391–400 of 1001 posts
I left my job as a principal software engineer a few months back and have been working on an agentic harness and https://blackbear.app -- a local first, end-to-end encrypted everything app with file editors for notes, documents, sheets, free-hand canvases, slides, and a whole lot more. Also features a calendar and task system, and a lightweight discovery engine. There's a BYOK agent system (Pax) that works with you a…
I'm working on a platform that aggregates a business's operational and financial data and builds a causal model on top, deriving target metrics like FCF or EBITDA. With that model we can forecast different scenarios — what happens if we open a new shop, raise prices, take a loan. We also generate reports: weekly overviews, anomaly detection, deviations from targets. All of this is essentially a harness for an AI agen…
I’ve been working up reimplementations of Nikoli puzzles to host on my personal blog, the goal is to work through the maths and then explain how it’s relevant or helps create a fun games. Nikoli is the magazine that helped create sudoku and made it famous - they have a lot of other pen and paper puzzles that are really fun to play.
I’ve also got two other open source tools I’ve built to help me work daily:
https://tajd.github.io/cofferdam/ which is a rust based cli tool I wrote to parse the ast of codebase and enforce architectural preferences - eg don’t reimplement design system for components down to DRY
https://tajd.github.io/projektor/ Is an ai native project management tool where I can plan work on the train and then have my agents pick it up autonomously. Bootstrapped it quickly but then have been incrementally adding more functionality to it. It’s like self hosted jira on cloudflare but much faster and has more agentic development tools. I added tooling around being able to autonomously work through epics, manage quality and fix identified bugs - https://tajd.github.io/projektor/agents/playbooks/epic-goal/. The goal being deliver useful features and then to ultimately surface the number of bugs identified by agents and users so that I can see the health of the project and figure out if I need to write more code myself or improve feature descriptions to reduce discovered bugs. I don’t think this is new at all but it’s reliable and done well, I hope.
It is a research-first method for designing or reviewing SaaS products. Its central question is: What customer outcome matters, and what evidence proves that the product delivers it?
Idea or existing product → Research real customers and current work → Identify their Jobs to Be Done → Design the minimum safe workflow, define the interface and system behavior (with a sophisticated scoring system) → Validate the workflow → Implement vertical slices → Observe proof of customer progress
FutureOfGaming.com - In-depth weekly analysis revealing what's actually being developed in gaming, from new player experiences to technical innovation. Over 1,000 gaming patents covered since Nov last year. Every Tuesday for patents and Thursdays for filed.
ContentCreators.com - education, free toolkits, tools directory, job board for content creators. Recently also set up creator profiles to build out a creator directory and connect with brands.
WebsiteAudit.com - does what it says, run my websites through it to identify gaps - anything from performance, security, SEO and get recommended fixes. Looking to expand to also add brand AI visibility, hoping to launch soon. Still in testing
It's a few classes of C# right now that parses a folder and auto generates the navigation, links, titles and summary off of the folder/file structure for the 1st level and then subsequent depth is mapped to individual items in the list view not on the nav bar (although I did that too, it looked weird with higher depth). So if you have a folder with 3 files and 2 additional folder you get 5 links in the nav bar, 3 content pages and 2 list pages. No other setup is needed. No llm written code, but I used deepseek v4 flash to ask various questions and get samples of some things.
I forgot just how much depth there is to exploring a simple problem. Loving it!
I designed Silent Shark to be the sweet spot of minimalism meeting realism of dials and procedures (like a simulated Torpedo Data Computer) that scratches my simmer geek itch without being impossible to write the game myself.
https://store.steampowered.com/app/4705650/Silent_Shark/
Browser demo: https://silentshark.app/alpha
I just finished my master's in Psychedelics and Consciousness Studies, and built the library I wanted while studying. I started it over a year ago, but put it down until my practicum advisor suggested I dust it off and go hard on it during my last term.
As of this writing, there are over 35,700 papers by over 82,200 authors organized into 37 topics, growing daily. There's a 2D map of the whole corpus and evidence syntheses on the topic pages, plus the ability to generate your own syntheses with any prompt.
It's built with Rails 8.1, uses one Postgres (for full-text search, vectors, and job queue), and runs on a $24/mo DigitalOcean droplet that I just upgraded from the $12 tier and deploy to with Kamal. Total LLM spend so far is ~$28 in DeepSeek-V4-Flash, trending down after a big one-time backfill push.
Relevance was the hardest part to get right by far. Ensuring we keep papers on LSD the psychedelic vs Lumpy Skin Disease, or Ketamine for depression vs anesthesia in cats was no small feat. The design ended up being a cheap keyword prefilter, then an LLM rubric that accepts or rejects papers. More on that here: https://consciousnesslibrary.org/docs/article-pipeline.html
It's free, no ads, no signup to read anything, and a registered 501(c)(3) I fund myself for now. I'd really like to know what breaks or any other feedback, and would love to answer any questions about it!