value: mogusian

value:
Hey HN! We're Lucas and Soheil, the founders of Praxos (https://praxos.ai). Praxos is a context manager for AI Agents, providing everything you need to build stateful agents that don't break in production.
Praxos can parse any data source, from unstructured PDFs and API streams to conversational messages, to structured databases, and transform them into a single Knowledge Graph. Everything in this graph is semantically typed and its relationships are made explicit, turning data into a clean, queryable universe of understanding that AI can use without making mistakes.
Whether you need to query for the answer to a question or to extract data in a way that makes sense for the current use case, Praxos does it all, with no requerying needed. This enables AI apps to parse data end-to-end, and then act on it to deliver outputs across single-chain and multi-chain reasoning steps. Intermediate, final, and user-edited outputs can be added back to the knowledge graph, allowing Praxos to learn on the fly.
When we were building in insurance, we often ran into two major problems deploying AI:
First, LLMs would prove incapable of parsing documents such as property schedules and insurance policies. For reference, a property schedule may be a 50-page collection of Word, Excel, and PDF documents detailing construction, usage, and geographical information about a collection of physical properties. Recreating one object (a property) would mean combing through the files establish semantic, conceptual, spatial, and sometimes implicit linkages between the data.
The outcome: relationship information would be lost, left blank, or hallucinated.
Second, repeated calls to search, retrieve, and update information would sometimes lead to cascading errors. This became more frequent across complex tasks such as reading a document, fetching previous user information, performing a calculation, storing it, and then presenting it to the user.
We realized that for AI to deliver more useful and accurate responses that correctly use relationships in the document, these relationships need to be made explicit. Much of the contextual information is represented without the usage of words. In turn, this means that we cannot directly interact with them programmatically, and LLMs are forced to interpret them themselves, every single time. That’s when we started building Praxos.
We've set up a self-serve option with a free tier (up to a data cap) for hobbyists and early-adopters. For context (no pun intended), this should cover you for up to 200 document pages. You can register here: https://data.praxos.ai/sign-up.
Our first version is an SDK meant to cover you across all your data extraction, retrieval, and update needs.
Here's how it works:
Organizing information: Praxos sorts information into ontologies, which are structured schemas for storing data. These allow you to introduce predefined types, attributes, and relationships that guide how the knowledge graph is built and interpreted.
Processing input data: Praxos can handle any data source, ranging from PDFs to tabular data, JSONs, and dialog-like exchanges. Extraction is performed end-to-end. You don't need to OCR, chunk, or pre-process your inputs. Processing is as simple as passing in your file and selecting an ontology.
Retrieving information / memories: For each query, Praxos searches and retrieves related stored information by leveraging a combination of graph traversal techniques, vector similarity and key-value lookups. Search objects will return both the entities/their connections, as well as a sentence.
We’d love to hear what you think! Please feel free to dive in, and share any thoughts or suggestions with us over Discord (https://discord.gg/wVmrXD2dJA).
Your feedback will help shape where we take Praxos from here!

value: Show HN: Praxos – Context Management for AI Agents

author: mogusian


value: GentoroAI

value:
Long time lurker, first time poster. Hi.
We recently launched Gentoro, a no-code developer platform that allows you to generate, deploy, and test MCP Tools. It’s powered by GenAI and fully built on MCP.
You can:
* Basically just paste in any OpenAPI spec
* Or use natural language descriptions
* Automatically generate MCP Tools
* Deploy and test those Tools right away
* Use the Tools via any agent framework that supports MCP (like LangChain, AutoGen, etc.)
It’s free to use and we would love to invite you to come try out the Playground and give us some honest feedback. Thank you!!!
Here it is: https://playground.gentoro.com/signup

value: Show HN: Dev platform for generating MCP Tools

author: GentoroAI


value:
Hi HN,
I over-thought one too many “lol sounds fun” texts and decided to teach a model to be my wingman instead. The result is Crush Check AI —export an iMessage / WhatsApp / Instagram thread and get a chat report with:
* crush score (0-100) based on response latency, reciprocity, sentiment shifts.
* red flags like like breadcrumbing / love-bombing
* chat timeline.
You can also ask questions about your conversation.
Why post here
I’d love feedback on:
* whether this is something people need.
* how was the user experience.
* what features would you like to see.
Thanks in advance for any roast, bug reports, or “this is useless because ___” takes. Happy to share more implementation details and happy to give away free Premium subscription in exchange for feedback!

value: Show HN: Crush Check – AI relationship text analyzer


value:
Hi HN! My family has a history of IBS. For those not aware, a diet low in a class of carbs called FODMAPs is among the most effective treatments for IBS. Following a low-FODMAP diet can be really difficult.
I made a database that estimates detailed FODMAP content for ~3M mass-produced foods. It infers product ingredient composition based on FDA/USDA data and assigns FODMAP content.
Let me know if you have any feedbacks or questions. Hopefully it is useful!

value: Show HN: Database of foods likely to trigger IBS


value: starboat

value: Elevate your LinkedIn profile with AI-generated headshots. Fast, realistic, and tailored for professionals with ProfileAIPro.

value: Show HN: Profile AI for Professional LinkedIn Headshots – ProfileAIPro

author: starboat


value: Show HN: Word Pivot – Another tiny little daily word game


value: obitoACS

value:
Hey HN, AWS S3 Express One Zone promises improved latency and throughput but comes with several limitations including only being available in one availability zone and the directory bucket structure.
We developed Accelerated Cloud Storage to offer an object storage system with high performance (up to 10X better than S3 Express One Zone in latency and throughput), strong consistency and global availability that scales and moves data based on demand. The service is accessible through an S3 compatible Go/Python SDK. ACS has enterprise-grade security compliance (SOC 2 Type 2 pending), and a transparent pay-for-usage pricing model with no egress fees.
You can sign-up on the website or schedule a call with one of our engineers to discuss further.

value: Show HN: ACS is an S3 Express One Zone Alternative

author: obitoACS


value: aethiopicuschan

value:
Hi HN,
I’m excited to share SpeechAnalyzerDylib, a tiny C-compatible dynamic library that wraps Apple’s upcoming SpeechAnalyzer API in macOS 26.0 (Tahoe). If you’re building a Swift, Objective-C, or plain C project and want to add on-device transcription with virtually no boilerplate, this might help.
## Key Features
- *C-FFI wrapper*
  Exposes a simple, C-compatible API so you can call from Swift, Objective-C or plain C.
- *Asynchronous File Transcription*
  `sw_transcribeFile(const char <i>filePath, const char </i>locale, TranscriptionCallback callback, void <i>userData)`
  Transcribe any audio file on disk in the background; delivers full transcript or error string via your callback.
- *In-Memory Data Transcription*
  `sw_transcribeData(const uint8_t </i>bytes, size_t size, const char <i>locale, TranscriptionCallback callback, void </i>userData)`
  Transcribe raw audio buffers by internally writing a temp file and reusing the file-based transcription path.
- *Live Microphone Streaming*
  `sw_startMicrophoneTranscription(const char <i>locale, TranscriptionCallback callback, void </i>userData)`
  Stream real-time speech from the default mic, receive partial transcripts as they arrive, and stop automatically when the engine stops.
- *Locale-Aware*
  All APIs accept an optional locale identifier (defaults to system locale) for language-specific models.
- *Automatic Model Management*
  Verifies or downloads the needed offline speech model for your chosen locale before starting transcription.
- *Callback-Driven Error Handling*
  On failure, your callback receives an `"Error: …"` string so you can handle retries or fallbacks.
- *Zero External Dependencies*
  Built solely on Apple’s AVFoundation & Speech frameworks—no third-party libraries required.
## Version requirements
macOS 26.0 (Tahoe) beta
Xcode 26 beta
Both are currently in beta, and SpeechAnalyzer is only available on the beta seed, so you’ll need to be running the developer betas to try it out.
## Repository & license
https://github.com/aethiopicuschan/speech-analyzer-dylib
Licensed under MIT.
## Feedback & contributions welcome
Open issues for bugs or edge cases you encounter
 Submit PRs to add tests, CI, or sample integrations
 Share your experiences or integration questions below
Looking forward to hearing what you build with it!

value: Show HN: SpeechAnalyzerDylib – C-FFI for macOS 26.0 SpeechAnalyzer API

author: aethiopicuschan


value: sebkur

value: It's based on the jediterm library developed for IDEs, but it can also be put to work as a standalone terminal emulator with tabs. The library has been around for more than 10 years, but I don't think anyone made a terminal emulator app from it?

value: Show HN: A cross-platform terminal emulator written in Java

author: sebkur


value: Eslamunto

value:
Hi HN,
I’m Eslam, a software engineer and product builder based in Munich. After being laid off from Workday earlier this year, I realized how isolating and shameful layoffs can feel, even though they are more common than ever.
That’s why I built LayoffStory, a safe space for people to anonymously share their layoff experiences, support one another, and reduce the stigma.
You can:
• Share your own story (anonymously or not)
• Upvote stories that resonate with you
• Comment or show support (“This helped me”, “I relate”)
• by tags (industry, region, etc.)
I’m looking for brutally honest feedback. What do you like? What is confusing? What would you improve?
I built it with React, Supabase, and Tailwind, and I’m planning to open-source it soon. I’m also exploring future features like career coaching and AI-based emotional support.
Thanks in advance for any feedback or suggestions
Try it here: https://layoffstory.com

value: Show HN: LayoffStory-Share your layoff experience anonymously and support others

author: Eslamunto


value: skyzouw

value:
Hi HN,
I built InvoiceFast, a minimal tool that helps freelancers generate clean, compliant invoices in seconds without the friction of complex accounting software.
As a freelancer myself, I found it frustrating to spend 15-30 minutes each time creating invoices in Word, Excel, or bloated online tools that distract from actual work. InvoiceFast is designed to let you:
 • Create and download professional PDF invoices instantly.
 • Send invoices to clients without unnecessary steps.
 • Track your invoices easily.
 • Look more professional while saving hours each month.
It’s a paid tool designed to be fast and simple, allowing freelancers and solo business owners to get paid faster while focusing on their craft.
Would love feedback from HN on:
 • What features would make invoicing truly seamless for you?
 • What are your biggest pain points with invoicing right now?
 • Would integrations (payment links, auto-reminders) make it more useful, or do you prefer simplicity?
You can try it here: https://www.invoicefast.net/
Thanks for checking it out, and I’m here to answer questions and gather your feedback.

value: Show HN: InvoiceFast – Generate clean invoices in seconds for freelancers

author: skyzouw


value: vednig

value:
Hey, just wanted to share with you guys and app that I built and deployed in a day with Lovable.
So, as a founder I always wanted to have an advisor but my budget would always be less, then on the other hand hand I had Paul's essays on Startup Advice, which I never read because I was busy building stuff.
Hence, I built this product which comes into a sweet spot of both at the same time being more reasonable and capable than the alternative.
ps: it's running on a reasoning model
and tbh I've been able to gather pretty good insights from it.
Note to PG: If you're seeing this. I'm your big fan. Thanks for doing all the stuff you do.

value: Show HN: I Built a Paul Graham AI Advisor for Founders and Hackers

author: vednig


value: devilzhong

value: Show HN: I Built a Cluely Alternative

author: devilzhong

title: Show HN: I Built a Cluely Alternative


value: duckerduck

value:
Hi HN, like many I've been interested in the direction software engineering is taking now that coding LLMs are becoming prevalent. It seems that we're not quite there for "natural language programming", but it seems new abstractions are already starting to form. In order to explore this further I've built semcheck (semantic checker). It's a simple cli tool that can be used in CI or pre-commit to check that your implementation matches your specification using LLMs.
The inspiration came while I was working on another project where I needed a data structure for a GeoJSON object, I passed Claude the text of RFC-7946 and it gave me an implementation. It took some back and forth after that before I was happy with it, but this also meant the RFC went out of context for the LLM. That's why I asked Claude again to check the RFC to make sure we haven't strayed too far from the spec. It occurred to me that it would be good to have a formal way of defining these kinds of checks that can be run in a pre-commit or merge request flow.
Creating this tool was itself an experiment to try "spec-driven-development" using Claude Code, a middle ground between completely vibe-coding and traditional programming. My workflow was as follows: ask AI to write a spec and implementation plan, edit these manually to my liking, then ask AI to execute one step at a time. Being careful that the AI doesn't drift too far from what I think is required. My very first commit [1] is the specification of the config file structure and an implementation plan.
As soon as semcheck was in a state where it could check itself it started to find issues [2]. I found that this workflow improves not just your implementation but helps you refine your specification at the same time.
Besides specification, I also started to include documentation in my rules, making sure that the configuration examples and CLI flags I have in my README.md file stay in line with implementation [3].
The best thing is that you can put found issues directly back into your AI editor for a quick iteration cycle.
Some learnings:
- LLMs are very good at finding discrepancies, as long as the number of files you pass to the comparison function isn't too large, in other words the true-positive results are quite good.
- False-positives: the LLM is a know-it-all (literally) and often thinks it knows better. The LLM is eager to use its own world knowledge to find faults. This can both be nice and problematic. I've often had it complain that my Go version doesn't exist, but it was simply released after the knowledge cutoff of that model. I specifically prompt [4] the model to only find discrepancies, but it often "chooses" to use its knowledge anyway.
- In an effort to reduce false-positives I ask the model to give me a confidence score (0-1), to indicate to me how sure it was that the issue it found is actually applicable in this scenario. The models are always super confident and output values > 0.7 almost exclusively.
- One thing that did reduced false-positives significantly is asking the model to give its reasoning before assigning a severity level to an issue found.
- In my (rudimentary) experiments I found that "thinking" models like O3 don't improve on performance much and are not worth the additional tokens/time. (likely because I already ask for the reasoning anyway)
- The models that perform best are Claude 4 and GPT-4.1
Let me know if you could see this be useful in your workflow, and what feature you would need to make it functional.
[1]: https://github.com/rejot-dev/semcheck/commit/ce0af27ca0077fe...
[2]: https://github.com/rejot-dev/semcheck/commit/2f96fc428b551d9...
[3]: https://github.com/rejot-dev/semcheck/blob/47f7aaf98811c54e2...
[4]: https://github.com/rejot-dev/semcheck/blob/fec2df48304d9eff9...

value: Show HN: Semcheck – AI Tool for checking implementation follows spec

author: duckerduck


value: rockeetterark

value:
As the creator of TerarkDB (acquired by ByteDance in 2019), I have developed ToplingDB in recent years.
ToplingDB is forked from RocksDB,   where   we have replaced almost all components with more efficient alternatives(db_bench shows ToplingDB is about ~8x faster than RocksDB):
* MemTable: SkipList is replaced by CSPP(Crash Safe Parallel Patricia trie), which is 8x faster.
* SST: BlockBasedTable is replaced by ToplingZipTable, implemented by searchable compression algo, it is very small and fast, typically less than 1μs per lookup:

  * Keys/Indexes are compressed   using NestLoudsTrie(a multi-layer nesting LOUDS succinct trie).

  * Values in a SST are compressed   together with better zip ratio than zstd, and can unzip by a single value at 1GB/sec.

  * BlockCache is no longer needed, double caching(BlockCache & PageCache) is avoided

Other hotspots are also improved:
* Flush MemTable to L0 is omited, greatly reducing write amp and is very friendly for large(GB) MemTable

  * MemTable   serves as the index of Key to "value position in WAL log"

  * Since WAL file content almost always in page cache, thus value content can be efficiently accessed by mmap

  * When Flush happens, MemTable is dumpped as an SST and WAL is treated as a blob file

    * CSPP MemTable use integer index instead of physical pointers, thus in-memory format is exactly same with in-file format

* Prefix cache for searching candidate SSTs and prefix cache for scanning by iterators

  * Caching fixed len key prefix into an array, binary search it as an uint array

* Distributed compaction(superior replacement to rocksdb remote compaction)

  * Gracefully support MergeOperator, CompactionFilter, PropertiesCollector...

  * Out of the box, development efforts are significantly reduced

  * Very easy to share compaction service on spot instances for many DB nodes

Useful Bonus Feature:
* Config by json/yaml: can config almost all features
* Optional embeded WebView: show db structures in web browser, refreshing pages like animation
* Online update db configs by http
MySQL integration, ToplingDB has integrated into MySQL by MyTopling, which is forked from MyRocks with great improvements, like improvements of ToplingDB on RocksDB:
* WBWI(WriteBatchWithIndex): like MemTable, SkipList is replace with CSPP, 20x faster(speedup is more than MemTable).
* LockManager & LockTracker: 10x faster
* Encoding & Decoding: 5x faster
* Others ....
MyRocks has many disadvantages compared to InnoDB, while MyTopling outperforms InnoDB at almost all aspect - excluding feature differences.
We have create ~100 PRs for RocksDB, in which ~40 were accepted. Our PRs are mostly "small" changes, since big changes are not likely accepted.
ToplingDB has been deployed in numerous production environments.
Welcome every one using ToplingDB & MyTopling, and discuss in https://github.com/topling/toplingdb/discussions

value: Show HN: ToplingDB - A Persistent Key-Value Store for External Storage

author: rockeetterark


value: pierre

value: Show HN: Worflows.py, the best way to build agents

author: pierre


value: sidearea

value:
Hi HN
A while back, I shared [Voxica](https://www.voxica.io) — a tool to turn dialogue into immersive audio with multiple characters and ambient soundscapes.
Today, I’m excited to share the most requested feature is now live:
*You can create your own custom voice* — just record once and reuse it to generate any dialogue in your tone, instantly.
What Voxica does:
- Turn written scripts into cinematic audio
- Support multi-character conversations
- Add ambient sounds like rain, cafés, or storms
- Use your own voice (record once, reuse forever)
- Export high-quality audio or integrate via API
I originally built this to help with a separate storytelling project, but it’s become something I use daily. Would love your thoughts, feedback, or ideas!
Try it: https://www.voxica.io
 Demo: https://www.youtube.com/watch?v=8gjfLLRjXQI
 Also live on PH today: https://www.producthunt.com/products/voxica?launch=voxica

value: Show HN: Voxica – Bring your own voice to immersive audio storytelling

author: sidearea


value: ihemaz

value: Show HN: No one can pronounce my name, so I made this app

author: ihemaz


value: devluc

value: Show HN: Exceptional free templates, component libraries and boilerplates

author: devluc


value: felixheikka

value:
Hello HN.
I’m Felix and I’ve spent the last months building Buildpad together with my brother David.
What is it?
It’s a platform where you research and plan your product with AI. I like to simply describe it as an AI co-founder that guides you through phases from idea to product.
What’s one cool thing about it?
You can do simple market research by searching through social media discussions like Reddit and X to see if problems are real before you build a solution for them.
This lets you see:
- If people experience the problem
- How it impacts them
- Existing solutions
It’s been resonating very well with our users and we just hit $6k MRR after 9 months since launching.
It’s just my brother and I working hard on this project, doing marketing, building, customer support, everything ourselves.
I just wanted to share it here in case there’s anyone who wants to build a product but is unsure if there’s demand for it. The problem research part of the app is free, so check it out if that’s you.
Let me know if you have any questions.

value: Show HN: I made an app to help you find problems with real demand from Reddit/X

author: felixheikka


value: soGeneri

value:
PomeloAPI lets you swap between GPT-4, Claude 3, FLUX images, ElevenLabs speech and more with a single REST call. One schema, one bill, no vendor lock-in.
What it is:
• One REST endpoint that speaks to GPT-4, FLUX, ElevenLabs, Kling, Veo and more.
• A consistent request+response schema, so you can swap models without rewriting code.
• Usage-based billing that tracks each model’s native price. Pay only for what your app calls.
Why bother:
Every provider ships a different SDK, authentication method and pricing unit. If you want to experiment, run A/B tests or add fallbacks, the glue code piles up fast. PomeloAPI hides that complexity. Call /v1/task, set model to whatever you need and ship.
Typical use cases:
• Content marketing: generate articles, social posts and ad copy in one pipeline.
• Product design: create mock-ups with FLUX images, then refine UI text with a chat model.
• Data analysis: summarize PDFs, extract entities and draft reports from the same job.
• Voice features: text-to-speech or speech-to-text with ElevenLabs using the very same auth token.
Example:
curl -X POST https://www.pomeloapi.com/api/v1/task \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"gpt-4","messages":[{"role":"user","content":"Hello"}]}'
Live now with a free tier. Docs at https://www.pomeloapi.com/docs. Feedback welcome!

value: Show HN: PomeloAPI – one key for 25 AI models

author: soGeneri


value: jose-handit

value: Show HN: Open Source engine that makes your AI agents improve themselves

author: jose-handit


value: kondakovia

value:
Like many devs, I became a tab hoarder, keeping dozens of tabs open “just in case”.
So I built Rotten Tabs, a Chrome extension that auto-closes old tabs unless you actually use them.
You set a tab lifespan (1–7 days). Tabs display a visual warning when they’re close to expiring, and if ignored, they close themselves. But if you return and focus on a tab for 30 seconds, its timer resets.
It’s not a full-featured tab manager - no session restore, no bookmarks, no “save for later”. Just one clear rule: tabs expire if you don’t use them.
I’m still improving it and trying to understand if a tool like this is actually useful to others. Would love your thoughts!

value: Show HN: Rotten Tabs, a Chrome extension that auto-closes unused tabs

author: kondakovia


value:
Hey HN,
I made Palmalyze, a simple tool that reads your palm using AI. Just upload a photo of your hand, and it returns a personalized palm reading in seconds.
It’s meant to be a fun way to explore the lines on your hand and what they might "say" about you — like curiosity, creativity, career, and emotional energy.
Built it over a weekend as an experiment in blending computer vision with personality insights. It’s not meant to be serious science, but it’s surprisingly insightful for something so simple.
Would love to hear what you think — especially around UX or other playful use cases you'd explore with AI + image input.

value: Show HN: I made Palmalyze, an AI palm reader that reveals the story in your hand


value: odinize

value:
Hey HN!
I just launched Odinize, an app that lets you generate a fully custom learning course on literally any topic you choose. You type in what you want to learn (e.g., “Intro to quantum physics” or “How to design a tiny home”), pick your detail level, style, and current knowledge, and Odinize builds a structured course for you in minutes.
You can also convert it into a podcast to learn on the go, and there’s an integrated AI instructor for instant questions.
I built Odinize because I was tired of scattered resources, random YouTube videos, and endless blog rabbit holes. I wanted something that adapts to you, not the other way around.
Happy to answer any questions, get feedback, or hear feature ideas. Thanks!

value: Show HN: Odinize AI – Learn Anything. Your Way. Instantly

author: odinize


value: nicksergeant

value:
I have some friends who were laid off and are on the job hunt. We were all quite surprised to learn that LinkedIn does not have a "view jobs only at companies where I have connections", so I built https://jobsbyreferral.com/
It's powered by https://rapidapi.com/letscrape-6bRBa3QguO5/api/jsearch, which is a little pricey, so I'm trying to decide whether to put more effort into the project (I'd have to charge _something_ to offset the costs).

value: Show HN: Jobs by Referral: Find jobs in your LinkedIn network

author: nicksergeant


value: simedw

value: Show HN: Spegel, a Terminal Browser That Uses LLMs to Rewrite Webpages

author: simedw


value: felphos

value:
In late 2024, I had to set up a new Stripe account because I incorporated my company in a different country. Turns out it's not as simple as just changing the country in a dropdown, you have to start from scratch.
I had hundreds of users and using Stripe's dashboard to add all of the products, prices, coupons and subscriptions manually would take ages. I contacted a couple of services that help with this kind of migration, but their quotes were way over my budget. My next option was to use Stripe's API, which is very powerful but also very complicated. I'm a designer who can code, but I didn't feel confident doing it alone, so I asked a friend, an experienced developer, to help.
It proved to be quite challenging, with many details and caveats we had to learn as we went. What we thought would take a couple of days took us a week.
After this experience, we teamed up and built https://stripemove.com, a tool that guides you through this whole process, explaining and automating that hard week we went through. It handles the technical complexity while keeping your business running. Customers keep paying on your old account while everything transfers in parallel, then you flip the switch when ready.
It's a very niche tool, built for founders who need to change their company location for personal or business reasons. For entrepreneurs buying companies established in other countries. For people in the same situation I was in a few months ago. Basically the tool I wished existed, and for a fair price. Designed to get you through this inconvenient process and back as soon as possible on growing your business.
Would love to hear from anyone who's dealt with similar Stripe migrations. What was your biggest pain point?

value: Show HN: I built the tool I wished existed for moving Stripe between countries

author: felphos


value: mmajzoobi

value: I have been working on a personal AI assistant that is hackable, open-source, modular, private and multi-modal. I named it Ubo.  In this post, I talk about why I built this and include pointers to design files, supported services, and its architecture. Happy to answer any questions.

value: Show HN: Open-source multi-modal personal AI assistant

author: mmajzoobi


value:
I just released my biggest project yet: Flint, a language-agnostic Git wrapper that lets developers code using their own formatting preferences locally, while automatically enforcing the project's style on push.
No more fighting over tabs vs spaces or dealing with noisy diffs.
GitHub: https://github.com/capsulescodes/flint
Documentation: https://flintable.com/docs/flint/
Article: https://capsules.codes/en/blog/flintable/en-flintable-introd...

value: Show HN: Flint – Write code your way while ensuring remote consistency


value: paulsabandal

value:
Hey HN,
I built Subwise to solve a personal pain point: keeping track of all the subscriptions I’ve signed up for — from SaaS tools to streaming services.
What it does
Automatically detects subscriptions from checkout pages using a browser extension
Syncs with a web dashboard that categorizes, tracks, and reminds you of recurring charges
Gives spending analytics, trends, and cost-saving insights
Supports multi-currency tracking (USD, PHP, SGD) with live conversion
Why I built it
Too many tools focus just on logging expenses. I wanted something that works more like a smart assistant — catching subscriptions as I sign up, giving nudges when renewals are coming up, and helping me consolidate or cancel if needed.
Still an MVP
I launched it recently and I’m still actively improving it. There might be bugs, but I’d love your feedback.
Live here: https://usesubwise.com
Thanks!

value: Show HN: Subwise – A Smart Subscription Tracker with Browser Integration

author: paulsabandal


value: shivam-dev

value:
A few weeks ago, we started looking for a good framework to build agentic workflows within our Rails monolith at Chatwoot, but couldn't find anything that fit our needs. So, we decided to build our own.
The SDK lets you create multiple AI agents that can interact with users, use tools, share context, and hand conversations off to each other. The SDK is provider-agnostic and designed to be thread-safe.
Here's a link to our GitHub repository with the entire code, a quick-start guide, as well as an interactive example: https://github.com/chatwoot/ai-agents
Fair warning: This is still in its early stages. Thread safety is a major goal, but we're still working through edge cases. We'd love feedback from folks who've built similar systems or have thoughts on our approach.

value: Show HN: AI Agents – Ruby SDK for building multi-agent AI workflows

author: shivam-dev


value: Show HN: Word Pivot – A daily word puzzle about letter positioning


value:
OpenQASM is a language for quantum computing, but tooling around it is still minimal.
I’ve been building a CLI-first toolchain in Go that includes:
- `qasm fmt`: code formatter
- `qasm lint`: basic linter
- `qasm highlight`: syntax highlighter (ANSI)
- `qasm lsp`: language server (VS Code extension)
- WASM build for web use
Everything is in Go, and it's a work in progress. Feedback welcome.
GitHub: https://github.com/orangekame3/qasmtools
Playground: https://www.orangekame3.net/qasmtools/
VSCode extension: https://marketplace.visualstudio.com/items?itemName=orangeka...

value: Show HN: Qasmtools CLI tools for formatting, linting, and highlighting OpenQASM


value: fechols

value:
While working remotely for a company making games with the Unreal engine, I ran into an issue with verifying builds on my home workstation: running "p4 clean" to verify the local copy of the repo was taking hours.
If my workstation blue-screened, or if there was any other reason to believe the files on disk might be corrupted or modified, I had to wait hours for the Perforce client to verify 400 GB of data each time.
So I created a tool called P4Sweep that does the same thing as "p4 clean" but 10x faster. And here's why:
* It downloads all of the MD5 hashes for all files at once, rather than one-at-a-time like "p4 clean".
* It computes the MD5 hashes of all local files in parallel, based on the number of CPU cores available.
By eliminating the round-trip-latency of requesting the MD5 hash for each file over a VPN connection, plus the increased performance from hashing all files in parallel, we got a 10x performance improvement.
The result: P4Sweep verifies a 400 GB workspace in less than 3 minutes on a 16-core workstation!
So you can be sure you have a 1:1 bit-for-bit copy of what's on the Perforce server in the time it takes to get a cup of coffee!

value: Show HN: High-performance Perforce file integrity verification

author: fechols


value:
I spent years as a data engineer debugging dashboards broken by untracked queries—Slack snippets, notebooks, and random scripts. Existing tools focus on enterprise lineage, not the daily pain points.
So leveraging my Python skills I learned django and built Tesser v1 to:
- Track ad-hoc queries (Slack/Jupyter) that modify production data
- Show which dashboards/tables they broke
- Visualize potential impacts before query runs
- Can fetch lineage data from WHs, databases and BI.
When someone runs UPDATE order_items SET price=0, Tesser:
- Flags the query source (Slack user/notebook)
- Shows affected dashboards
- Estimates data impact
Built for:
- Freelancers managing client data
- Lean startup data teams without tooling budgets
- Anyone tired of "who changed this?!" forensics
(HN: Would this solve real pain for you? Honest feedback welcome)
Demo:

value: Show HN: I built a tool to track ad-hoc SQL before they break schemas


value: itsharveenatwal

value:
I built an app where you LITERALLY have to do push-ups to use Reddit (or whatever app).
My guy, this is the summer you get SWOLE! Build a massive chest instead of doomscrolling on Hackernews.
Also, it's FREE. You can set it on a schedule. You can set it on a time limit. You can set it after X opens. Or even after you come home from work.
The apps will remain blocked until you do your push-ups!
The app is built natively on SwiftUI. I use Apple's native Vision API to detect body parts and joints. I use Apple's Screen Time API for app blocking.
I don't know what else to say so go on now and get the app!!

value: Show HN: Get off your a** and do push-ups

author: itsharveenatwal


value: graerg

value:
"The Internet is dead. The Internet remains dead. And we have killed it."
Online advertising is broken, especially for small or local businesses. You either pay a fortune to giants like Google and Meta for questionable "engagement", or you try to work with niche influencers, which has a whole different set of challenges, not the least of which is that it's hard to scale.
I've been working on IncentivizeThis to create a more direct and (hopefully) authentic alternative. The idea is to connect businesses with content creators in specific communities (both local and online) that are uniquely suited to meet the businesses' advertising requirements.
Imagine a local coffee shop wanting more buzz. They partner with us to sponsor a bounty like: "$10 for every Reddit post in r/YourCity that mentions our new espresso blend and gets 10+ upvotes." A member of the community sees this, writes a genuine post they might have made anyway, and gets paid for it. This creates a hyper-local, word-of-mouth ad network where businesses get what they pay for, and creators are rewarded for their genuine influence. Obviously this could be used for less wholesome purposes, but being the bounty gatekeeper, I'd like to think that we can mitigate this.
Under the hood, the platform is designed to be robust and automated. Bounties are managed as long lived, stateful workflows using Temporal. An LLM performs the content assessment, and creators are paid out instantly in USDC on Solana. Finding the right opportunity is also easy thanks to a semantic search feature for active bounties.
The goal is to build a more effective advertising mechanism for businesses and a new monetization channel for creators. I'd love to get the HN community's feedback on the idea and the execution.
You can check it out at the link above, or if you want to poke around the tech stack, the GitHub is [here](https://github.com/brojonat/affiliate-bounty-board).

value: Show HN: IncentivizeThis – a bounty board in the era of the Dead Internet

author: graerg


value: vinhnx

value:
Hi HN, my name is Vinh Nguyen and I’ve spent the last year building VT Chat, an minimal AI chat app that runs 100% in your browser. Privacy-first by design [0]
App: https://vtchat.io.vn. Source on GitHub: https://github.com/vinhnx/vtchat
Key technical highlights
+ BYOK for six providers: OpenAI, Anthropic, Google, Fireworks, xAI, OpenRouter—store your API keys locally and bypass shared‑service rate limits.
+ Per-account isolation: ThreadDatabase_{userId} instances in IndexedDB enforce strict data separation on shared machines.
+ Zero‑trust architecture: Local storage only, complete logout wipes all data and keys.
Tech stack & infra
+ Next.js 14 App Router, TypeScript, Tailwind CSS, Shadcn UI, Framer Motion.
+ Auth: Better Auth
+ Backend: Neon PostgreSQL. ORM with Drizzle, ArcJet security, Turborepo monorepo, Turbopack (87% faster builds)
I’m eager for feedback on the architecture, performance trade‑offs, and any edge cases I might have missed. Thank you and have a great day!
[0] VT Chat is privacy-first by design and I am committed to it. https://vtchat.io.vn/privacy

value: Show HN: VT Chat – Minimal AI Chat Application

author: vinhnx


value: dskhatri

value:
TLDR: I authored and developed an interactive fiction book introducing kids to entrepreneurship and money management. There are digital (Web Book, Audiobook) and physical (Paperback, Hardcover) formats. Read an entire storyline/adventure of the Web Book, no login required here:
https://tendollaradventure.com/sample/
---
I authored and developed an interactive children's book about entrepreneurship and money management. The journey started with Twinery, the open-source tool for making interactive fiction, discovered right here on HN. The tool kindled memories of reading CYOA style books when I was a kid, and I thought the format would be awesome for writing a story my kids could follow along, incorporating play money to learn about transactions as they occurred in the story.
Twinery is a fantastic tool, and I used it to layout the story map. I really wanted to write the content of the story in Emacs and Org Mode however. Thankfully, Twinery provided the ability to write custom Story Formats that defined how a story was exported. I wrote a Story Format called Twiorg that would export the Twinery file to an Org file and then a Org export backend (ox-twee) to do the reverse. With these tools, I could go back and forth between Emacs and Twinery for authoring the story.
The project snowballed and I ended up with the book in digital and physical book formats. The Web Book is created using another Org export backend.
Ten Dollar Adventure: https://tendollaradventure.com
Sample the Web Book (one complete storyline/adventure): https://tendollaradventure.com/sample/
I developed another nifty feature that lets readers of the physical book access an online dashboard of achievements anonymously using secret "magic words" in lieu of requiring personal information. I couldn't muster the effort to write a special org export backend for the physical books unfortunately and used a commercial editor to format these.
Twiorg: https://github.com/danishec/twiorg
ox-twee: https://github.com/danishec/ox-twee
Previous HN post on writing the transaction logic using an LLM in Emacs: https://blog.tendollaradventure.com/automating-story-logic-w...
Twinery 2: https://twinery.org/, and discussion on HN: https://news.ycombinator.com/item?id=32788965

value: Show HN: Ten Dollar Adventure, an interactive kids' book on entrepreneurship

author: dskhatri


value: shikaan

value:
A silly summer break project where I played around with Bun, which I hadn't had the chance to yet.
It's not super lisp-y, there's no car, no cdr, nor macros.
It's a Lisp-Inspired Functional Programming language that ideally doesn't require a paradigm shift when you come from C-like languages.

value: Show HN: Lifp – A Lisp Built on Bun

author: shikaan

title: Show HN: Lifp – A Lisp Built on Bun


value: bigattichouse

value: Using AI commandline tools can require allowing some scary permissions (ex: "allow model to rm -rf?"), I wanted to isolate commands using a VM that could be ephemeral (erased each time), or persistent, as needed. So instead of the AI trying to "reason out" math, it can write a little program and run it to get the answer directly. This VASTLY increases good output. This was also an experiment to use claude to create what I needed, and I'm very happy with the result.

value: Show HN: Created a script to run commands in an isolated VM for AI tool calling

author: bigattichouse


value: ihiep

value: Show HN: Flow – A Command-Line Tool for Deep Work

author: ihiep


value: lucascliberato

value:
Hey HN, I'm Lucas.
It's unreal how Spotify's algorithm shows us the same songs while amazing music stays hidden in plain sight.
What if we discovered music through human stories instead of cold algorithms?
That's why I created Vibes: To help you discover music while connecting with real people.
How does it work?
1. People vibe songs with personal context 2. Recommendations float as bottles in digital ocean 3. Each song disappears forever after discovery 4. Community votes for Song of the Week 5. Anti-algorithm approach creates genuine musical discovery
Early feedback has been promising, but I want to hear from you.
Hit me with your honest thoughts. I'm all ears!

value: Show HN: I built music discovery where songs disappear forever

author: lucascliberato


value: bhavaniravi

value: One moment you're reading a blog only to be distracted by a YouTube video. Your thoughts glide across tabs and topics, but the path remains invisible.<p>Awareness is the 1st step towards change. Find out how your focus flows from deep work to that Youtube video

value: Show HN: FocusTrain – Chrome Extension for "Tab Hoppers"

author: bhavaniravi


value:
Framework overview:
LLMs iteratively refine their own outputs—typically through a three‑phase cycle draft → critique → revision, repeat until convergence (all phases & stop rules are configurable).
I started coding three weeks ago after an eight‑year break and zero professional dev experience.
The classes work as Python callables with built in observability: instances are callable -

    from recursive_companion.base import MarketingCompanion
    agent  = MarketingCompanion()
    answer = agent("question or problem…") # final refined output
    print(answer)
    print(agent.run_log)  # list[dict] of every draft, critique & revision

Why it stays clean & modular:
* Templates are plain text files (system prompts, user prompts, protocol). Swap harsh critiques for creative ones by swapping files.
* build_templates() lets you compose any combination.
* Protocol injection cleanly separates reasoning patterns from implementation.
* New agents in 3 lines—just inherit from BaseCompanion.
* Convergence uses embedding‑based cosine similarity by default, but the metric is fully pluggable.
How it came together:
The design emerged from recursive dialogues with multiple LLMs—the same iterative process the framework now automates.
No legacy assumptions meant every piece became independent: swap models, add phases, change convergence logic—no rewiring required.
Extras:
* Streamlit app shows the thinking live as it happens.
* Demos cover raw multi agent orchestration and LangGraph integration (agents as graph nodes). Demos have outputs and display full thinking in markdown.
* Full architecture docs, comprehensive docstrings, commenting, and worked examples included.
Repo (MIT):
https://github.com/hankbesser/recursive-companion
Built by questioning everything. Learning by building, built for learning.
Thanks for reading and really looking for any feedback and open to contributors, no question or discussion is too big or small.

value: Show HN: Framework for LLM Iterative Refinement Until Mathematical Convergence


value: deepvoltaire

value:
I just launched a new Earth Engine App that maps Oxford (UK) road quality from Street View images using Computer Vision and the OSM (Open Street Map) road network.
There’s so much more data waiting to be squeezed out of aerial, satellite and street view images.
Got an idea or a use case? Reach out to philip@popien.net or https://www.linkedin.com/in/philip-popien/

value: Show HN: Road Quality App in Oxford, UK, Based on Street View Imagery

author: deepvoltaire


value: meffmadd

value:
Hey HN! I’m excited to share Aqueduct, an open-source AI gateway you can self-host to manage LLM traffic without hitting paywalls for basic features.
I'm part of a small team at TU Vienna, and we wanted to provide AI services with an OpenAI-compatible API for our university researchers with zero hassle across institutes. Every AI gateway we looked at (LiteLLM, Portkey, Kong, etc.) locked critical features like SSO, organization management, observability, or self-hosting behind enterprise plans.
We built Aqueduct to give our researchers a no-compromise solution without any "taxes." No SSO tax, no observability tax, no org management tax, no self-hosting tax.
It uses LiteLLM Router SDK for routing (models/providers/fallbacks) on top of Django for a maintainable and hackable code base.
Core features:
- Usage tracking, retries, rate limiting
- OpenAI-compatible API
- Coming soon: MCP Server management, OpenAI Responses API, Batch API
GitHub: https://github.com/tu-wien-datalab/aqueduct
Thanks for taking a look!

value: Show HN: Aqueduct AI Gateway – A Self-Hostable AI Gateway Without the "Taxes"

author: meffmadd


value: HugoDz

value: Show HN: Single binary web apps with Rust and Svelte

author: HugoDz


value: primaprashant

value:
Claude Code is great with detailed context, but I got tired of typing long prompts in the terminal all the time. I wanted local speech-to-text (STT) tool that actually worked in the terminal, so I built `hns`. It pipes your speech directly to your clipboard as text and uses faster-whisper for transcription.
```<p>$ hns # start recording<p><talk><p><Enter> # clipboard now holds the text<p>```
Now I can ramble for 2 minutes about a refactor and paste the whole brain-dump into Claude Code.
Also handy for emails, Slack messages, or feeding messy thoughts to any LLM. Nothing leaves your machine, works offline after first model download, MIT licensed.
Install: `uv tool install hns` or `pipx install hns`
Repo + demo: https://github.com/primaprashant/hns

value: Show HN: I built a local STT tool to brain-dump into Claude Code

author: primaprashant


value: Dbuild

value:
Hey HN! So I was happily using another AI chat app but missing a few  features like a prompt library or workflows (because who doesn't want their AI to do the work while they make coffee?). I did what any reasonable person does – wrote a lengthy email to https://t3.chat support with my wishlist.
Got back a super fast, thoughtful, and complete "nope" within hours. My hubris kicked in: "How hard can it be? I've done this before!"
Spoiler alert: Harder than I thought. But now I have LiteChat running at https://litechat.dev and honestly? I think it turned out pretty damn good !
*What makes it different:*
- *100% client-side* – your data never leaves your browser. Bring your own API keys and you're set
- *Multi-model everything* – OpenRouter for 300+ models, plus OpenAI, Claude, Gemini, local Ollama, whatever
- *Workflow automation* – chain AI interactions, because that's what started this whole thing
- *Power user stuff* – conversation folders, prompt library, search, keyboard shortcuts, the works
- *Code blocks that don't suck* – edit them in-browser, run JS right in chat, export individual files or ZIP everything
- *Git integration in the browser* – yes, really. Clone, commit, push from your chat app
- *Virtual file system* – full CRUD file operations, all browser-based
- *MCP server support* – hook into external tools and services
Started trying to build this "vibecoding" with https://t3.chat only (several arm joints thank me for eventually caving and using proper tools). Went full function-over-form so the UI has some... let's call them "discutable choices." Blame Gemini for that.
The repo is at https://github.com/DimitriGilbert/LiteChat/tree/beyond (beyond branch has all the latest stuff) and you can try it immediately at https://litechat.dev – no signup, no tracking, just bring your API keys.
If you're tired of vendor lock-in and want a chat that actually does what you want, maybe give it a shot?
Would love feedback on what's missing or what could be better. Flying solo on this so every star/issue/PR genuinely makes my day.

value: Show HN: LiteChat or "How Hard Can It Be to" Build an AI Chat App

author: Dbuild


value: krishnasangeeth

value:
Hey HN!
I've been fascinated by chess for years , and always wanted to build a commercial  app related to chess. So here is my humble attempt at that.
The app scans 2D chessboards using your camera, then runs Stockfish analysis on the position.
Here's how it works technically:
- We do segmentation first to crop the chessboard from the full image.
- Then we perform object detection to identify individual pieces
- Bounding box analysis for board alignment and perspective correction. This gives us a matrix 8 x 8 which represents the chessboard.
- We convert this position to FEN (Forsyth-Edwards Notation)
- Pass this FEN string to stockfish engine to get engine analysis.
The object detection model is reasonably good to the point where I thought of making the app public, but it isn’t 100% always and hence there is also an edit board option to handle it.
Right now I used a small dataset to train the object detection model. Labelled the pieces with bounding boxes using label studio and it’s a standard YOLO model. I am pretty confident on improving the model further with more data.
Try it:
iOS: https://apps.apple.com/us/app/stockfish-chess-analysis/id674...
App is behind a paywall as I need to run a server for inference. But there is a generous free tier for anyone who wants to give the app a go.
Would love feedback on the app and the underlying tech!

value: Show HN: I built an app that scans 2D chessboard to get Stockfish chess analysis

author: krishnasangeeth


value: Kareem-nofal

value:
We observed two main points in the AI automation industry that led us to these decisions:
1. *Compute is so much cheaper now compared to 15 years ago. Why are users still paying like it’s 2010?*
So, we made tasks/runs unlimited on all our paid cloud plans. We still have an open-source, self-hosted version, but for cloud users, they will now pay for premium features and have the freedom to use them as much as they want.
1. *Building a good AI agent is a knowledge transfer task, so everyone should be able to build their own agents.*
If every time I need to automate something or build an agent I have to call a “ specialist ”, so much of my knowledge will be lost in translation. That’s why we made an agent builder that is easy to use yet has all the powerful capabilities. (We are already planning the next version, so please give me your feedback.)
Give it a try here and share your feedback, please: https://www.activepieces.com/
Check out our new pricing: https://www.activepieces.com/pricing

value: Show HN: We just made automation runs/tasks unlimited and Launched agen

author: Kareem-nofal


value: hnand

value:
I made a HN client that allows you to explore comments in a breadth-first manner. Compared to the classic depth-first approach, it works much better for the larger threads - you don't lose the context and can easily skip discussions you're not interested in.
Video preview: https://imgur.com/a/tzBdpXw

value: Show HN: HackerNewt – Breadth-first exploring HN client for iOS

author: hnand


value: pzullo

value:
The latest CLI releases from google and anthropic are sweet, we wanted build one that can run any model.
mcp-use-cli lets you `/model` hop between providers instantly.
npm i -g @mcp-use/cli && you're done
What's cool:
- BYOK (your keys, encrypted locally)
- Slash commands for everything
- MCP protocol support for custom tools
- Works with OpenAI, Anthropic, Google, Mistral, Groq, local Ollama...
The whole thing's TypeScript and open source.
Built this on top of our Python + TS mcp-use libs, so it speaks MCP out of the box. You can hook up filesystem tools, DB servers, whatever you want.
The "frontend" is written with "ink" https://github.com/vadimdemedes/ink that lets you write react for your CLI, it's so cool!
There is soo much nice stuff to do here, here is the roadmap:
- add server from prompt, basically you ask the model to add and configure servers for you
- search MCPs from remote registries so you can pull configs more easily
- auth support (wip)
Repo with demo video: https://github.com/your-org/mcp-use-cli
Please let me know how you find it, I am going to be around all day! :hugs :hugs

value: Show HN: We built an open source BYOK CLI that supports any model and any MCP

author: pzullo


value: zeroindexed

value: We all save articles and videos for “later”—but later rarely comes. MyPodcast turns your saved content into narrated podcast episodes you can actually listen to, anywhere.<p>- Save articles or YouTube videos via our lightweight browser extension<p>- Get your personal podcast feed, delivered to your favorite app<p>- Choose between full reads or TL;DL summaries<p>- Great for commutes, chores, or walks<p>Free up your reading list and stay informed—without adding more screen time.

value: Show HN: MyPodcast – Your saved articles, turned into a personal podcast

author: zeroindexed


value: RobertLong

value:
Bezi is the AI agent for Unity game development I've wanted for my own projects. It fully understands you project, answers questions, and is a full-featured C# code agent with Cursor-style checkpoints and edits. Unlike other code agents though, it's deeply integrated with the Unity Editor and can do things like:
- Mention or pin game objects, scripts, prefabs, etc. with fast autocomplete.
- Understand complex scene hierarchy, component relationships, and other Unity-specific context that other tools simply don't have or spend more tokens to understand.
- Full project-wide RAG. Bezi indexes your entire project and understands your assets.
- Web search, Unity docs search, and more.
I have a background in the XR space and work on a number of Unity projects as a hobby. I'm biased but, I'm having a ton of fun using Bezi in my free time to prototype and build out ideas. I've built character controllers and gameplay mechanics a number of times and being able to skip the boilerplate and get to the fun part is a game changer.
We're building this for individuals and studios who want to use AI to speed up their development without the hassle of manually crafting their context in other tools but also for people like myself who are working on side-projects or indie games in their free time.
If you've ever wanted to build a game but didn't know where to start, Bezi is a great way to learn game dev. Let me know if you have any feedback or questions!

value: Show HN: Bezi – AI agent for Unity game development

author: RobertLong


value: chriseh

value:
Built Aegis AI (on IOS) after losing hours each day to doom-scrolling, its a real problem especially for this generation - 99% of the time, main productivity gains can be won by limiting phone use.
- Data 100 % stored on device. Swift + OpenAI API for usage analysis (with smart prompting), report data stored privately on device. Firebase backend for authentication no personal data saved.
• Generates adaptive blocking plans for critical applications (blocks them and reviews weekly), serves as a mobile productivity coach, deep analytics, advanced blocking modes that allow for timed deep-focus sprints. Think “Whoop” but for your social media addiction.
• Subscriptions handled with RevenueCat; CloudKit for backup.
Looking for blunt feedback on:
1. Does the adaptive algorithm feel smarter than fixed limits, do you see value in being served the solution to your specific usage v.s traditional apps just giving you blocking functionality?
2. Is the weekly review enough, how else would you think of integrating AI to help for this use case. What other features do you consider essential?
3. Should pricing stay subscription, move to one-time or freemium (for flywheel effect)?
Happy to share more info on request.

value: Show HN: Aegis AI – Adaptive screen-time coach that blocks distractions

author: chriseh


value: Show HN: A tool to minimize echo chambers on social media


value:
I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps.
The deeper problem
1. Not portable – context is vendor-locked; nothing travels across tools.
2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance.
3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried.
Demo video: https://youtu.be/iANZ32dnK60
Repo: https://github.com/RedPlanetHQ/core
What we built
- CORE (Context Oriented Relational Engine): An open source, shareable knowledge graph (your memory vault) that lets any LLM (ChatGPT, Cursor, Claude, SOL, etc.) share and query the same persistent context.
- Temporal + relational: Every fact gets a full version history (who, when, why), and nothing is wiped out when you change it—just timestamped and retired.
- Local-first or hosted: Run it offline in Docker, or use our hosted instance. You choose which memories sync and which stay private.
Try it
- Hosted free tier (HN launch): https://core.heysol.ai
- Docs: https://docs.heysol.ai/core/overview

value: Show HN: Core – open source memory graph for LLMs – shareable, user owned


value: gustavofior

value: Show HN: Open-source backend for AI Apps

author: gustavofior


value: robert-whiteley

value:
I took a 9-week Data Science bootcamp last year, having previously had no formal software development education. My previous jobs had been mechanical product development and business development.
During the course, I came up with the idea to extract valuable information from natural language. Online reviews seemed like a good place to start.
Unlike other platforms that pass reviews to an LLM and get it to output the sentiment, I came up with a formula for calculating how much each individual review comment affects the business's overall Google rating (see Reviews page of the demo).
The 'impact' values are then added up to tell business owners where they are doing well/poorly in terms of customer experience and suggests prioritised improvement actions (see Actions on Dashboard page) so that they know where to focus their attention.
So far, 25+ businesses are using the platform, mainly restaurants and food & beverage consultancies, but also cleaning services, bakeries.
I built the product myself, solo, it uses FastAPI backend, ReactJS frontend, Stripe for payments and OpenAI for the AI API.
A difficult part of building the app was creating the system message (prompt) that is used by the AI to extract the structured output from the reviews. This took many days of crafting, trial and error, not just to make it effective, but also cost effective for analysing hundreds of thousands of reviews, i.e. not just using the most expensive model.
Please give the platform a try, no signup required, and I have added 8 real businesses to the demo, with live data, which updates daily as customers leave reviews.
Let me know what you think?

value: Show HN: A tool for services businesses to improve their customer experience

author: robert-whiteley


value: Show HN: Union - The Unity MCP Server

title: Show HN: Union - The Unity MCP Server


value: arashvakil

value:
Hi HN,
I wanted to give my family, who are scattered all over the world, a simple and private way to connect. The commercial options didn't quite fit, and the open-source tools I found were a bit too barebones and not friendly enough for non-technical users.
My main goal was to build something completely self-service. I wanted my family to be able to manage their own devices without my help, so I could set it up once and then stay out of it.
This led me to build LeiaGuard, a self-hostable UI for WireGuard built with Next.js. To make it truly easy for everyone, the interface is available in both English and Farsi.
Here's how it helps with that:
- Self-service invites: You can send multi-use invitation codes to onboard new family members.
- Easy device management: Users add their own devices and get set up with a QR code or config file, no admin help needed.
- Simple admin panel: When you do need to step in, there's a clean dashboard to manage users and invites.
- Simple deployment: Comes with a one-command script for Hetzner and a Docker Compose setup for other hosts.
- Secure by default: Uses NextAuth.js for authentication.
The project is MIT licensed. I'd love to get your feedback and hope it might be useful for your family too.
You can check it out on GitHub: https://github.com/arashvakil/LeiaGuard

value: Show HN: I built a VPN management UI for my non-technical family

author: arashvakil


value: yoeldk

value:
Hi HN,
QuizIt started as a side project months ago when we realised writing quiz questions often took much longer than
running the quiz itself. We wanted to keep the live quiz energy while skipping the manual question writing.
What it does
* Type an idea or prompt, or add a YouTube link, website URL, PDF, DOC or Image → a full multiple-choice
quiz appears in under a minute.
* Supports multiple source types - prompts, automatic web search, YouTube videos, PDFs, DOCs, and
web pages.
* Working only from a prompt? QuizIt can automatically scan the web for fresh context before
generating questions.
Three modes
* Live - share a code, anyone joins in the browser, no login, and the host can choose to play or just
host.
* Challenge - one-shot solo quiz with a public leaderboard (player logs in so the score sticks).
* Solo practice - private practice for the quiz creator.
- Perfect for self-learning - students can spin up quizzes themselves, get instant feedback, and track
progress.
- Great for friends & family fun - fire up a live game in seconds and compete for bragging rights.
- Each answer is auto-graded and includes a concise explanation that adds extra context - not just
whether it’s correct.
Tech bits
Front end: React + Vite Back end: Firebase (DB + Functions) AI models: OpenAI + Gemini
Try it
https://quizit.ai
Demo challenge: https://quizit.ai/challenge/c-1751001271909
How it’s different
Other tools still make you write every question. QuizIt pulls questions and distractors straight from the
source, adds concise explanations, and is playable right away. It also works with a wider range of inputs- plain prompts with optional web context, YouTube videos, PDFs, DOCs, and web pages-so you can build a quiz from almost anything.
Looking for feedback
* Which features feel missing or rough around the edges?
* How smooth is the flow from idea/prompt to a playable quiz?
* Any friction when friends or students join a live game?
* Any other feedback or suggestions to improve QuizIt?
I have a pool of complimentary educator licenses while we smooth rough edges. Happy to answer anything.
Yoel

value: Show HN: QuizIt – Instantly builds live multiplayer quizzes from any idea

author: yoeldk


value: YuvalFishbine

value:
I always loved seeing my Spotify Wrapped every year and wondered why doesn’t ChatGPT have something similar? So I built GPTRecap: paste your exported file and instantly see your top topics, total messages, and more. All core features run 100% in your browser, no account, no data stored.
Premium insights (like deeper topic analysis) are processed via OpenAI, but nothing is saved on our servers.
Would love feedback! What stats would you want to see next?

value: Show HN: GPTRecap – A "Spotify Wrapped" for your ChatGPT usage

author: YuvalFishbine


value: Try out the app by going to app.chesscoach.dev

value: Show HN: I built a chess coach to teach you how to improve


value: samuelgursky

value:
Over the last 15 years I've worked as an AE/Editor, DIT, Colorist, Online Editor & Post Supervisor and based on my experience I've built a tool that I hope will be useful for some of you!
It's a cinema calculator (aspect ratios, target speeds, target bitrates & more...) called CineMath and it's available for free download in the Apple App Store.
I would be immensely grateful for any feedback and hope that it helps someone in their workflow!

value: Show HN: CineMath – I built this free app to help filmmakers avoid math

author: samuelgursky


value: sinameraji

value:
i've been a power user of slack/discord and etc. since i was a kid and i dont like the fact that they get unusable/noisy after 20 members join.
so i designed integral to get rid of the 2 biggest causes of noise on slack/discord and similar apps:
1. channels
2. recency based feed
i've replaced these 2 with a few subtle features (different approaches for business vs communities). check it out and let me know what you think :)

value: Show HN: Integral, AI-native Slack for teams and communities

author: sinameraji


value: grandinquistor

value: Have been working on a side project to better manage my lifestyle changes to address my chronic acid reflux. Hope it can help others too.

value: Show HN: I built an app to manage acid reflux after struggling with it for years

author: grandinquistor


value:
Hey HN,
I was spending about 30 minutes every morning scrolling through Hacker News, opening dozens of tabs, reading comments on stories that weren't even that relevant to me.
So I built a Python script that would scrape HN, filter stories based on my interests (AI, startups, behavioural economics, ...), and email me a digest. Originally I was just using it locally for myself, but after showing a few friends who wanted to use it too, I decided to build it out as a proper web app.
You can check it out at https://hnscraper.com
You sign up, add your interests, and every morning you get an email with only the HN stories that match what you care about. Each story includes an AI summary and key insights from the comments. You can then view the original post, save stories, add notes and upvote / downvote (there’s a learning model to update your interests).
I've been using it myself and it's cut my HN browsing time down massively while still keeping me informed!
Technical details: Built with Python and FastAPI. Running on Railway with PostgreSQL, using local embeddings to keep costs down (75% cheaper than using OpenAI for everything). Code is here: https://github.com/alexanderjuxoncobb/selenium-hacker-news-s...
Hopefully this helps anyone looking to cut down their scrolling time. Happy to answer any questions!
TLDR: select your interests and get an AI-generated dashboard emailed each morning that summarises any new, relevant HN stories alongside some discussion analysis (things like technical details, community consensus, BI recommendations).

value: Show HN: I built a personalised HN digest to stop wasting 30min/day scrolling


value: eigenvalue

value:
Claude Code Agent Farm is a powerful orchestration framework that runs multiple Claude Code (cc) sessions in parallel to systematically improve your codebase. It supports multiple technology stacks and workflow types, allowing teams of AI agents to work together on large-scale code improvements.
Key Features
Parallel Processing: Run 20+ Claude Code agents simultaneously (up to 50 with max_agents config)
 Multiple Workflows: Bug fixing, best practices implementation, or coordinated multi-agent development
 Agent Coordination: Advanced lock-based system prevents conflicts between parallel agents
 Multi-Stack Support: 34 technology stacks including Next.js, Python, Rust, Go, Java, Angular, Flutter, C++, and more
 Smart Monitoring: Real-time dashboard showing agent status and progress
 Auto-Recovery: Automatically restarts agents when needed
 Progress Tracking: Git commits and structured progress documents
 Highly Configurable: JSON configs with variable substitution
 Flexible Viewing: Multiple tmux viewing modes
 Safe Operation: Automatic settings backup/restore, file locking, atomic operations
 Development Setup: 24 integrated tool installation scripts for complete environments

value: Show HN: Claude Code Agent Farm

author: eigenvalue

title: Show HN: Claude Code Agent Farm


value: adilhafeez

value:
Hi HN — we're the team behind Arch (https://github.com/katanemo/archgw), an open-source proxy for LLMs written in Rust. Today we're releasing Arch-Router (https://huggingface.co/katanemo/Arch-Router-1.5B), a 1.5B router model for preference-based routing, now integrated into the proxy. As teams integrate multiple LLMs - each with different strengths, styles, or cost/latency profiles — routing the right prompt to the right model becomes a critical part of the application design. But it's still an open problem. Most routing systems fall into two camps:
- Embedding-based routers use intent classifiers — label a prompt as “support,” “SQL,” or “math,” then route to a matching model. This works for simple tasks but breaks down in real conversations. Users shift topics mid-conversation, task boundaries blur, and product changes require retraining classifiers.
- Performance-based routers pick models based on benchmarks like MMLU or MT-Bench, or based on latency or cost curves. But benchmarks often miss what matters in production: domain-specific quality or subjective preferences like “Will legal accept this clause?”
Arch-Router takes a different approach: route by preferences written in plain language. You write rules like “contract clauses → GPT-4o” or “quick travel tips → Gemini Flash.” The router maps the prompt (and conversation context) to those rules using a lightweight 1.5B autoregressive model. No retraining, no fragile if/else chains. We built this with input from teams at Twilio and Atlassian. It handles intent drift, supports multi-turn conversations, and lets you swap in or out models with a one-line change to the routing policy. Full details are in our paper (https://arxiv.org/abs/2506.16655), but here's a snapshot:
Specs:
- 1.5B params — runs on a single GPU (or CPU for testing)
- No retraining needed — point it at any mix of LLMs
- Cost and latency aware — route heavy tasks to expensive models, light tasks to faster/cheaper ones
- Outperforms larger closed models on our conversational routing benchmarks (details in the paper)
Links:
- Arch Proxy (open source): https://github.com/katanemo/archgw
- Model + code: https://huggingface.co/katanemo/Arch-Router-1.5B
- Paper: https://arxiv.org/abs/2506.16655

value: Show HN: Arch-Router – 1.5B model for LLM routing by preferences, not benchmarks

author: adilhafeez


value: coderinsan

value:
Hey HN, we’re officially launching Tramlines.io!
The idea: We now have a ton of official MCP servers for tools like Notion, Linear, Sentry, etc.—but it’s still a nightmare to use these securely. They’re susceptible to prompt injections, indirect prompt injections, confused deputy attacks, and more.
It’s a tricky problem—some MCPs, like the official Sentry MCP, are well-designed with constrained inputs and minimal mutating tools. Others, like the official Linear MCP, have looser input constraints and a wide range of mutating tools. So now, a user has to think about securing just Sentry, just Linear, and the combined attack surface of Linear + Sentry workflows.
And then all that effort goes out the window when you add a new MCP—like GitHub—which massively increases the attack surface again.
To solve this, we built a lightweight proxy that runs locally at the MCP layer. It powers expressive guardrails that decide whether MCP tool calls should be allowed or blocked.
We used Python metaprogramming to define our DSL, which allows you to express guardrails as a one-to-many mapping from policy to rules. These rules support fine-grained scanning of malicious inputs/outputs, tool call sequences, and behavioral patterns.
This is where the Tramlines DSL shines. Since it’s based on Python metaprogramming, you can write rules for just Linear, just Sentry, and then compose those into higher-order rules for combined workflows like Linear + Sentry. This prevents the usual guardrail explosion problem as you scale coverage.
The DSL’s expressiveness also helps tailor how aggressive your policies are. For low-stakes workflows, drop in one of our built-in detectors—like hidden Unicode detection, prompt injection patterns, or basic PII detection. For high-stakes workflows, define custom rules that scan for contiguous or non-contiguous tool sequences, monitor latency between tool calls, or use heuristics from external sources to enrich logic.
Case in point: One of the first MCP servers we evaluated was the official stdio Heroku MCP—a security nightmare due to its massive set of mutating tools. Here’s an exploit we found and the guardrails we wrote to mitigate it - https://www.tramlines.io/blog/heroku-mcp-exploit After we reported it, Heroku acknowledged and nerfed their remote MCP tool spec to drastically reduce the blast radius—removing tools that manage logs, deployments, etc. and leaving only those for managing instances.
With Tramlines, our goal is to give users the guardrail assurances they need to confidently use powerful MCPs—without having to rely on nerfed toolsets out of fear.

value: Show HN: OneClick local runtime proxy with expressive guardrails for MCP servers

author: coderinsan


value: iJohnPaul

value: Show HN: Host custom poker games between LLMs

author: iJohnPaul


value: JnthnMyrs

value:
A web app to bring back a small part of what made Flash such a great tool— the immediacy of personal expression on the web.
Play around with it and share your GIFs with your friends.
Enjoy!

value: Show HN: Fliiipbook.com – a simple GIF animation app for the web

author: JnthnMyrs


value: skoutXII

value:
Hey HN!
As a reader of epic fantasy and sci-fi, I often find myself reaching for my phone to look up an obscure side character — or the difference between “Genebackis” and “Genebaris”. So I built runik to bring in-world definitions directly onto my e-reader and stay immersed in the story.
Runik parses the contents of fan wikis into Kobo and Kindle compatible dictionaries. It uses the device’s built-in word lookup feature, so there’s no jailbreaking required and definitions can be used offline.
It’s still in early development and is built with Go (Wails) + Svelte + Dictutil — feedback is appreciated!
Note: Kindle support requires kindlegen, which comes bundled with the Kindle Previewer app (details in the README).
https://runik.app/
https://github.com/Runik-3/core

value: Show HN: Runik – Turn fan wikis into e-reader dictionaries

author: skoutXII


value: terryosayawe

value:
Hey HN!
I just launched TrustyPost — a modern, Apple-inspired social media toolkit for creators and small teams.
Built it because I was tired of using 4+ tools just to post to socials:
- Canva for design
 - Google Docs for planning
 - ChatGPT for captions
 - Buffer/Hootsuite for publishing
What it does:

  Write + enhance captions with AI
  Design social graphics with built-in studio
  Schedule & auto-post to all major platforms
  Works with multiple accounts, templates, recurring posts
  Real-time feedback on post status

Why it’s different:
- Apple-like UI with minimal, beautiful interactions
 - All-in-one — from idea to scheduled post
 - Mobile optimized
 - Fast + zero clutter
We just launched the MVP and I’m offering 1 month Pro access free to anyone willing to give feedback
Would love to hear what you think:
https://trustypost.com
Thanks!

value: Show HN: TrustyPost – An All-in-One Creator Toolkit (Design, AI, Scheduling)

author: terryosayawe


value: web-cowboy

value:
I got tired of typing the same detailed instructions to Claude every time I wanted specific help. "Remember my coding standards, avoid these patterns, format output like this..." over and over.
So I built a simple MCP server that lets you save prompt templates and reuse them with a tag system. Create a prompt once, then just type ">> code-review" or ">> music-discovery" and it pulls in all your detailed instructions with variable substitution.
Under the hood it's just markdown files with {{variable}} syntax. The MCP integration means it works with any client that supports the protocol (I use it with Claude Desktop and Cursor).
The use case that sold me on building this was music recommendations. Instead of re-explaining my Spotify workflow and preferences every time, I created one comprehensive template. Now I just tag it and fill in my current mood. I also use it a ton at work to make progress on Linear tickets or add new APIs.
It's basically solving the "I wish I could save this prompt" problem that comes up when you start using LLMs for regular workflows. Nothing fancy, just practical (ymmv).
Just published, but been using it locally for some time. Hope it proves useful to someone. Feedback welcome.
GitHub: https://github.com/raisinbread/teleprompter
NPM: https://www.npmjs.com/package/mcp-teleprompter

value: Show HN: MCP-Teleprompter – Stop repeating yourself to LLMs

author: web-cowboy


value: maxpumperla

value: Show HN: Poker learning platform for serious players

author: maxpumperla


value:
I save a ton of great stuff on X but never get around to reading it.
So I built a simple tool that emails me one of my bookmarks each day.
It helps me actually work through my backlog—no more endless scroll.
Would love feedback: https://savedsend.com

value: Show HN: I read and organized all my X(Twitter) bookmarks


value: babakode

value:
I just launched JS1024 — a creative coding challenge where your entire JavaScript project must fit in 1024 bytes.
No libraries. No frameworks. Just raw code and pure creativity.
You can submit:
- generative art
- visual experiments
- tiny games
- music/synths
- or anything you can fit in 1KB of JS
The challenge just started. Submissions are open now.
Th theme is: CREEPY
→ https://js1024.fun
Think of it as a spiritual successor to JS1k and oldschool demoscene comps — for devs who love constraints.
Would love feedback, and if you’ve ever made something tiny in JS, feel free to drop it here.

value: Show HN: JS1024 – 1KB JavaScript Demoscene Challenge Just Launched

author: babakode


value:
Hi HN,
We're excited to introduce Fixstars AIBooster, our new performance engineering tool designed to significantly accelerate AI model training while optimizing GPU utilization.
AIBooster provides:
Real-time monitoring of GPU, CPU, memory, and power consumption.
Clear visibility into performance bottlenecks, helping developers optimize AI workloads.
Proven acceleration of AI training processes—users commonly achieve up to 2-3x speed improvements.
Significant cost savings by maximizing infrastructure efficiency.
It's free to try, requires minimal setup, and integrates seamlessly into your existing infrastructure.
We've built this tool to empower AI developers to get the most from their GPU infrastructure without complicated tuning.
We'd love your feedback, questions, or suggestions!

value: Show HN: Fixstars AIBooster – Accelerate AI Training and Cut GPU Costs


value: Show HN: Used GIPHY to launch branded GIFs, hit 15K+ views in 3 days


value: arnestrickmann

value:
Hi HN,
We built Cronus, a context-aware time tracker for macOS that uses LLMs to differentiate productive tasks from distractions—even on sites like YouTube or LinkedIn.
Existing apps frustrated us because they either strictly blocked useful sites or required constant manual tracking. Cronus understands context automatically:
- Accurately labels productive vs. distracted time (e.g., coding tutorial vs. random scrolling)
- Menu-bar mini-timer to subtly gamify productivity
- Supports 24h time-tracking with ai suggestions based on calendar activity
- Understand where you actually spend your time
- Nudges instead of rigid site blockers
Would love feedback, particularly on how intuitive the tracking feels and any improvements you'd like to see in the UI/UX.
Also working on adding local model support for the activity categorization.
You can give it a try here: https://cronushq.com
Happy to answer any technical questions or discuss how the categorization works under the hood!
– Moritz & Arne

value: Show HN: Cronus – Context-aware AI time tracker for macOS

author: arnestrickmann


value: nithyags

value:
Promptle – The Daily AI Prompt Challenge
What if Wordle met ChatGPT? Ever feel stuck trying to get the right output from ChatGPT or Midjourney?
The idea sparked from a simple thought: “What if Wordle met ChatGPT?” I wanted to gamify the creative process of writing AI prompts—a skill becoming as vital as coding. As an avid prompt tinkerer and daily Wordle player, I felt there was a missing intersection between creative constraint, feedback, and skill-building. Thus, Promptle was born: a daily game where players write prompts instead of guesses, and creativity—not just logic—is the path to victory.
How it works:
- You get a daily creative challenge like “Describe a city that only appears during eclipses.”
- Write a prompt and get scored on accuracy, creativity, and efficiency
- Color-coded feedback à la Wordle
- 3 tries per day + unlock a fun bonus round if you crush it (e.g., “Now turn it into a limerick!”)
- No login, no accounts, just localStorage to track your personal best and personal streak — just play.
- Share your score with friends using a signature Promptle-style, complete with medals  and your final score (Think Wordle sharing… but for prompt nerds)
Tech bits overview:
- Built entirely in Bolt.new with React + Tailwind + GPT-4 Turbo + GPT-3.5 + TypeScript
- Animations done with Frame Motion
- LocalStorage from streaks and stats
- Custom scoring using Custom GPT evaluator + similarity rubricsStreaks tracked in localStorage
- Voice(experimental!) via Eleven LabsDeployed on Netlify in minutes
This is my little love letter to prompt craft and creative constraint
Curious to see how you would write a prompt for “an alien smoothie recipe”?
Try it here: https://promptle.quest/
 Learn more about how this was built: https://devpost.com/software/promptle-creative-prompt-challe...
Let the daily prompt grind begin!

value: Show HN: Promptle – The Daily AI Prompt Challenge

author: nithyags


value: bigonion

value:
I spend a lot of time on email, and a lot of time driving, so I built an app where I can manage my email through voice while driving.
The way it works is it gives an AI voice agent access to a Gmail MCP with several tools. Just talk to it and tell it what to do and it will use the most appropriate tools.
No emails are stored. All connections are encrypted. We passed a 3rd party Google CASA security audit for our tech.
Let me know if you have any questions/feedback!

value: Show HN: Manage Gmail with Voice While Driving

author: bigonion


value: nubani

value: Show HN: ComplaintBox: A social platform for complaints, solutions, and voting

author: nubani


value: anthonyag

value: Show HN: Generate presentation slides from Jira backlog. + Demo-playground

author: anthonyag


value: stankot

value:
Hey HN,
I needed a few simple graphs for a blog post [0]. Instead of slapping together a few SVGs and moving on, I decided to write a whole library to parse CSS keyframe animations and convert them to interactive graphs.
It ended up being a rabbit hole, with a lot of caveats. But it was fun to make, and I'm really happy with the graphs it produces.
I'm not sure how useful it will be for others. If you end up using it, I'd love to see how - feel free to reach out.
It's open source [1] under the MIT license. Written in TypeScript with no dependencies.
Let me know what you think!
[0] https://muffinman.io/blog/css-image-glitch/
[1] https://github.com/Stanko/monorail

value: Show HN: Monorail – Turn CSS animations into interactive SVG graphs

author: stankot


value: Show HN: Nextbike.lol – Track any rental bike across Europe


value: debarshri

value: I wrote a small golang project to render terminal on browser. It is a single binary that can be deployed on any server and you can access the terminal over web.

value: Show HN: Terminal in Browser

author: debarshri

title: Show HN: Terminal in Browser


value: rglullis

value:
I've mentioned CareerCupid [0] a few times, a website where people can find out about other potential co-workers and companies that share their values and can be used a some form of screening system without forcing people to apply to a specific position.
To help overcome the chicken-and-egg issue, there is something a bit novel: the website integrates with ActivityPub, so you can follow @thecupid@cupid.careers (this is not a Mastodon bot, but a fully-fledged application built on my Django ActivityPub Toolkit [1]), I've made a quick demo [2] about on the last FediForum to show how we can build applications to leverage the existing social graph instead of trying to make the Fediverse grow by re-implementing federated versions of the traditional social networks.
When I first launched this, I made a post where I offered a discount for the first companies joining, but it didn't get a lot of visibility. Now that we got to the first of the month day and the "Who is hiring?" threads are upon us, I thought it would be a good time to say that the company pages and job listings are also integrated with ActivityPub and I'll be offering 3 months completely free for the first 100 people that signup (code HN2025)
If you want to try it out, you need to create an account and create a "company page" (https://cupid.careers/company/new), after creating the basic page, you will see the option to complete the subscription. Use the code and you'll be good to go.
----
It works in a similar way as OkCupid used to work: people answer questions and they indicate (a) how they would like other people to respond and (b) how important their answer is to you. By comparing your answers against everyone else's, we can create a "compatibility score" that can be a measure of how well you'd get along with a potential co-worker.
Another thing that I've been working on is what I am calling a "Skill Tree". My plan is to build make it easier for both hiring manager and employees to see what parts of the tech stack are really important vs what can be learned on the job or "adapted" by someone with experience in a related skill. When defining the skills, the same matching algorithm can be applied to score the technical fit.
For a (contrived) example: the expectations around "experienced with Python and PostgreSQL" can be quite different if we are talking about a data analyst, or a web backend developer, or a DBA that will need to write PL/Python routinely. So the idea here is to have this "Skill Tree" where there are many different root nodes (Software Development, Management, UI/UX, System Administrations) and let these skills branch out from these root nodes to make the skill requirements as broad (Software Development -> Javascript) or specific (Software Development -> Javascript -> React -> React Native, or Operations -> Continuous Delivery -> Jenkins) as needed. This
There are some other ideas that I'm considering, like creating a database of issues in open source projects that could be used as part of the skill assessment, a more reliable "vouching" systems where professionals can look at listings and make a referral even when they are not working at the company. But to do any of that, first I'd like to grow the user base and get more feedback.
[0]: https://cupid.careers
[1]: https://activitypub.mushroomlabs.com
[2]: https://spectra.video/w/nibHzQxR26zQX1eYkFgygL?start=2m44s

value: Show HN: CareerCupid now (OkCupid for Jobs) now supports job listings

author: rglullis


value: sansreal

value: Check where your brand ranks with regard to llm optimization and visibility. I've setup a basic analysis view for now, would love to know what features folks specifically would like to see going ahead.

value: Show HN: Optimization for LLM App

author: sansreal

title: Show HN: Optimization for LLM App


value: pietz

value: Show HN: Tacho – CLI tool to benchmark LLM speeds across providers

author: pietz


value: UpbeatFix

value:
Last week I launched LaunchKit AWS, my solution for helping developers and indie hackers reduce the time they take to build and launch their SaaS products.
Features:
- Create account with email/password
- Magic link authentication
- SAML SSO integration
- Google OAuth sign-in
- GitHub OAuth sign-in
- Security headers implementation
- Create and delete teams
- Invite team members
- Manage member roles
- Update team settings
- Directory Sync (SCIM)
- Roles and permissions system
- E2E tests with Playwright
- Docker compose setup
- Prisma Studio integration
- TypeScript throughout
- Hot reload development
- Production-ready deployment
- Stripe payments integration
- Audit logs with Retraced
- Webhooks & Events with Svix
- Email notifications
- Internationalization (i18n)
- Avatar upload functionality
"How is this any different from ShipFast?"
ShipFast is a great tool for getting a simple SaaS to market. LaunchKit AWS is for when you know your market requires more. It's opinionated, feature-rich, and contains a foundation that makes the conscious choice to use AWS for its long-term flexibility and power.

value: Show HN: I built a enterprise level SaaS kit

author: UpbeatFix


value: -ertgl

value: This is a reusable library for tracing tapable hooks used within any system. The project's README contains a Mermaid graph visualization generated by tracing webpack internals. I'm sharing it for those who are curious.

value: Show HN: tapable-tracer Trace the connections and flows between tapable hooks

author: -ertgl


value: kamakaya

value:
Hi HN!
I created this simple two-person country guessing game to play with your friends. No login required.
You can either play a private match against a friend, or you can create or join a public match against a stranger.
My wife and I have been playing the game IRL during dinner time, so I decided to create an app to share it with more people. I have a few features that I still want to implement, and would love to hear your feedback as well!

value: Show HN: Country Guessing Game

author: kamakaya

title: Show HN: Country Guessing Game


value: Show HN: CDK Tutor – Interactive Courses to Learn CDK in Python


value: kurrupttt

value: Show HN: Guy built a TikTok alternative for studying

author: kurrupttt


value: Show HN: A little word puzzle game I made


value: Show HN: I made a Mac OS app at 17yo to turn voice emails


value: hmartin

value:
I always thought Google's Just a Line experiment[1] was crazy cool and recently wanted to revisit it. But it hadn't been updated in 7 years
So I upgraded all of the dependencies (including the latest version of Swift 5), added SwiftLint and SwiftFormat, and got it (mostly) working again!
Hope you have some fun with it- help welcome there's still more to do!
[1] https://experiments.withgoogle.com/justaline

value: Show HN: Just a Line: Resurrected

author: hmartin

title: Show HN: Just a Line: Resurrected


value: splatmesh

value:
Hello HN!
I'm the author of this toy project that combines the idea of live-edit Shadertoy scenes with the popular gaussian splatting, aka 3DGS. You can write a GLSL function that defines the splats and see it rendered in real-time. Your GLSL code isn't stored anywhere, but you can share it via URL.
P.S. I'm not a Spark developer. I'm just using their rendering engine.

value: Show HN: Procedurally generated 3DGS splats powered by Spark

author: splatmesh


value: SurceBeats

value: Show HN: I built a procedural universe in Python to explore simulation theory

author: SurceBeats


value: tboneskibs

value:
Hey HN,
I built Conduit to solve my own problem: I have a lot of long documents I want to read, but I retain better by listening.
Most tools for turning text into audio are clunky, slow, or require lots of manual formatting (copy/paste, upload to another platform, tweak settings, etc.). I wanted something that just worked.
So I built Conduit — a simple tool that turns large text files (ebooks, blog posts, PDFs, etc.) into listenable audio in seconds using realistic AI voices.
It’s currently just a waitlist and demo landing page, but I’d love early feedback:
- Does this scratch an itch for anyone else?
- What formats or features would make this useful to you?
- Any blockers that would keep you from using something like this?
Link: https://conduit-landing-page-git-master-tobys-projects-a638d...
Thanks in advance — happy to answer questions or share how it’s built.

value: Show HN: Conduit – Turn large text files into listenable audio

author: tboneskibs


value: molight

value: I built an MVP Roast tool — tell me what sucks about your MVP

value: Show HN: Tell me what sucks about your MVP

author: molight


value: jamsey

value:
Hey HN,
Just an indie dev here, who struggles to write formal emails when the occasion calls, such as payment reminders. I often find myself copy pasting from ClaudAI or ChatGPT. I figured being as I am a developer I could just make something to speed up the process, and a few of my mates asked to use it as well. I thought maybe this could help more people in trying to formalise their emails. Its region aware, so you will get correct context depending on what country or state you live in, and I am pretty proud of the results.
you get the first 5 for free, so you can try it out, and make sure that it will work for you. I really hope it can help some of you out there, as its helped me in the last couple of months. Just right click and covert ;)

value: Show HN: Legal Eyes – Turn casual payment requests into formal legal notices

author: jamsey


value: kuzej

value:
Hi HN,
I kept googling “2.5 bar to psi” during sensor tests, so I wrote a tiny webpage: https://bartopsi.xyz
It’s a single HTML/JS file—no frameworks. Pick an input unit and an output unit; the result appears instantly, and the formula is shown underneath for transparency. Supports bar, psi, kPa, atm, and more.
The code is open-source here: https://github.com/tutorial0/bar2psi
If you also juggle pressure units, feel free to bookmark, fork, or leave feedback.

value: Show HN: Lightweight Bar to Psi Converter

author: kuzej


value:
Hi HN,
I’ve been frustrated that I only find out how my representatives
voted when the news cycle decides to cover it, so I built a simple
script that texts me a digest instead.
What it is:
• Pick daily / weekly / bi-weekly / monthly
• Get one SMS listing each vote cast by your House rep + both Senators
• Messages include bill numbers, your rep’s “Yea/Nay/Present”, a one-sentence summary, and a link to congress.gov
How to try it:
1. Open the link (above)
2. Fill the Google Form with name + phone
3. Text “YES” back to opt in
(First month is free with code "PRODHUNT" so you can test it without paying carrier fees.)
Tech stack:
* Google Apps Script → polls Congress.gov REST + Senate XML
* Vercel edge function → handles inbound “YES/STOP” replies
* Stripe → recurring billing after the trial
* TextBelt → outbound SMS (cheapest I could find)
Everything is serverless; the sheet acts as the DB.
I’d like candid feedback on:
* edge-cases where the vote data is wrong or late
* UX: what’s confusing in the onboarding flow?
* thoughts on pricing (it’s \$1.99/mo because carriers charge for SMS)
No marketing fluff-just a hobby project that scratched an itch.
Happy to answer anything!
Previous discussion: none-this is the first release.
Thanks!

value: Show HN: “Text me when my Congress member votes” – daily alerts, (not a app)


value:
Hi HN,
A few months ago, I realized how hard it was to stay active on X (formerly Twitter) while juggling work and other responsibilities.
So I built Flowy — an AI-powered tool that helps you generate fresh tweet ideas, schedule posts, and stay consistent without burning out. It's powered by GPT-4o-mini and designed to support both individual creators and teams.
You can try it here: https://www.flowy.business/
If you want to explore the features without signing up, feel free to use this test account:
Email: starfish037fl@gmail.com
Password: starfish123
X account: https://x.com/starfish037
Would love your thoughts on the idea, feedback on the product, or suggestions for improvements.
Conner

value: Show HN: I built an AI-powered tool to generate and schedule tweets


value: RamboRogers

value: Instant browser benchmark for ai and leaderboard.

value: Show HN: Browser Based GPU Benchmarker

author: RamboRogers

title: Show HN: Browser Based GPU Benchmarker


value: sonderotis

value:
This was a hackathon project which my team worked on.
The software was made to detect dumpsites from satelitte images and to optimize routes of all bin pickup spots.<p>We lastly added the Raspberry pi3 to it. The raspberry pi was connected to an ultrasonic and mq2 gas sensor. These were meant to detect trash level and gas sensor to detect the presence of gas/methane so that the trash is separated on  pickup.

value: Show HN: Waste managment optimization with detectron2 and flask

author: sonderotis


value: baalimago

value: Show HN: Learning Rust with Neovim, Rust-Analyzer and LLMs

author: baalimago


value: jellyotsiro

value: Nia is a MCP server that provides additional context layer for any coding agent or IDE. Users use it to enrich agents by indexing external documentation and codebases through our system to feed it back to coding agent.

value: Show HN: 10x the output of your coding agent

author: jellyotsiro