alt Hacker NewsAsk HN: What are you working on? (June 2026)
What are you working on? Any new ideas that you're thinking about?
Comments
https://github.com/jpfaraco/muy
I've been building this little animation tool I’ve wanted for years, inspired by one of Bret Victor’s demos from his talk “Inventing on Principle”. I wrote about it here [1].
Basically, instead of setting keyframes and tweens, you perform animations in real time: select a layer, manipulate its properties and the timeline records every frame.
No install, no account needed. It's like Excalidraw, for animation.
I still have some ideas and hope to keep evolving it. And I hope other people find it useful for making neat videos.
Tritium, the legal IDE.
This week we're working on a modular WASM build to allow others to embed Tritium directly into their own platforms. AI native startup law firms love it.
I have a nonlinear attention mechanism which seems to improve data efficiency, but it's slow. I'm trying to learn the python CuTe DSL to speed it up.
I'm also reading Principles and Practice of Deep Representation Learning, Or: A Mathematical Theory of Memory.
Trying to polish a bunch of my projects I've worked on over the years but never had the cojones to release to the wider world:
Hallways (https://hallways.lonnycorp.com) - a web browser for 3D spaces, where instead of hyperlinks you have portals that you can seamlessly walk through
LonnyMQ (https://lonnymq.lonnycorp.com) - a performant, production-ready TS PostgreSQL message queue library and accompanying blog post that walks through its design (of which I'm quite proud of)
CS Final Year Project: Multi-vendor Food Delivery System
2 person team and we didn't do anything manually beside creating the entity relationship, and briefly documenting the overall design system we wanted. Now we are sitting on an almost 80% completed system with 6 more months in hand.
I’m working on Peak Flow Meter Diary, a simple app to help people with asthma record peak flow readings more easily, then combine those records with environmental data to provide earlier warnings about possible triggers.
In the UK alone, around 7.2 million people have asthma. Globally, WHO estimates that asthma affected 363 million people in 2023 and caused 442,000 deaths.
Peak Flow Meter Diary is not meant to detect every possible trigger. It will not warn you if someone suddenly sprays perfume nearby, or if a dusty bag is opened in the same room. But it could help with risks that can realistically be monitored ahead of time, such as weather, pollen, pollution, cold air, storms, and similar factors. The aim is to make daily tracking easier, show simple visual warnings and notifications, and make it easier to share useful records with clinicians.
I’m also trying to build it in a way that reduces paper, plastic, and electronic waste. If funding allows, I would like to make the project carbon-negative.
That is the bigger dream: to make a small example of how even modest start-up can think about environmental impact from the start, and use it as a practical showcase.
The pitch and full project explanation are here: https://www.kickstarter.com/projects/why5/peak-flow-meter-di...
Feedback welcome, especially from anyone with asthma, clinicians, carers, or people who have worked on health tracking tools. By now I know that my kickstarter is not going anywhere, so I would value any input was the idea that bad, or lack of marketing and accessing appropriate groups etc. I think this community has a lot of experience so I would like someone to share what could have I done better. Do not be shy to tell me if you think idea was waste of time.
I’m working on improving the global agents.md experience.
I’m doing composable and dynamic global profiles which are selected based on what you’re doing.
Still plugging away trying to build a AI Infrastructure Database - any input super welcome
Aside from that, I've launched a new tool that tries to promote Solar panels. The UK has some of the most expensive energy in the world, so I've been trying to let homeowners and building managers understand if their building's are suitable.
Uses some APIs all plugged together - including the DEFRA datasets for DSM (LiDAR from planes).
I'm working on an easy-to-embed typed language called Ekto. I am taking a lot of inspiration from Koka and aiming to support full multi-shot delimited continuations all while keeping the virtual machine deeply predictable from the host side.
I'm also rebuilding an integrated task/knowledge/publication system I'd previously built atop Gemini's Gemtext format. While I loved the simplicity, I've discovered that there are lots of burrs in that design, especially on the publication side, which I'd be able to lift by using a more fully featured document format like Djot.
Still plugging away on SourceMinder (https://github.com/ebcode/SourceMinder). I know, I know, everyone and their brother is working on token-saving schemes for LLMs. But I’ve found it to be useful even without the LLM. I’m working on a proper website for it now where you can try it out in the browser (wasm port) — try before you don’t buy (it’s GPL). Feedback welcome.
Been deep diving into visual model architectures. Currently running some small evaluations on an idea around unlabeled mask segmentation that will run efficiently on mobile phone hardware. Looking promising so far!
Been working on optimizing CLIs for cheap agent use and figuring out how to build integrated agentic features that aren’t a full chat interface. Agent UX optimization is kind of fun! Much more testable than human UX, though it’ll be interesting to see how much generalizes across model families.
Been doing this to improve/simplify the grammar for Trilogy[1], a streamlined SQL language - I’ve been planning a redo of one feature and it’s nice to be able to rapidly get feedback on various syntax success rates. Also been particularly useful to optimize error messages, which should help people too.
I've been working on a inference engine for a System F Omega inspired language and getting to a point where it is starting to feel good in small programs. I'm not sure why I started this, but I'm hoping to make something like an experience reminiscent of Lisp/Smalltalk by working in an interactive environment.
My goal with this language was to pick a set of primitives to compose and express as much as possible.
I don't have a demo up yet but if anyone was curious https://codeberg.org/lilbigdoot/gloo/src/branch/thinkythough...
The two main features I am missing right now are recursive types (I want to do proper mutual recursion and have been procrastinating) and some form of type classes or implicit modules. Structural typing has been useful and I'm finding a lot of features are falling out for free from that.
Long term goal is to create something with performance within a reasonable range of C# / Java etc generally, with tools for opting out of GC. I don't plan on chasing zero cost memory safety, since I want to spend my "budget" on tooling and expressiveness.
Until the language semantics stabilize I plan on generating some pretty naive JS/TS to play around with real programs, and eventually target .NET and native (likely via C++ transpilation)
I'm working on GPS tools to help support my current contract. I've found there are no good tools for tracing a route on a map and having a mobile device think it's traveling that route. I'm not just talking GPS coordinates, but speed, direction, motion detection, precise timing between waypoints, being able to play these trips forward and backward, step by step, etc. I'm talking time-travel debugging for GPS applications.
It's still early days, but I have a demo running. Unfortunately, it requires using a drop-in replacement library for CoreLocation. That alone may make it infeasible.
I’m working on Kern, a small, git native, make and unix inspired llm workflow.
Modules are simply folders, and the tool just reads from stdio and outputs to stdout. Runs are stored in simple text files with all the info of inputs, outputs and other metadata.
Too many things :tm: From Campaign Management CMS for an organization I'm part of. To various reverse engineering one offs.
Today I caused thermal runaway on a BLE thermal (sic!) printer. That melted half of its components together before I noticed. The fun fact is you can do that witouth authorizing, as long as printer is turned on "poof".
Now I'm trying to figure out a BT protocol if DJI Power station, so I can read and track its metrics.
I wrote an improved driver'ish for cheap 5G modem recently. I've been on the last 5% stretch for few months lol.
And I started reverse engineering my LandRover OBD/CAN stuff, so I have some data to publish for other hakers.
https://mdview.io - the best way to read big technical documentations. Right now I am working on Grill Me feature for rigorously questioning and stress-testing plans or designs without leaving the app ui
- https://namebrewery.com: An MCP for looking up domain name availability. Brainstorming names within the LLM has been great and now I can have it do the registrar look ups from within the LLM too.
- https://altitag.com: A real estate photographer can upload a drone photo and get points of interest pins overlaid on the photo using EXIF data. The annotations help provide some nice neighborhood context without needing to open up Photoshop.
I'm working on building a Gaussian Splatting PLatformhosted on Cloud GPUs so folks can integrate capture/splat rendering in their own apps.
Currently in beta, working out some pipeline optimizations. Looking for people to test! Feel free to try it out, join the discord, etc. Looking for feedback on the experience, reliability, etc.
The goal is for folks to be able to tune their own pipelines, right now I am working on adding more API params/knobs. Looking to build a good capture guide too, since most folks struggle with capture IMO
I’m working on my guitar practice app, Captrice https://www.captrice.io after a brief gap.
The last few months I’ve been reading a lot about neuroscience behind learning and practicing music and I’m fascinated by the subject. It has helped me realise why the app works for me, as well as my own mistakes that held back my progress for many years despite putting in decent efforts.
It was a much needed inspiration to continue working on it with a re-evaluated roadmap.
I recently wrote a blog post about it - https://www.captrice.io/blog/what-makes-captrice-work.html
I’m working on https://getvedahome.com
My mother had a stroke a little over a month ago and I don’t live close by. I went in search of a wellness product that would let me know how she’s doing without her feeling I’m prying too much. I didn’t find one, so now I’m trying to build it. I’m also working on moving closer.
I’ve been plugging away at my running coach style app, powered by the original idea of training for a trail race while living in a flat area with no easy access to natural climbing that has evolved into a fully functional plan generator: https://runcoach.fly.dev
It works well for me so far and I’m pretty happy with it!
I’m working on my developer portfolio that deeply incorporates the forgejo API, which is where I host my code. It basically gives a personalized dashboard for my personal projects.
Working on a brand-new version of my free project management tool, Post Haste. It’s a tool for creating new projects from templates where you set the initial folder structure and project settings, as well as enforcing naming conventions. It was initially created for video editors but you can use it in any industry.
It’s a complete redesign from scratch that combines Mac and Windows into a single codebase via Dioxus (right now they’re two completely separate codebases).
Existing app is at https://www.digitalrebellion.com/posthaste
I'm working on a framework for general purpose interactive tutoring systems. An SRS background process over a pluggable system of pedagogy protocols over a given curriculum. This is at https://github.com/patched-network/vue-skuilder, or https://patched.network/skuilder
With this framework, I'm making (among other things) an early literacy app at https://letterspractice.com. My aim here is to hit >= 75% efficacy of Mentava at <= 1% of the price.
The app is near to production readiness, and I'd be happy to share access now with anyone who has verbal but non-literate kids. Be in touch if interested at colin at letterspractice.com
Adding agents to my SQL canvas (https://kavla.dev)
Here's a live example of it figuring out when to post on HN: https://kavla.dev/hn (spoiler, its noon UTC on Sundays)
And here's it generating an interactive map of 20000 earthquakes: https://kavla.dev/quakes
I feel like the canvas is actually a great way to interact with an agent, everything it does is visible, so auditing what it did is (relatively) easy.
I still got some credits to burn so agent usage is free atm (you still have to sign up to use it though)
I'm still working on a self-hosted search service called Hister with the goal to reduce dependence on online search engines.
Hister is a full text indexer for websites and local files which automatically saves all the visited pages rendered by your browser. It provides offline result previews, a flexible web (and terminal) search interface & query language to explore saved content with ease or quickly fall back to traditional search engines.
I've been using it for a few months and as my local index is growing I can avoid opening google/duckduckgo/kagi - and even websites listed in results - more and more frequently.
The initial reception is overwhelmingly positive with already more than 30 contributors and hundreds of contributions - perhaps you can find it useful as well. (Or at least have some constructive criticism =])
GitHub: https://github.com/asciimoo/hister
Website: https://hister.org/
Small read-only demo: https://demo.hister.org/
AWS for AI agents - https://instavm.io
Providing sandboxes through a CLI. Guardrails such as egress control and secret injection and audit trails built in.
We can also be used as 3rd party sandboxes in Anthropic managed agent and OpenAI sdk.
https://instavm.io/blog/self-hosting-claude-managed-agents-o...
I'm working on a semantic layer for Nextcloud: https://astrolabecloud.com
The service is composed of two open-source services, namely a Nextcloud app (Astrolabe) and backend (nextcloud-mcp-server). I use the service as an MCP server across a number of apps, and others use it primarily for semantic search over large numbers of documents.
Both are open source, and I'm working on a managed offering, completely based in the EU, for individuals/teams that already use Nextcloud and want to be able to use semantic search across some or all of their documents.
Essentially your data stays in Nextcloud, and the MCP server backend keeps a vectordb in sync to enable semantic queries over your content. The number of supported apps is growing, including:
- notes
- deck cards
- files
- news items (RSS feeds)
- cookbook recipes
- contacts & calendar
And I'm adding support for other apps as I go.
Agent harness for durable workflows, starting with Temporal.
Most agents for durable workflows feel like toy examples. There is no "Codex" or "Claude Code" for, say, Temporal. So I'm building full-featured agent for these runtimes. Why? Because it makes long-running agents easier to operate and scale. Currently, all frontier harnesses need to run inside a guest OS and need a dedicated process, this is quite challenging to orchestrate and maintain.
To make it work, I had to figure out what part to run as deterministic workflow code, and what part to run as I/O or side effects (aka activities). I'm using a CAS for most of the payloads to maintain a lightweight footprint in the workflow code.
Currently supporting skills, MCP, prompts, a virtual file systems, and soon sandboxes.
Nothing besides normal work. Sometimes is good to do a break on personal projects after 3 years nonstop
An all time classic, a headshot generator: https://instant.photos
seeing how far 1 person project can go with Zigpoll: https://www.zigpoll.com
Crossed over 100K MRR and I'm shooting for 2M ARR by the end of the year. Growing something in this stage is totally different from making it go from zero to one so it's an interesting learning curve. AI has also changed the calculus as well where it seems less crazy to try and do this sort of thing. Time will tell!
I'm working on Ito.ai : https://www.ito.ai/
It's Agentic QA + auto-provisioning sandboxes. Makes it plug and play to do code reviews that actually run your code instead of looking at it really hard. B/c the agents control all of the environment (ie running all of the services), it's able to collect runtime evidence about pretty much everything.
A couple open source examples: (Excalidraw) https://app.ito.ai/share/d1cb1475-fbe5-4c71-901b-409ba2aa6d6... & (n8n) https://app.ito.ai/share/bb7d73aa-fd08-482d-9938-87938e2a232...
I’m working on a coding agent that doesn’t have access to the shell. Essentially all it could do is edit and read code, verify and run tests. But due to that limitation I’ve made it target only rust projects for the time being.
Im still working on station display: https://stationdisplay.com/
I also just posted a new blog post on trash valorisation: https://stefan.schueller.net/posts/kva-winterthur/
I'm working on a system-wide desktop ad-blocker and privacy guard called Zen (for almost 2.5 years now): https://github.com/irbis-sh/zen-desktop
Working on it has been a joy as ad-blocking tech touches so many aspects of software engineering - from systems and security to the intricacies of JS environments in browsers.
Benefits-wise, system-wide filtering disables ads and tracking not just in browsers, but desktop apps as well (which you'll be amazed how much they do). It's especially relevant now as Google is re-activating their efforts to hinder ad-blockers by killing Manifest V2 in Chrome. So much of tech is actively bleeding cash on AI right now, which means the efforts to screw over users will only accelerate. This makes something that sits at the network level indispensable imo.
I'm working on a dashboard for ranking llms, then finding the best local (by size) and/or hosted (by price) variants of the models. Currently have ArtificialAnalysis leaderboard for ranking, ollama registry for local models and openrouter for hosted models. https://ollamadash.up.railway.app
By default, home page gives all models in the leaderboard, local and hosted. Search for models in the search box on the home page to find the top models by ranking, local(by size) and hosted (by price).
You can also do deep querying/sorting/searching filters of models in each of these three nodes (see the other tabs on top).
The next steps I am working on (would love feedback on this or anything else):
Phase 1: - Change clicks on home page model tiles in one column to search and show models filtered by that across Artificial Analysis, Ollama, OpenRouter - User specifies their system VRAM (unified/dedicated) and we automatically filter the home page with models that would fit on that RAM - in the three columns. - User specifies their price range (per MTok, max across input and output), and we similarly filter and rank by those models across all columns. - User specifies both (VRAM and price range), and we filter by both - leaderboard is union of local and hosted, local by VRAM and hosted by price range match.
Phase 2: Once I have this working, add a local desktop client that automatically reads user system and infers VRAM, renders app as webview. Considering pyside6 with Qt for this.
Phase 3: On desktop client, user can download and chat with the local models automatically based on leaderboard, optionally call hosted models, etc. Used primarily to evaluate and compare local vs hosted models for user's use cases. Also have some interesting alternate experiences to host within the local private app for user to interact with llms, agents, etc.
Do let me know whether this seems useful, or how I can make it more useful.
I am working on an open-source alternative to Quokka.js. https://github.com/apatki1996/quoll
It started out as a project to try Fable. It wrote a lot of the code and I am learning as I go. I am still questioning some of the design choices but so far it is working. I do want to improve it, so any feedback is welcome.
I've been working on my vision for a better web app development ecosystem. https://wildloop.dev/
It currently exists of 12 libraries/tool, most of which are pretty stable by now, though some are still very much in flux.
This is one of those things that turns out to be kind of a lot of work. :-)
Helping my wife ship https://quantral.com - a platform to monitor X and Reddit for financial chatter and score companies and authors. We discovered lots of stocks early in this AI cycle from X. There’s lots of noise, so we built a platform to more easily monitor the social sentiment for our investment purposes, but now we are trying to spin out a fully fledged consumer product.
Open-source Shopify for every vertical. Then leveraging that to build an interoperable, decentralized marketplace
I've designed my first automated test equipment (4 voltmeters with 4 gains, 4 ammeters with 4 shunts, 4 regulated voltage sources) in kicad and now I'm slowly assembling it, testing and calibrating: https://imgur.com/a/ate444-Y0cORf2
Attemping to write my own CDCL SAT solver right now. I've experimented in the past with a DP & DPLL SAT solver. I'm currently somewhat mentally stuck on how to create the derived clause after a conflict, but I'll get there :)
the internet backbone for booksellers: https://bookhead.net
I wonder how many people are scraping this thread right now and posting into llm something like “take the best ideas from this thread with highest chance of quick revenue”.
Anyway, I’m working on my manual skills of soldering.
I'm working on Bsharp, an Android app to teach perfect pitch (absolute pitch) to my kids: https://play.google.com/store/apps/details?id=com.bsharp.app
I'm working on water treatment equipment that does not use chemicals. Manufacturing is bloody hard!
We are in the process of writing our own vertical stack with Go to control the machine instead of expensive and handicapped solutions from Siemens and etc.
Messing around with my Lambda Calculus tutorial repo. I just did a total rewrite of Nominal Inductive Types.
https://github.com/solomon-b/lambda-calculus-hs