Posted by david927 6/29/2025
Ask HN: What Are You Working On? (June 2025)
After a lot of grief trying to make Plex and jellyfish to work with my collection, and then some more with the community [1] I decided to make my own.
There's no selling point and clear pathway to monetize, as other solutions are way more mature and feature complete, but this is my own and serves my needs the best.
I've been working on it on and off for last 8 years or so, and it's been my personal benchmark for js ecosystem. The way it works, every now and then I come back to the project, look at the latest trends in js world and ask myself a simple question - what should I change in the codebase to make it online with the latest trends. And everytime it leads to full rewrite. Kind of funny, kind of sad.
In a nutshell I have a huge movie collection - basically I'm preparing for armageddon where all online streaming services cease to exist and I need both backend to fetch me detailed information about movies in the collection as well as frontend to help to decide what to watch tonight.
My next major endeavor will be trying to integrate RAG to take a bite at my holy grail - being able to ask a question like "get me a good gangster flick" and get reasonable recommendations.
[1] I think it was jellyfish where I was asking on their forums for how to manually create a collection, stating I'm a software engineer with 20+ exp and they kept telling me that I shouldn't touch the code... While having an online campaign asking for volunteers to contribute to the codebase.
For me that means Go + stdlib HTML templates (I want to try Gomponents at some point) to minimize dependencies. I copied the HTMX JS minified file into my source tree for some interactivity. I handwrote the CSS.
It looks very "barebones" (some would say ugly), but it's been solid as a rock. It's been a year and I haven't needed to update a thing!
I remember asking them some 10-15 years later to help me with a project and they were like "sure, we'll do it CakePHP". Initially I was like "you mean in Cobol?". But then I realized they were masters of that tech, it works, and there's no need to reinvent the wheel and learn some new trendy web framework that will be forgotten in a blink of an eye.
Autonomous robotics for sustainable agriculture. Based in the south of the UK. Prototypes of an autonomous mechanical farm-scale weeding robot currently beginning real-world testing. Still a huge amount of work to do though.
Hardware and software developed fairly much from scratch, not using ROS (for not entirely crazy reasons...); everything written in Rust which I find well suited to this application area.
The robot is built using off-the-shelf components and 3d-printed custom parts, so build cost is surprisingly low, and iterations are fast (well, for hardware dev).
On robot compute is a couple of Raspberry Pi 5s.
Currently using the RPi AI Kit for image recognition, ie Hailo 8[L] accelerators.
Not currently using any advanced robotics VLA-type AI models, but soon looking to experiment with some of it, initially in simulation.
Feel free to get in touch if you'd like to talk :) Contact details in my HN profile, and on our website.
It's a tough space - convincing farmers to give it a go and running trials takes time and the UK isn't a very startup-friendly environment - investors are too often looking for a quick return.
This is such an important area - it's only going to become more critical to be able to grow more food whilst using less fertiliser and weed killer - so I wish you the very best of luck!
Yes, it was all very sad the way SRC ended.
Coincidentally, we're based fairly close to where they operated. We are in touch with some of the people that used to be involved with SRC, and have been able to learn from some of their experiences. There is agreement that the UK can be difficult for this kind of startup, but also about the importance of the product area.
I have seen a few of these, but only one (about a decade ago) that used legs not wheels
Wouldn't it be better if the robot walked rather than rolled?
You may be able to illuminate this for me...
So we decided to stick with wheels, at least for this product iteration!
I also felt the ROS build system more convoluted than necessary; and seemed rather brittle - it was too easy to break it with OS or other updates.
We found that many off-the-shelf ROS nodes didn't do quite what we wanted, and ended up spending much more time than expected rewriting code that we expected we wouldn't need to. It is quicker, and we end up with less & more maintainable code, by writing it ourselves.
I expect this could have been resolved, but when testing ROS we also ended up using more compute resources on-robot than we expected.
Using our own system allows us to build exactly what we require, which has become more important as our system gets larger and more complex; and means integrations into other systems (including testing) are easier.
Your comment gave me a lot to think about, thank you.
Long-term, passion project of mine - I'm hoping to make this the best typing platform. Just launched the MVP last month.
The core idea of the app is focusing on using natural text. I don't think typing random words (like what some other apps do) is the most effective way to improve typing.
We offer many text topics to type (trivia, literature, etc) where you type text snippets. We offer drills (to help you nail down certain key sequences). We also offer:
- Real-time visual hand/keyboard guides (helps you to not look down at keyboard) - Extremely detailed stats on bigrams, trigrams, per-finger performance, etc. - SmartPractice mode using LLMs to create personalized exercises - Topic-based practice (coding, literature, etc.)
I started this out of passion for typing. I went from 40wpm to ~120wpm (wrote about it here if you're interested: https://www.typequicker.com/blog/learn-touch-typing) and it completely changed my perspective and career trajectory. I became a better programmer and writer because I no longer had to think about the keyboard, nor look down at it.
Currently, we're doing a lot of analysis work on character frequencies and using that to constantly improve the SmartPractice feature. Also, exploring various LLM output testing/observability tools to improve the text generation features.
Approaching this project with a freemium model (have paid AI powered features; using AI to generate text that targets user weakpoints) while everything else in the app is completely free. No ads, no trackers, etc. (Hoping to have sufficient paid users so that we can run the site and never have to even think about running ads).
I've received a lot of feedback and am always looking for ways to improve the site.
1. Typing uppercase characters counts as a mistake
I'm not sure how that got to be the case, but somehow typing an uppercase letter instead of the lowercase is a mistake, despite the fact that sentences start with a lowercase letter. This conflicts with my muscle memory of starting sentences with a capital letter.
2. WPM is not a useful metric on its own
WPM can rise and fall depending on the length of the word. The bigger the word the less likely you are to type that word correctly from muscle memory, so the speed drops. The speed also drops due to the word being longer. I believe having both metrics would yield more useful data, such as when do you slow down etc.
Speaking of which, there are some more statistic things that could help, like measuring how fast you are at fixing the mistakes, or measuring three-letter combinations instead of two-letter combinations, because the context of the third letter might help, but you do need more data to gain a statistically significant result. Maybe trying to classify mistakes by the side of keyboard they happen on -- i.e. are they simple typos or a miscoordination of your hands.
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Also, as pointed out by another commenter, hands also threw me off. I've been observing them and it's interesting that I don't use my little finger for the left row -- it's used in case I need to press shift.
> 1. Typing uppercase characters counts as a mistake. I'm not sure how that got to be the case, but somehow typing an uppercase letter instead of the lowercase is a mistake, despite the fact that sentences start with a lowercase letter. This conflicts with my muscle memory of starting sentences with a capital letter.
So if you click on the topics (or whatever mode you're on), you will see the Options menu on the side. Capitalization is off by default but you can flip that back if you prefer capitalization. I've had folks request that capitalization be off by default hence the current state but I might change the default settings.
> 2. WPM is not a useful metric on its own
All typing sites generally use the same formula to calculate WPM - the length of the word doesn't matter. Most (pretty much all sites I've tried) sites use this formula: https://www.speedtypingonline.com/typing-equations. By all typed entries it's characters in this case. So it always assumes a length of 5 (avg. word length) and that's how it's calculated acorss all typing sites.
We have VERY detailed metrics. I may add a CPM toggle (toggle between both) but it seems most people prefer WPM as that's what they're used to on other sites.
> measuring three-letter combinations instead of two-letter combinations,
We measure both - see trigrams tab in the stats section.
> Also, as pointed out by another commenter, hands also threw me off. I've been observing them and it's interesting that I don't use my little finger for the left row -- it's used in case I need to press shift.
The hands are mostly there for folks learning correct touch typing practice - it's based on the most recommended general guidance for touch typing. It can be toggled off with the hand-icon button :)
1. AI interactions cost the service money, which is inevitably passed on to the consumer. The if it's a feature I do not wish to use, I like to have options to avoid paying for that feature. So in this case, avoiding AI use is a purely economic decision.
2. I am concerned about the content LLMs are trained on. Every major AI has (in my opinion) stolen content as training material. I prefer not to support products which I believe are unethically built. In the future, if models can be trained solely on ethically sourced material where the authors have been properly compensated, I would think this position.
I've experimented in the past with running an LLM like this on a CPU-only VPS, and that actually just works.
If you host it on a server with a single GPU, you'll likely be able to easily fulfil all generation tasks for all customers. What many people don't know about inference is that it's _heavily_ memory bottlenecked, meaning that there is a lot of spare compute left over. What this means in practice is that even on a single GPU, you can serve many parallel chats at once. Think 10 "threads" of inference at 20 Tok/s.
Not only that, but there are also LLMs trained only on commons data.
Yeah, LLMs are indeed really good for this use case.
> That said. I would love to see a middle tier pricing which had some features but avoided the AI use.
Only paid features are AI features. Everything else is free and no ads :)
You can type anything and as much as you want, you have access to all the advanced stats, you can create a custom theme from a photo of your keyboard, etc.
Everything but AI features is free right now. (Might change in future as we’re adding a lot more features so we will definitely consider a mid tier price )
Dunno about the trigrams though, mostly it's on the "token group" level for me - either the upcoming lookahead feels familiar or it doesn't, and I don't much get bothered by the specific letters as much as "oh I don't have muscle memory on that word, and it's sadly nestled between two easy words, so it's going to be a patchy bit of alternating speed".
> Dunno about the trigrams though, mostly it's on the "token group" level for me - either the upcoming lookahead feels familiar or it doesn't, and I don't much get bothered by the specific letters as much as "oh I don't have muscle memory on that word, and it's sadly nestled between two easy words, so it's going to be a patchy bit of alternating speed".
Could you elaborate a bit on this part - not sure I fully follow.
The trigrams/bigrams is mostly to help the user discover if there are some patterns that really slow them down or have a lot of mistakes. This is something I wanted that I didn’t see in any other apps.
This also what we use under the hood for SmartPractice weak point identification. We look at what the most relevant character sequences (for example the ta sequence is way more common than za) are and what the user struggles with the most. This is just one of the weak points we use in the user weakness profile.
> One piece of feedback and a gripe I have with a lot of these is that missed or extra characters throw off the entire next sequence and essentially require backing up to deal with them, as opposed to wrong characters which are fine to just be mistakes you move on from. It'd be great to have some detection for when the user is continuing that re-aligns their string.
Thank you for the feedback! I’m not entirely sure I can visualize exactly what you mean by this:
> It'd be great to have some detection for when the user is continuing that re-aligns their string.
Could you give an example of this?
I curious because I’ve been exploring alternative and unique UI ideas for typing practice so this could lead me into a new direction
> according to its archive...
Let's say I mistype and don't double the first "c", but otherwise type entirely correctly.
> acording to its archive...
This would be counted as having everything wrong except the first 2 characters, which doesn't feel like a good reflection of my accuracy.
I know this is a hard problem because I don't think there's any simple guaranteed way to re-align the string to account for a possible deletion or insertion, particularly if there are more mistakes in the following text, but finding and using some sort of accuracy-maximizing alignment would be great to have.
Yes - this is a very, very good point and something I actually spent so much time analyzing how I could implement a solution to this.
I think I spent over a week at one point. I refer to this issue as an off-by one or off-by two inaccuracy. Just as in the example you provided, the user only misses one character but types the rest of the word correctly (however because they missed one, the whole word is not mistyped).
This is indeed a very hard problem and in addition to the example you provided there are many other cases where this type of off-by one (or off-by two) mistyping can occur. At this time, I've put that problem on hold. I tried a few solutions but my friends said the UI was too confusing - the general initial feedback I received is to just keep typing as natural as possible; no stopping a user when they make a mistake, no guard-rails of any kind. Just mimic real typing as much as possible.
Issue is, it's one thing to implement the solution to this but another is how to correctly display this to the user. In essence, the text is just a collection with each character having an index. Per each character we measure everything; milliseconds taken to type, errors made for that character, whether it was corrected or not, etc. But if we're handling off-by one or off-by two, displaying this to the user in a non-confusing way is really hard. UX is hard haha
Main focus is https://wheretodrink.beer, collecting and cataloging craft beer venues from around the world. No ambition of being exhaustive, but aiming for a curated and substantial list. After the last thread, a bunch of people added their suggestions, thanks! It helped add interesting new venues from cities I hadn’t covered yet.
I’m very slowly layering on features, and have a few spin-off ideas I’ll keep brewing on for later. The hardest problem thus far has been attempting to automate popularity rankings and automatic removal of defunct venues without breaching a bunch of ToS.
Also made https://drnk.beer, a small side project offering beer-related linkpages and @handles for Bluesky (AT Protocol). It's been on the backburner, but still very much live.
Probably looking for another small project for the next few months to focus on something else for a while. Always curious to see what others are building and doing. Thanks for sharing!
Think around 5% is from visitors, 10-15% from my own experience and the rest just procrastination research.
Started with the cities I know well, and after that adding on countries or cities close by, main focus has been Europe. At one point I tried to use ratebeer's dataset as a starting point, before they closed down, but it was so horribly outdated and irrelevant that it was more work than sourcing manually.
So I basically look for existing blog-ish top-lists for a city, then try to verify the information with search, social media, untappd, etc. Looking for social proof that the venue is operational and relevant.
To keep it updated I have some very rudimentary monthly tasks to ping a venue's website and notify me on things that signal they're closed. I also email myself a list of 10 random venues with all relevant links daily, so I can do a manual 5 min alive check.
- LegalJoe: AI-powered contract reviews for startups, at the "tech demo" phase right now: https://www.legaljoe.ai/
- ClipMommy: A macOS tool to help (professionals who record a lot of videos | influencers) organize their raw video clips. Simply drag a folder of "disorganized" videos onto ClipMommy, and ClipMommy organizes the videos into folders / subfolders, adding tags, based upon some special statements that you can make at either the start or the end of your video (think audio-based "clapboard"). I'm expecting to release this within a week or two on the Mac App Store (Apple allowing...).
As an aside, I've been very impressed with Claude Code, it's (for me at least!) leading the way for how the next generation of business software might leverage AI. I plan to iterate on LegalJoe to make more "agentic" as a result of what I've seen is possible in Claude Code.
I would have liked to also provide a Google Doc plugin, but the Google Docs APIs [1] don't provide the required capabilities (specifically: a way to create tracked changes). Word's Add-In APIs [2] are also limited in some regards, but since they let you manipulate raw OOXML, you can work around those limitations for the most part.
[1] https://developers.google.com/workspace/docs/api/how-tos/ove...
[2] https://learn.microsoft.com/en-us/javascript/api/word?view=w...
The insight: Most security scanners find problems but don't fix them. Industry average time to fix critical vulnerabilities is 65+ days. We generate the actual fixes and create PRs automatically, including educational content on the nature of the vulnerability and the fix in the PR description.
Technical approach: - AST-based pattern matching (moved from regex, dropped false positives from 40% to <5%) - Multi-model AI for fix generation (Claude, GPT-4, local models) - ~170 patterns across 8 languages + framework-specific patterns; can grow this easily but need more customer validation first.
Business model experiment: Success-based pricing - only charge when fixes get merged ($15/PR at the moment). No upfront costs. This forces us to generate production-quality fixes & hopefully reduces friction for onboarding.
Early observation: Slopsquatting (AI hallucinating package names that hackers pre-register) is becoming a real attack vector. It's pretty straightforward to nail and has a lot of telltales. Building detection & mitigation for that now.
Stack: Elixir/Phoenix, TypeScript, AST parsers
- 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
I'd encourage you to embrace full decentralization via blockchain technology. Why? Any successful tech that empowers and connects local communities becomes very politically interesting very quickly.
You might also be interested in geohashing as a more user friendly way to group nearby posts, although lat/lon is easier for a cpu.
Building cables for multiple personal and professional projects, I was frustrated by having to cobble together harness diagrams in Illustrator or Visio, cut snippets from from PDFs for connector outlines, map pin-outs, wire specs, cable constructions, mating terminals, and manually updating an Excel BOM.
Splice gives you:
An SVG canvas to drag-and-drop any connector or cable from your library to quickly route and bundle wires. Assign signal names to wires or cable cores.
Complete part data Connector outlines, pin-outs, terminal selections (by connector family & AWG), cable core colors & strand counts, wire AWG/color.
Automated BOM & exports parts-ready diagrams, wiring drawings, and a clean BOM in SVG, PNG, or PDF.
Connector & Cable Creators. Connectors or cables not in the existing library can be added with an optional outline and full specs (manufacturer, MPN, series, pitch, positions, IP-rating, operating temp, etc.), then publish privately or share publicly.
Demos & tutorials: Harness Builder → https://www.youtube.com/watch?v=JfQVB_iTD1I
Connector Creator → https://www.youtube.com/watch?v=zqDsCROhpy8
Cable Creator → https://www.youtube.com/watch?v=GFdQaXQxKzU
Full tutorials → https://splice-cad.com/#/tutorial/
No signup required to try—just jump in and start laying out your harness: https://splice-cad.com/#/harness. If you want to save, sign up with Google or email/password.
[1] Added many standard DSub, M8/M12, and USB connector outlines/pin arrangements to aid in the creation of connectors not currently in the library
[2] In concert with the addition of more connector outlines, added a Magic Button on the Connector and Cable Creator pages that pulls all fields for an entered MPN from Digikey or Mouser. Now, you can just enter your part number (like CDM806-04A-MP-F011-67 for this CUI connector, https://www.digikey.com/en/products/detail/same-sky-formerly...) and the fields will populate automatically. If a standard outline is recognized, you have the option to load the outline and pin arrangement too. For cables, this will pull the core count and other cable properties.
[3] The Harness Builder now features a grid and snap-to functionality to align items. You can also share a link (ie, https://splice-cad.com/#/shared/lgcy2htze9zlqs4igdgycfncy98f...) to a harness design that a collaborator can view or clone/edit).
Check out https://www.hi-harnesses.com/ - limited parts at this point but the closest thing I know of.
Obviously the main thing is getting the listings data, which as far as I know (mostly) isn't readily available any other way that scraping the cinemas' websites, for which I set this up as a separate-ish project[1]
Time Out should have long done that but instead they stopped their print edition.
Hope you didn't start on it!
(By the way, it wasn't too easy to scrape in the end…)
More PRs very welcome if you're in the mood!
I'll add the Peckhamplex now.
Handles everything from real-time driver tracking, public order tracking links, finding suitable drivers for orders, batch push notifications for automatic order assignment, etc.
Backend: Feathers.JS, Postgres + TimescaleDB & PostGIS, BullMQ, Valhalla (for multi-stop route optimization although most of our deliveries are on-demand)
Frontend: SvelteKit
Mobile App (Android only for now): React Native/Expo, Zustand, Expo push notifications, and two custom native modules for secure token storage and efficient real-time GPS tracking. The tracking was probably the toughest to get right to find the best balance between battery/data efficiency and more frequent updates.
Been testing it for a couple weeks and as of last week, that company moved their operations over to it with 50+ drivers and thousands of orders processed through it so far (in a country with pretty unreliable connectivity/infrastructure).
I built it initially as a favor but open to other applications for it.
That's a hell of a favor. Is this something you built by yourself or were you part of a larger team?
I built it all myself (including the integration with our ordering platform) It was sort of my white whale project that I've always wanted to do but didn't have the chops/time.
The advancements in AI-assisted coding encouraged me to give it a shot though and the results turned out great. It was a heavily supervised vibe-coding project that turned into a production-ready system.