tracks price changes on any website. I was inspired by https://camelcamelcamel.com, but wanted something that worked for more than just Amazon.

It’s been handy for big purchases I’m ok waiting for and stocking up on recurring non-perishable essentials when they go on sale. It also lets me know when something has come back in stock.

I'm still working on Habitat. It's a free and open source, self-hosted social platform for local communities. The plan is for it to be federated, but that's a while off yet.

I finally cracked ansible/docker-compose provisioning on Ubuntu and plan to expand that out to support Debian also. The groundwork is there. I can finally see an official release in the distant horizon, I just need to put those quality of life features in now, like the ability to delete your own account, change your email address, notifications on comments and all that stuff.

- The idea: https://carlnewton.github.io/posts/location-based-social-net...

- A build update and plan: https://carlnewton.github.io/posts/building-habitat/

- The repository: https://github.com/carlnewton/habitat

- The project board: https://github.com/users/carlnewton/projects/2