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Hi HN - I’m Peter, here with Harry (devhawk), and we’re building DBOS Java, an open-source Java library for durable workflows, backed by Postgres.

https://github.com/dbos-inc/dbos-transact-java

Essentially, DBOS helps you write long-lived, reliable code that can survive failures, restarts, and crashes without losing state or duplicating work. As your workflows run, it checkpoints each step they take in a Postgres database. When a process stops (fails, restarts, or crashes), your program can recover from those checkpoints to restore its exact state and continue from where it left off, as if nothing happened.

In practice, this makes it easier to build reliable systems for use cases like AI agents, payments, data synchronization, or anything that takes hours, days, or weeks to complete. Rather than bolting on ad-hoc retry logic and database checkpoints, durable workflows give you one consistent model for ensuring your programs can recover from any failure from exactly where they left off.

This library contains all you need to add durable workflows to your program: there's no separate service or orchestrator or any external dependencies except Postgres. Because it's just a library, you can incrementally add it to your projects, and it works out of the box with frameworks like Spring. And because it's built on Postgres, it natively supports all the tooling you're familiar with (backups, GUIs, CLI tools) and works with any Postgres provider.

If you want to try it out, check out the quickstart:

https://docs.dbos.dev/quickstart?language=java

We'd love to hear what you think! We’ll be in the comments for the rest of the day to answer any questions.

I’m the CEO of AirGradient, where we build open-source air-quality monitors. Two months ago I decided to build our first native iOS app myself. I’ve been coding on the side for ~15 years, but had never touched Swift or SwiftUI. Still, I went from empty repo to App Store approval in exactly 60 days, working on it only on the side.

The app itself is a global PM2.5 map with detail views, charts, and integration with our open-source sensors -straightforward, but fully native with Swift and now live on both iOS and Android (native Kotlin version).

The interesting part for me was actually not so much the result, but on the process that I settled on. Agentic coding let me work in parallel with the AI: while it generated code, I could switch to CEO work - replying to emails, commenting on tickets, working on proposals, and thinking through strategic planning. The context switching wasn’t always easy, but having the coding agent on one virtual desktop and company work on another made the rhythm surprisingly smooth. It felt less like traditional "coding time" and more like supervising a very fast (junior) developer who never pauses. At times I felt super human when the AI got a complex feature implemented correctly in the first shot (and obviously there were a few times when it was extremely frustrating).

What helped tremendously was that I asked the AI to draft a full spec based on our existing web app, fed it screenshots and Figma mocks. Sometimes these specs were a few pages long for a simple feature including API, data models, localisations, UI mockups, and error handling. It produced consistent SwiftUI code far faster than any normal design-to-dev cycle. I still had to debug, make architectural decisions, and understand the tricky parts, but the heavy lifting moved to the tools.

This experience changed my view on a long-standing question: Should CEOs code? The historical answer was usually "not really." But with agentic coding, I believe the calculus shifts. Understanding what AI can and can’t do, how engineering workflows will change, and how non-engineers can now contribute directly is becoming strategically important. You only get that understanding by building something end-to-end, and I believe it's important that CEOs experience this themselves (the positives & the frustrations).

The bigger shift for me was realizing how this changes the entire software workflow. Designers can hand over mocks that agents turn directly into working components. PMs can produce detailed specs that generate real code instead of just guiding it. Even non-engineering teams can create small internal tools without blocking developers. Engineers don’t disappear—they move upward into architecture, debugging, constraints, and system-level reasoning. But for leadership to make good decisions about this future, it’s not enough to read about it. You have to feel the edges yourself: where the agents excel, where they fall apart, and what parts still demand deep human judgment.

So yes, I now think CEOs should code. Not permanently - only a few hours a week. Not to ship production code forever, but to understand the new reality their teams will be working in, and how to support them in this new work environment.

I’m sharing this partly to hear how others on HN approach the question of whether CEOs or technical leaders should still code. Has getting hands-on with AI tools changed your perspective on leadership, team structure, or strategy?

Happy to answer questions and compare notes.

Here are the apps: Apple App Store: https://apps.apple.com/us/app/airgradient-map/id6752292182 Android Play Store: https://play.google.com/store/apps/details?id=com.agmap.andr...

(Keep in mind this is version 1, so lots of improvements will come in the coming weeks and months)

Hi HN,

I made a tiny tool called YAML Validator that checks your YAML files with one Docker command — no installs, no setup, no excuses.

It does:

- Syntax checks

- yamllint linting

- checkov security scanning

- All in one lightweight, zero-config container

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How to use:

docker run -v "$(pwd):/data" pooyanazad/yaml-checker <yaml-file>

Optional alias (for .bashrc / .zshrc):

alias ytest='docker run -v "$(pwd):/data" pooyanazad/yaml-checker'

Then simply call:

ytest sample.yaml

YAML powers CI/CD, configs, infra ,and breaking it is too easy. This aims to catch syntax, style, and security issues early with minimal friction.

I’d love feedback, ideas, or edge cases to test.

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GitHub: https://github.com/pooyanazad/YAML-validator

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Thanks for reading!

Pooyan

The AI Bubble Monitor is an analytical tool designed to track and visualize indicators of potential market bubbles in AI-related sectors. It aggregates multiple data sources and metrics to produce a composite "AI Bubble Score" that ranges from 0 to 100. The tool breaks down the overall score into five sub-indices: Valuation, Capital Flows, Adoption vs Fundamentals, Sentiment & Hype, and Systemic Risk. Each sub-index provides insight into different aspects of market behavior and potential overvaluation.

The article discusses the importance of credit and how Quantra's platform can help individuals and businesses manage their credit effectively. It outlines Quantra's features, including credit monitoring, score analysis, and personalized recommendations, to help users improve their credit health and make informed financial decisions.

Generative art has been a long-standing interest of mine. I’ve seen a lot over the years — but this generation was absolutely pure.

Gerbil is an open source app that I've been working on for the last couple of months. The development now is largely done and I'm unlikely to add anymore major features. Instead I'm focusing on any bug fixes, small QoL features and dependency upgrades.

Under the hood it runs llama.cpp (via koboldcpp) backends and allows easy integration with the popular modern frontends like Open WebUI, SillyTavern, ComfyUI, StableUI (built-in) and KoboldAI Lite (built-in).

Why did I create this? I wanted an all-in-one solution for simple text and image-gen local LLMs. I got fed up with needing to manage multiple tools for the various LLM backends and frontends. In addition, as a Linux Wayland user I needed something that would work and look great on my system.

Hey HN, this is David from Aluna (YC S24). We work with diagnostic labs to build datasets and evals for oncology tasks.

I wanted to share a simple RL environment I built that gave frontier LLMs a set of tools that lets it zoom and pan across a digitized pathology slide to find the relevant regions to make a diagnosis. Here are some videos of the LLM performing diagnosis on a few slides:

(https://www.youtube.com/watch?v=k7ixTWswT5c): traces of an LLM choosing different regions to view before making a diagnosis on a case of small-cell carcinoma of the lung

(https://youtube.com/watch?v=0cMbqLnKkGU): traces of an LLM choosing different regions to view before making a diagnosis on a case of benign fibroadenoma of the breast

Why I built this:

Pathology slides are the backbone of modern cancer diagnosis. Tissue from a biopsy is sliced, stained, and mounted on glass for a pathologist to examine abnormalities.

Today, many of these slides are digitized into whole-slide images (WSIs)in TIF or SVS format and are several gigabytes in size.

While there exists several pathology-focused AI models, I was curious to test whether frontier LLMs can perform well on pathology-based tasks. The main challenge is that WSIs are too large to fit into an LLM’s context window. The standard workaround, splitting them into thousands of smaller tiles, is inefficient for large frontier LLMs.

Inspired by how pathologists zoom and pan under a microscope, I built a set of tools that let LLMs control magnification and coordinates, viewing small regions at a time and deciding where to look next.

This ended up resulting in some interesting behaviors, and actually seemed to yield pretty good results with prompt engineering:

- GPT 5: explored up to ~30 regions before deciding (concurred with an expert pathologist on 4 out of 6 cancer subtyping tasks and 3 out of 5 IHC scoring tasks)

- Claude 4.5: Typically used 10–15 views but similar accuracy as GPT-5 (concurred with the pathologist on 3 out of 6 cancer subtyping tasks and 4 out of 5 IHC scoring tasks)

- Smaller models (GPT 4o, Claude 3.5 Haiku): examined ~8 frames and were less accurate overall (1 out of 6 cancer subtytping tasks and 1 out of 5 IHC scoring tasks)

Obviously, this was a small sample set, so we are working on creating a larger benchmark suite with more cases and types of tasks, but I thought this was cool that it even worked so I wanted to share with HN!

My cofounder and I run a startup in oncology, where we handle cancer genomics data. It occurred to me that, thanks to a recent complexity theory result, there's a clever way to run bioinformatics algorithms using far less RAM. I built this Rust engine for running whole-genome workloads in under 100MB of RAM. Runtime is a little longer as a result - O(TlogT) instead of O(T). But it should enable whole-genome analytics on consumer-grade hardware.

Hey HN, I built Logosive because I want to see certain debates between my favorite thinkers (especially in health/wellness, tech, and public policy), but there's no way for regular people to make these happen.

With Logosive, you propose a debate topic and debaters. We then handle outreach, ticket sales, and logistics. After the debate, ticket revenue is split between everyone involved, including the person that proposed the debate, the debaters, and the host.

Logosive is built with Django, htmx, and Alpine.js. Claude generates the debate launch pages, including suggesting debaters or debate topics, all from a single prompt (but the debates happen between real debaters).

I’m now looking for help launching new debates, so if you have any topics or people you really want to see debate, please submit them at https://logosive.com.

Thanks!

Hi HN,

We built an AI agent for data analysts that turns the soul crushing spreadsheet & BI tool grind into a fast, verifiable and joyful experience. Early users reported going from hours to minutes on common real-world data wrangling tasks.

It's much smarter than an Excel copilot: immutable data steps, a DAG of SQL views, and DuckDB for instant crunching over millions of rows. Our early agent prototype ranked #1 on the Spider2-DBT bench. https://spider2-sql.github.io

Try it out and we'd love your feedback!

Thanks, Di Wu & the Shadowfax team

P.S. Shadowfax is Gandalf's horse from LOTR. There's a hidden easter egg site with 3 different triggers, see if you can find them.

Hey HN,

I recently built whatstype.org , a free personality test website that helps people explore their thinking, communication, and relationship patterns.

Unlike most MBTI-style sites that only give you a short label, Whatstype digs deeper:

The test adapts to your responses dynamically

Results are structured around reasoning style, emotional pattern, and social interaction

Each of the 16 personality types includes detailed analysis, strengths, challenges, and real-life advice

No login, no tracking — everything runs client-side

I built it because I was frustrated with the typical “clickbait MBTI quizzes” that don’t respect users’ time or data. Whatstype focuses on clarity, accuracy, and clean UX rather than virality.

Tech stack:

Next.js 14 + TypeScript

TailwindCSS for UI

Structured JSON content for multi-language results

Fully static export, hosted on Cloudflare Pages

If you’re into psychology, data visualization, or just enjoy introspective tools, I’d love your feedback — especially on:

Question design (is it too long / too short?)

Result presentation clarity

Ideas for making the insights more actionable

You can try it here: https://whatstype.org

Thanks for reading!

Hi HN,

I built a simple tool to solve a problem I've faced as a developer and freelancer: how can you definitively prove a file (like code, a contract, or a design) existed at a specific time?

It's called Akashi Notari, and it’s a simple utility for creating an on-chain "Proof of Existence." It lets you anchor any file's cryptographic hash on the blockchain (supports Base, Ethereum, Optimism). And costs less than a dollar.

The main focus is privacy and simplicity:

- *100% Private:* Hashing (SHA-256) is done entirely in your browser. The file never leaves your computer. Only the calculated hash is sent to the blockchain. - *Fast:* The whole process, from file drag-and-drop to a confirmed transaction, takes about 60 seconds. - *Verifiable:* As soon as the transaction confirms, you get a PDF certificate with the hash, timestamp, and a direct link to the on-chain transaction for verification.

I built this as a "poor man's copyright" or a simple notarization tool for:

- *Freelancers:* Proving when a deliverable was completed. - *Creators:* Timestamping IP (art, music, manuscripts) before sharing it. - *Anyone:* Timestamping contracts or records without the cost and hassle of traditional notaries. Maybe some commit-reveal scenarios.

The workflow is just:

1. Drag/drop your file. 2. Connect a wallet. 3. Confirm the transaction. 4. Download your PDF certificate. 5. Prove anytime in the future that your file existed using simple instructions in PDF

You can try it out here: https://akashi-notari.com/ You can also retrieve/verify existing certificates here: [https://akashi-notari.com/certificate-retrieval](https://www.google.com/search?q=https://akashi-notari.com/ce...)

I'd love to hear what the HN community thinks!

Hey HN, I'm Marcel from Tusk. We’re launching Tusk Drift, an open source tool that generates a full API test suite by recording and replaying live traffic.

How it works:

1. Records traces from live traffic (what gets captured)

2. Replays traces as API tests with mocked responses (how replay works)

3. Detects deviations between actual vs. expected output (what you get)

Unlike traditional mocking libraries, which require you to manually emulate how dependencies behave, Tusk Drift automatically records what these dependencies respond with based on actual user behavior and maintains recordings over time. The reason we built this is because of painful past experiences with brittle API test suites and regressions that would only be caught in prod.

Our SDK instruments your Node service, similar to OpenTelemetry. It captures all inbound requests and outbound calls like database queries, HTTP requests, and auth token generation. When Drift is triggered, it replays the inbound API call while intercepting outbound requests and serving them from recorded data. Drift’s tests are therefore idempotent, side-effect free, and fast (typically <100 ms per test). Think of it as a unit test but for your API.

Our Cloud platform does the following automatically:

- Updates the test suite of recorded traces to maintain freshness

- Matches relevant Drift tests to your PR’s changes when running tests in CI

- Surfaces unintended deviations, does root cause analysis, and suggests code fixes

We’re excited to see this use case finally unlocked. The release of Claude Sonnet 4.5 and similar coding models have made it possible to go from failing test to root cause reliably. Also, the ability to do accurate test matching and deviation classification means running a tool like this in CI no longer contributes to poor DevEx (imagine the time otherwise spent reviewing test results).

Limitations:

- You can specify PII redaction rules but there is no default mode for this at the moment. I recommend first enabling Drift on dev/staging, adding transforms (https://docs.usetusk.ai/api-tests/pii-redaction/basic-concep...), and monitoring for a week before enabling on prod.

- Expect a 1-2% throughput overhead. Transforms result in a 1.0% increase in tail latency when a small number of transforms are registered; its impact scales linearly with the number of transforms registered.

- Currently only supports Node backends. Python SDK is coming next.

- Instrumentation limited to the following packages (more to come): https://github.com/Use-Tusk/drift-node-sdk?tab=readme-ov-fil...

Let me know if you have questions or feedback.

Demo repo: https://github.com/Use-Tusk/drift-node-demo

Hi everyone, we are excited to share with you our new release of Data Formulator. Starting from a dataset, you can communicate with AI agents with UI + natural language to explore data and create visualizations to discover new insights. Here's a demo video of the experience: https://github.com/microsoft/data-formulator/releases/tag/0.....

This is a build-up from our release a year ago (https://news.ycombinator.com/item?id=41907719). We spent a year exploring how to blend agent mode with interactions to allow you more easily "vibe" with your data but still keeping in control. We don't think the future of data analysis is just "agent to do all for you from a high-level prompt" --- you should still be able to drive the open-ended exploration; but we also don't want you to do everything step-by-step. Thus we worked on this "interactive agent mode" for data analysis with some UI innovations.

Our new demo features:

* We want to let you import (almost) any data easily to get started exploration — either it's a screenshot of a web table, an unnormalized excel table, table in a chunk of text, a csv file, or a table in database, you should be able to load into the tool easily with a little bit of AI assistance.

* We want you to easily choose between agent mode (more automation) vs interactive mode (more fine-grained control) yourself as you explore data. We designed an interface of "data threads": both your and agents' explorations are organized as threads so you can jump into any point to decide how you want to follow-up or revise using UI + NL instruction to provide fine-grained control.

* The results should be easily interpretable. Data Formulator now presents "concept" behind the code generated by AI agents alongside code/explanation/data. Plus, you can compose a report easily based on your visualizations to share insights.

We are sharing the online demo at https://data-formulator.ai/ for you to try! If you want more involvement and customization, checkout our source code https://github.com/microsoft/data-formulator and let's build something together as a community!

Hey HN, Joel here, co-founder of Venturu.

Imagine trying to buy a house before Zillow. That’s what buying a local business is like today. It's a massive market, but it's completely fragmented and stuck in the 90s.

My co-founder, Luis, discovered this firsthand by knocking on doors to buy six of his own businesses. I saw it at industry conferences, where at 29, I’m usually the youngest person in the room. The system is built on gatekept information and a wall of fees designed to keep people out.

For a small business owner, it starts with a gut punch: you have to pay thousands of dollars just to get an idea of what your life's work is worth. Then, you face thousands more in listing fees just to get it seen on an outdated platform.

This broken model forces brokers to be gatekeepers. The high costs mean they can only list a fraction of their clients' businesses, hiding the rest on thousands of separate, clunky websites.

We’re trying to fix this by building the single, open, and free platform this market needs. We got rid of the scary upfront fees by offering free, instant valuations, and unlocked the hidden market by making all listings free.

It’s one place for owners, buyers, and brokers to finally connect efficiently.

It seems to be working. We’ve welcomed over 1,300 brokers who have listed 3,800+ businesses across all 50 states.

It's still early days, but our goal is to build this into the definitive marketplace for local businesses, creating the first real source of truth for valuations and making the entire process, from discovery to closing, more straightforward.

We’re building in the open and would love your feedback. Ask us anything.

I tagged all comments from "What Are You Working On?" (like https://news.ycombinator.com/item?id=45561428) posts and built a simple SvelteKit website, hope it's helpful to find people with similar projects. I'm also thinking of adding some analysis of project types over time to see changes in tech

Hey HN,

We built a wireless, low-profile macropad with a display called the Creavi Macropad. It lasts at least 1 month on a single charge. We also put together a browser-based tool that lets you update macros in real time and even push OTA updates over BLE. Since we're software engineers by day, we had to figure out the hardware, mechanics, and industrial design as we went (and somehow make it all work together). This post covers the build process, and the final result.

Hope you enjoy!

Hi all, I’ve been working on this project for a while but haven't shared it properly on Hacker News.

It is a casual gaming platform focused on simple multiplayer games that can be played in person with a central screen (like a TV) or remotely via video chat. You can also play on your smart Android based TVs via the app: https://play.google.com/store/apps/details?id=com.gametje (it was just released recently so could be buggy). It is also available directly in Discord: https://discord.com/discovery/applications/12153230008666071... as an embedded activity.

It is playable in 9 languages and doesn’t require any downloads. Most games revolve around creativity in some shape or form. They can be played by just about anyone whether or not you consider yourself a “gamer”. If you can text, you can play these games.

Why did I create it?

Some of you may see the resemblance to Jackbox games. I have been a huge fan of them for 10+ years and enjoyed playing their games a lot. However, I found their support for other languages a bit lacking. While living in the Netherlands, I have encountered quite a few non-native English speakers and wanted to help them have a similar experience. Jackbox also has some fragmentation issues between app stores. I own their games on PC and PS4 but I can’t share a “license” between them. They also come out with a pack every year with 5 games. You never know if the game(s) will be fun, or if you should try to buy a previous pack with the one killer party game in it.

I designed Gametje with these issues in mind. It is playable in multiple languages with more being added regularly (feel free to request one). You can play it from any device with a web browser. There is no need to install it via Steam or a game console. All games are available in one place with no “packs” to buy.

What’s up with the name?

I have been living in the Netherlands for some years and part of my original motivation stems from wanting to give my friends here a game to play in their native language. It's way easier to be witty/funny in your mother tongue after all! Because of that, I wanted to incorporate something Dutch into the site's name. The suffix ‘-tje’ is one of the diminutive endings in Dutch and is meant to soften a word or make it "smaller". Game + tje = Gametje, or a little game. I have been informed by native Dutch speakers that it should have been ‘Gamepje’ to be "correct" but I liked the way Gametje sounded better.

Where can I try it?

Go here: https://gametje.com/

You can test it out as a guest without signing up in order to get a feel for the games. Clicking into each game gives a short explanation and a small example of the gameplay. When creating a game room, you can choose to host via a central screen, host and play from a single device (like a phone) or cast the main screen to a Chromecast. There is also an Android TV app available that was just recently released: https://play.google.com/store/apps/details?id=com.gametje

After creating a game room, you can join from another browser window or device. You can also add AI players if you want to try it out on your own, although it is a lot more fun with real people. I also created a discord channel: https://discord.gg/7jrftHuHp9 where you can find other users to play with. If you sign up for an account, you can opt-in as an alpha tester and see the new games as they are developed. It’ll also keep track of all your previous games and make sure not to duplicate content. You can review previous games as well and relish in your past victories.

What am I looking for?

I am interested in feedback about the whole concept and also the gameplay. Is it fun? What could be improved? Interested in helping out? Let me know!

Happy to share the more technical details as well for those that are interested. You can also read a bit about the platform and games in my blog:

https://blog.gametje.com/

Thanks!

I wanted to query my own chat history but the JSON exports were a mess to work with. Built a small parser that turns them into clean SQL databases. Parsed 70k+ messages across multiple models. Useful for analyzing chat history, building a personal knowledge base, or archiving conversations. Simple CLI, open source.

Hey all. I built ShellDash, an interactive server admin dashboard with shell scripting and an appealing globe UI.

https://shelldash.com

The goal is to provide a global monitoring view of your servers, with shell script access, in a way that feels natural and productive, plus a minimal and appealing UI/UX.

The technology is fairly interesting. This being a browser app, I built a Go WASM SSH client running in the browser, proxied through my server WebSocket endpoints. This means I can provide you a Web UI to access your servers via SSH, without ever needing to see your credentials. I only see secured packets like OpenSSH sends over the open internet. Inspired by https://ssheasy.com/

Whether you have one server and periodically run a few common commands, or administering many scattered geographically, I hope ShellDash can make your experience more productive and fun.

I struggle with time blindness and kept missing client Zoom calls. MacOS notification banners appear for 5 seconds and vanish...my brain can't hold onto them. I spent 2 months building a solution.

What it is: Chime shows full-screen alerts that physically interrupt whatever you're doing. It's impossible to miss.

Technical details: - Built entirely in Swift/SwiftUI using Cursor. - Uses EventKit for Calendar + Reminders integration - Todoist REST API v2 for task sync - All data stays local—no cloud sync

How it works: - Syncs from Calendar, Apple Reminders, and Todoist every 1-30 min (This is customisable) - Extracts meeting links from meetings (30+ platforms: Zoom, Teams, Meet, Webex, etc.) - Schedules Timer-based full screen alerts with customizable timing - Sound rotation system to prevent habituation

The insight: Most accessibility focuses on making things "clearer" or "simpler." Neurodivergent brains need "impossible to ignore." Subtle equals invisible. I've been using it for a few weeks and went from missing chunk of meetings to zero.

Try it: 14-day free trial on Mac App Store. No signup required, just download and grant Calendar permissions. https://apps.apple.com/us/app/chime-remember-everything/id67...

Happy to discuss: - Building macOS apps with AI assistance - EventKit's quirks (hourly recurrence workaround, full screen alert implementation, etc) - Designing for neurodivergent users

Hephaestus is an open-source framework that simplifies the development of robotic systems. It provides a modular and scalable architecture, enabling seamless integration of various sensors, actuators, and computational units, making it easier to build and deploy complex robotic applications.

TexOCR is a free and open-source optical character recognition (OCR) tool that allows users to extract text from images. The article provides an overview of the tool's features, including its ability to handle a variety of image formats and its support for multiple languages.

I have a couple young kids and they always want to play mad libs. I only really found ones riddled with ads online so I made my own here. I'm a backend guy so go easy on my UI skills. Definitely used Cursor for help on the UI part of it. Anyway hope you play this with your kids too!

The article discusses the creation of YaraDB, an open-source database that uses the Yara malware detection language to store and query security-related data. The project aims to provide a flexible and scalable solution for security professionals to manage and analyze threat intelligence data.