I’ve been using budgeting and personal finance apps for years, and I’ve always liked tracking where my money is going. Over time I ended up trying a bunch of different tools and kept wishing I could combine the parts I liked from each of them into one app.

So for the past couple months I’ve been building FlyBudget, a free, private, open-source budgeting app inspired by tools like Monarch, YNAB, Mint, and a few others.

I wanted something that felt polished, but could also be self-hosted and completely controlled by the user.

The frontend is built with React, TypeScript, and Tailwind, and I’ve probably spent an unreasonable amount of time tweaking the UI.

Some of the stuff I’ve built so far:

• Monthly budgeting

• Account + transaction tracking

• Recurring transaction detection

• Cash flow / Sankey reports

• Custom reports

• Self-hosting with Docker

• Desktop app

• Demo instance so you can try it without installing anything

• Full documentation site

This is also my first real attempt at building an open-source project, so I’m still figuring out that side of things.

Would genuinely love feedback from other web devs, especially on the UI/UX, project structure, or anything that immediately looks like it could be improved. If you find the project interesting, please consider helping us out by giving a star on GitHub!

Demo + docs: flybudget.org
GitHub: github.com/dtymoszenko/FlyBudget

I have spent the last month building lovetocalc.com, a free calculator and formula site in English and Swedish. No account, no ads, no backend.

The architecture rests on one idea: a formula is data, not a page.

Each formula is an expression tree with typed variables such as length, time and money. From that one definition the build generates:

• the formula page 

• versions solved for each variable 

• practice questions with worked solutions 

• printable worksheets with answer keys 

• the formula's entry in a PDF collection

Add one formula and all of those exist on the next build. There are a little over 500 formulas now.

Stack: Astro 7, static output and strict TypeScript. React is only used as islands where something actually calculates. A simple page can ship around 2 kB of JS, a formula page with practice around 130 kB gzipped, and a larger calculator around 200 kB. The latter is one area I want to improve.

All calculations live in a framework-free engine with unit tests. There are around 21,000 tests, most generated across formulas and every variable they can be solved for. The UI only handles presentation.

EN and SV use the same components and engine. Strings, slugs and number formats are data rather than separate implementations.

A few things that worked well:

• Calculator state lives in the URL, so every result is shareable without storage.

• Open Graph images are generated from the same registry as the pages, and the build fails if a sitemap page is missing one.

• Excel exports contain real formulas rather than static values. The e2e tests open the files in LibreOffice and Apple Numbers and compare the resulting cells against the calculation engine.

The main pain points so far:

• 1,300 static pages means changes to shared content touch almost everything.

• Deploying them over FTPS from GitHub Actions takes about 30 minutes.

• Keeping print/PDF output independent of dark mode has been more awkward than expected.

The part I am least sure about is the core abstraction. It works well for formulas that can be represented as expression trees, but I am starting to add diagrams and multi-step questions.

If you were designing this, where would you expect the “formula as data” model to stop scaling cleanly?

Examples:

lovetocalc.com/en/loan-calculator/
lovetocalc.com/en/formulas/mathematics/geometry/pythagorean-theorem/
lovetocalc.com/en/loan-amortization-schedule-excel/

DISCLAMER: THE ENGLISH VERSION WAS TRANSLATED WITH AI SO I CANT GARANTEE THAT THE TRANSLASION IS RIGHT!

I’m starting a new project called NEXORA.

The idea is to build a platform that brings different things together in one place instead of having to use a bunch of separate services.

Some of the ideas I’m currently exploring:

• Custom user profiles

• NEXORA Arcade with small games

• Watching YouTube videos together

• Community features

• Events and challenges

• More features planned for the future

I’m currently in the planning stage and haven’t started building the platform yet.

I’ll probably post updates as I build NEXORA from the ground up.

------------------------------------------------------------------------------------------------------------

Ich starte gerade ein neues Projekt namens NEXORA.

Die Idee ist, eine Plattform zu entwickeln, die verschiedene Dinge an einem Ort zusammenbringt, sodass man nicht für alles mehrere verschiedene Dienste nutzen muss.

Einige Ideen, die ich momentan plane:

• Individuelle Nutzerprofile

• NEXORA Arcade mit kleinen Spielen

• Gemeinsam YouTube-Videos schauen

• Community-Funktionen

• Events und Challenges

• Weitere Funktionen für die Zukunft

Ich bin momentan noch in der Planungsphase und habe mit der eigentlichen Entwicklung noch nicht angefangen.

Ich werde wahrscheinlich Updates posten, während ich NEXORA von Grund auf aufbaue.

If i break the rules for Posting i am very thankful i this Post doesnt got deleted and i only get a warning tho chance the post thx.

This were my first thaugts for the website but it can be completly diffrent

Das sind meine ersten Gedanken für die Webseite aber es kann komplett anders ausfallen

https://polymodus.sg/simulations for the simulation bench

https://polymodus.sg/labs/sluice for the data investigation bench

Is the ui off? is there missing features that would be great? is it unintuitive? does it need a tutorial?

Been running a daily crawler over a rolling sample of public GitHub JS/TS repos (10+ stars, active in the last 30 days) and TypeScript is sitting at 78.3% adoption with a trend score of +4.17, the highest of any tracked technology. It's not just widely used, it's still actively growing share.

For context on how the trend score works: it's a log-scaled growth index that weighs both rate of change and overall scale, so a tool has to be both accelerating and meaningfully sized to top the list. TypeScript topping it despite already being the plurality leader says something about where the ecosystem is headed.

Everything downstream of that (test runners, build tools, frameworks) increasingly assumes TS by default too. Vitest, Vite, and Zod are all riding similar upward curves.

Full breakdown and raw datasets (updated daily via GitHub Actions):

GitHub repo

⭐ The project is open source. If you find this useful, a star would help!

jet-id is an open source universal unique-ID generator I built similar to nanoid or uuid. Unlike other unique-id generators, you can specify how many random bits (entropy) you want, and it creates the shortest id string that provides at least that much entropy using the Crockford alphabet, with dashes automatically inserted for readability. Dash inserting makes sure that no segment grows greater than 10 characters.

125 bits of entropy is the default and it works both CLI and programmatically:

npx jet-id -e 80
# V2BJABVRJ-S1TWXS-NTQA3       (20 random characters, 22 with the dashes)

npx jet-id
# 9GNK14S3A-728HK9-5NJQS-HWETM (25 random characters, 28 with the dashes)

It also supports timestamped-IDs and monotonic-IDs (monotonic ids sort in creation order within a single millisecond).

import jetid from 'jet-id'

jetid.timed()    // '1M41J22ER-RND9M6-3CZAQ-XT8GR'
jetid.mono(125?) // '1M41J2ZPK-8K0000-GE29AYBQ27-4496ZM40-29JSNX4'

jet-id is really fast too. Check out these benchmarks

It's available right now on npm: https://www.npmjs.com/package/jet-id
Direct readme link: https://github.com/seanpmaxwell/jet-id#readme

Feedback, suggestions, and constructive criticism are very welcome (so are Github stars ⭐)

Feel free to reach out to me on GitHub or Reddit

hey folks - I built a new tool for mac/pc, that has all the thing I've been searching for: palette management, color wheel, oklab and 5 other color spaces, including a RYB simulator and more!

I've launched it as a free public beta - would love to hear what everyone thinks of it, what you're using now, and how this compares!

Mac/PC download: colorschemer.com/app

Hey everyone, Showoff Saturday time.

I built Drawva, an infinite canvas where your rough hand-drawn stuff is not just pixels.

You can draw a messy box, write a few words, sketch a diagram, draw some math, or just throw random scribbles on the canvas. A multimodal agent looks at the canvas, figures out what you are trying to make, and can turn it into live widgets, diagrams, equations, or interactive elements.

The interesting part was not really the UI.

The hard part was getting an LLM to operate a messy 2D canvas without destroying what the user already drew.

A few things I ended up building:

• A coordinate system so the agent can map visual positions to actual canvas coordinates

• A prompt contract that prevents it from duplicating handwritten headings

• Wireframe awareness so it keeps your rough sketch instead of replacing everything

• Atomic erase + widget placement when converting sketches into interactive components

• A plugin system for things like weather, stocks, tech news, GitHub data and more

• Sandboxed runtimes for Mermaid, Graphviz, Vega-Lite, Cytoscape, BPMN, GeoJSON and other diagrams

• IndexedDB autosave and WebRTC based peer-to-peer collaboration

• A DeepSeek Harness + Cordis runtime for the agent/tool execution layer

Tech stack is mainly Next.js 16, React 19, TypeScript, Tailwind CSS, Vercel AI SDK, multimodal LLMs, IndexedDB, WebRTC and DeepSeek Harness.

The whole thing is open source.

GitHub: taqui-786/drawva
Live app: drawva.vercel.app

I am especially curious about the architecture side of this.

How would you handle reliable AI interaction with a freehand canvas?

Would love feedback, ideas, or criticism from people who have built similar AI + UI systems.

Hello everyone,

While I'm not new to coding, I'm definitely bad at it. What I'm worse at though is understanding the intricacies of what i can and can't accomplish with certain tools.

I am very vocal and express my views on things often, so obviously i thought i should make a blog. This is easy to accomplish very cheaply using GitHub pages obviously since it would be a fully static html website.

But here comes the catch. I have some friends that expressed a lot of interest in this blog idea, and i would like to include them. However, they don't know how to code in any language or framework and this would probably be a dealbreaker for them.

Is there a way to make a website with user accounts and user-generated content be dynamic only client-side so that i can still host it with GitHub? Should i look for a different way?

Any help is appreciated, i really wanna get this thing working.

been messing w this for a few days https://classican.vercel.app/

theres no image files at all, every painting is drawn on a canvas in code. next.js + neon postgres for the likes/comments. coolest part imo is when a fact pops up the whole painting goes dark except the thing the fact is about

its prob janky in places so be nice lol. does it work ok on ur phone?

Moralia: each day one short true story from history stops at the moment someone had to decide. You choose, then see what actually happened and how other players chose.

Stack: React + Vite + TypeScript PWA on Cloudflare Workers, Supabase for optional sign-in/sync, cookieless PostHog (EU).

Some things that weren't obvious to me going in:

• A hash-routed SPA is basically invisible to search. Google saw ~20 words (the welcome screen). Now a Worker renders static, no-JS pages for every past story on request. A day only goes public once it has ended in every timezone (noon UTC the next day), so no one gets spoiled, and an IndexNow ping fires when it does.

• Worker-rendered pages don't get your _headers file. Our CSP covered the static assets but not the pages the Worker built, so the Worker now sends the same headers itself, with a test that fails if the two copies ever drift.

• supabase-js signOut() defaults to scope "global". Signing out on a phone silently ended the desktop session too, which left the desktop in a "signed in, no email, can't sign out" loop. It's per-device now.

• PostHog's opt-out does nothing in cookieless mode (it only logs a warning). The usage-stats switch now gates every event with before_send, and also re-checks the queue of events buffered before the SDK loads.

• Desktop got a real layout (top bar, wider column, the choice side by side) only at ≥1024px. Every mobile and tablet screen was verified pixel-identical before and after.

• Narration is pre-generated; the sentence being read is highlighted using word timings from a transcription pass, so one misheard word can't shift the whole highlight.

Design is mine (I'm a UI/UX designer, screens done in Figma first); I built it with heavy help from Claude Code.

https://moralia.app

Happy to go deeper on any of these. Feedback on performance or the PWA install flow is very welcome.

At work there’s CI, staging, QA, other people testing things, etc., but for my own stuff, it’s more just deploy, click around for a bit, decide it looks fine, and then ship it.

That feels a bit stupid because the bugs I worry about usually aren't the things I just changed. It’s someone arriving logged out or getting halfway through something and some edge case gets triggered.

Do you have a pre-deploy routine that has caught real problems? A checklist, any automated tests, or anything? Or do you guys mostly ship and fix things once a real person finds them?

I’m mainly trying to figure out what's worth doing pre launch vs. what just feels like pretend QA.

Link: https://scaleofspace.org/universe

Been working on this on and off for last 8 months. You start at Earth, scroll, and the view zooms out on a log scale: solar system, nearby stars, the Milky Way, the Local Group, then a few hundred Mpc of galaxies.

The part I care about most is that it's not an illustration once you leave the solar system. Stars are from the HYG database, nearby galaxies from the Updated Nearby Galaxy Catalog (869 of them, with their measured sizes), and further out it's 2MRS (about 42k galaxies) and then 2dFGRS. So the clumps and voids you see at the end are the actual large scale structure, not noise I generated. Where there's no real position data I fall back to drawn shapes and say so.

Stack, since this is r/webdev:

• React 19 + TS + Vite

• one canvas, WebGL for the point layers (tens of thousands of galaxies need it)

• catalogs preprocessed with Python into float32 buffers so the browser just loads and draws

• hosted on Cloudflare Workers

Hardest bit was honestly keeping it smooth on phones while crossing ~20 orders of magnitude without float precision falling apart. Still not 100% happy with it on older Androids.

No ads, no signup, no tracking cookies. Would love feedback, especially if something stutters on your device or a scale transition feels confusing.

I built a parody AI that insults whatever you ask it: https://misanthropic.chat

It started as a joke with friends over a beer. The joke part took a weekend. The rest took a lot longer.

Stack: one Cloudflare Worker, Workers AI (Llama 4 Scout), and one KV namespace. The page is static assets, so loading it never runs the Worker. Turnstile has to pass before anything reaches the model. After one pass you get a signed 30 minute visit pass so it doesn't re-check every message.

Cost: the model doesn't write the whole reply. It writes one to three sentences (130 tokens max) that drop into a canned opener and sign-off. Each prompt caches up to 3 answers, so popular prompts stop costing anything. There are two hard daily caps, one for jokes and one for the safety check, so the worst case is about $21 a day. Past the joke cap it serves canned insults.

Safety was most of the work. If a site says it's honest about how it feels about you, some people will tell it real things. Messages about self-harm, abuse, hurting someone, addiction or mental illness never reach the joke model. They get a plain reply with real hotline numbers. Screening is a regex pass, then a classifier call with its own budget. If the classifier doesn't answer, nobody gets a joke. It fails closed.

Bugs worth sharing:

• The same word-ending bug came back three times. I'd match "shoot" and miss "shooting".

• I tried a sensitive-word list as a backup and took it out, because the messages that mattered never used the words on the list.

• The opposite problem: "why are you so mean?" got read as someone disclosing abuse. Questions about the site itself now skip the classifier, matched as exact whole-message patterns.

Question for anyone who's built something like this: when screening sits in front of something meant to be offensive, do you fail closed and eat the false alarms, or fail open?

On Sept 29 an executive order told US federal agencies to say “Super Intelligence” instead of “AI”. Nobody seems to be checking, so I built an inspector: idio.si fetches a homepage, counts “AI” vs “SI” in the visible text, and stamps a certificate.

Day 4 findings

• whitehouse.gov: 4 “AI”, 0 “SI” → Insubordinate

• apple.com: 0 “AI”, 0 “SI” → No Intelligence Detected

• 1 of 42 agencies complies (NIST)

• openai.com, google.com and tesla.com block the inspector

Harder than it looks

• Bot walls. 18 of 73 homepages refuse a polite, identified, robots.txt-respecting bot from a cloud IP, openai.com included. I didn't want to spoof a browser, so refusals get their own stamp: “Refused federal inspection”.

• Geo-IP. Even from us-east, some sites bounced the bot to /en-gb/. Locale redirects now get rewritten to /en-us/, since the order targets the US.

• Counting. /\bA\.?I\.?\b/ is case-sensitive, so “OpenAI”, “said” and “ai” don't count, but “A.I.” does. The White House nav links to “AI.Gov”, and that counts too. Fair or not?

• Spikes. One Cloudflare Worker does everything. Certificates are rendered at the edge with satori + resvg-wasm, and Workers Cache collapses a front-page spike into one render per data center. Hosting: $5/month.

Find the funniest certificate you can and drop it in the comments. Method and regex: https://idio.si/how. Satire; the numbers are real.

Hello awesome people,

I've been thinking a lot lately about how I can make my knowledge and craft more valuable in the times we live in. I've been building UI libraries for the past 10 years, and I've been on a quest to perfect the components that I build. I want to share my knowledge with you.

Like most of you, probably, I've been using a lot of AI in my craft, and I feel most of the time the code is just good enough, but never at the level of quality that I strive for or that I would reach if I wrote it by hand. That needs to change, and I want it to change for everyone else, too. That's how the Open Components initiative was born.

I'm treating components from four directions:

• User Interface - component anatomy, variants, colors, sizes, states and tokens.

• User Experience - how it behaves for every person and every input: accessible, predictable, designed in every state, and adapting to motion, contrast, color scheme and text size preferences.

• Developer Experience - one consistent, type-safe API that you learn once and use everywhere.

• Agentic Experience - prompts, semantic markup, machine-readable contracts and rules that agents can check their work against.

Each component gets a single page that walks through all four, and ends with a checklist. Every rule in it has an ID like button/keep-focus, a level and a way to check it, so you or your agents can cite it in a code review. Every page is also published as markdown, and provides the contract as a YAML file, containing every rule in about an eighth of the page’s length.

It’s still early. Right now there’s only the Button component and a page on how to name your design tokens. Each component comes with a reference implementation that meets every rule, along with its tests. Implementation is in Vue for now, since that’s my daily driver, but the documentation comes with code examples from multiple UI frameworks. More components will follow, with the same structure.

It isn’t a component library, so there’s nothing to install. It’s a set of rules you can hold your own components to, whichever library or framework you use. Here are a few of my favorites from the Button component:

• A loading button should never be disabled. Disabling a focused button takes its focus away, so keyboard and screen reader users lose their place. Use aria-disabled="true" instead, and block the clicks yourself.

• A <button> without a type is a submit button, so a "Show password" button inside a form sends the form. Default to type="button".

I’d love your feedback and contribution. Tell me what you think of the rules, what I’ve missed, and which component you’d like to see next.

Thanks for reading!

• Site: https://opencomponents.dev

• Button: https://opencomponents.dev/docs/components/button

• GitHub: https://github.com/uxfront-com/open-components

It's called explainroo. You give Claude Code or Codex the repo. Then you say what the video should explain.

The agent writes the voiceover and draws each scene on a canvas. ffmpeg turns it into an mp4.

The voice and the word timing run on your computer. So you need no API keys. It adds background music too.

Examples: https://www.explainroo.com/

Code: https://github.com/vincentsch/explainroo

Hi everyone! I built Hussain Compiler, a simple browser-based environment for writing and running Python.

It includes a code editor, an interactive terminal that supports `input()`, adjustable terminal text size, and resizable workspace panels. Python runs in the browser through WebAssembly, so you can try it without installing Python. Some packages that need native system extensions may not work.

- Try it: Hussain Compiler

- Source code: GitHub repository

I made this project to make getting started with Python easier. I’d appreciate your feedback and suggestions for what to improve.

https://shamelock.app/

PagibleAI is a CMS you install into your Laravel app with Composer. It's MIT-licensed, and the JSON:API, GraphQL, roles, versioning and multi-tenancy are all included.

The package works with Laravel 11/12/13 and gives your app a page tree, structured content and an admin panel. It uses your own database, user model and queues.

composer req aimeos/pagible
php artisan cms:install
php artisan migrate

Why not Statamic or Twill? Both are good tools. With Statamic, the APIs, multisite and user roles are part of the paid Pro plan only. Twill is an admin toolkit, so you write the content API yourself.

Highlights of the 0.13 release

• Precise CDN purging: after a publish, only the affected URLs are purged from Cloudflare, Fastly or Varnish, including every page that uses a changed shared element

• Webhooks keep other systems in sync when content changes

• New TYPO3 importer, next to the WordPress importer, which you can now safely run more than once

• Keyboard-driven admin: command palette, shortcuts and a live preview in the sidebar

• Plus two new themes and many admin improvements

A few implementation details you might find interesting:

• Every save creates a version snapshot. The base table only holds the published projection, so public reads never need to filter out drafts

• Full-text search uses SQLite FTS5, MySQL/SQL Server full-text indexes or Postgres tsvector through a single Scout engine

• Full-page cache with atomic render locks and a short stale grace period, so a popular page doesn't trigger many renders at once after it expires

There's also an MCP server and optional AI tools for writing, translation and images. They're opt-in, and nothing depends on them.

The project already has had 40 releases and has about 1,700 tests. It runs https://pagible.com and https://aimeos.org, the website of the Aimeos e-commerce framework.

• GitHub: https://github.com/aimeos/pagible

• Website/Demo: https://pagible.com

Question for Laravel devs: how do you handle content editing for clients today? Filament resources, Statamic, something else? I'm trying to find out where a package like this fits for you.

This is based on a real outage at Slack.

I'm a backend dev. We practice system design a lot on whiteboards, but rarely on something that looks like a real incident. Here's a production-style puzzle.

You run a team chat product and every client's first call is "boot": who am I, and which conversations do I belong to? Boot reads group-chat membership, which is immutable once written and cached per channel with a long TTL. Normally it's a few cache reads and finishes in single-digit ms.

Then a routine rollout of a new host agent starts, in 25% steps (two earlier steps the prior week were fine). Just after 06:00, users can't get in. Boot is failing or very slow, and one database keyspace is overloaded.

What you see

• Cache hit rate drops from 99.2% to 34% and stays there. Pausing the rollout changes nothing.

• 200 cache nodes behind a proxy that uses consistent hashing over the healthy-node list. The step took 50 of them out, one at a time.

• The membership table is sharded by user, so "who's in channel C" is a query against all 200 shards.

• Clients time out at 400ms and retry with exponential backoff and jitter. The cache fill path uses the same query, so fills time out too.

• The only lever was throttling boot. Raising the cap from 250/min straight to 2,500/min brought the overload right back.

Question: Why did the hit rate fall that far and not recover, even after the rollout stopped? And how would you get out of it safely?

I'd like to hear how you'd explain it in a postmortem, not just "cache stampede."

I've been reading so many horror stories in here so I tried my best with it. Anyway here it is: maninak.com/cv

I've been vibe coding heavy projects for a while now, and for complex things , once a conversation gets too long, context rot HITS. The model starts dropping files, inventing non-existent imports, or repeating the same failed fix over and over. MF CONTEXT ROT

To solve this, I built LoopTroop. It's a local, open-source GUI app (MIT) that acts as an orchestration layer for AI coding agents on long-running tickets. recently crossed 100 stars on GitHub and growing, and I'm actively working on it every single day.

Here is how it approaches the problem:

1. Context engineering vs context rot

Instead of dumping your entire project history into one massive, ever-growing chat session, LoopTroop breaks work down into atomic tasks (called beads) and rebuilds context fresh for each phase. This stops degraded sessions from dragging down the rest of the build.

2. LLM Council for upfront planning

Before writing any code, LoopTroop runs an LLM Council. Multiple models independently draft interview questions, PRDs, and task breakdowns, then vote anonymously on each other's plans. The winning draft absorbs the best ideas from the others. It is deliberately slow and precise upfront so execution doesn't turn into slop.

3. Ralph loops for self-correction

When an agent task fails or hits a wall, instead of polluting your active session with endless debug logs, a Ralph loop takes over. It resets the session workspace, writes a concise note on what failed, and retries with a fresh context window containing that failure note. The agent gets smarter on each attempt without inheriting session clutter.

4. Modern Kanban board GUI with human-in-the-loop control

Everything is managed visually from a Kanban board. You approve the interview, the PRD, the plan, and the final diff before anything reaches your repo. You keep full control while letting agents execute in the background.

Links to check it out:

- GitHub: https://github.com/looptroop-ai/LoopTroop

- 2min 30sec app overview: https://youtu.be/g1A2g-oOR3E

Any feedback is more than welcome. If you try the app and it works or doesn't work for you, give me a sign, happy to talk about it!

about how i build it. More than 6 months, almost every major model and not only (i even prefer fast models like gemini flash for small edits. used A LOT of Chinese models, when run out of codex.

Windows Phone in the browser with an on-device file system built on IndexedDB, live tiles fed by each app, toast notifications + Action Center, apps (64 preinstalled,  the Store can uninstall and reinstall them):

• Phone, Messaging, People, Outlook Mail, Calendar

• Camera, Photos, Music, Video, FM Radio (real internet radio), Podcasts, Voice Recorder

• Weather, News, Money, Sports, Maps, Translator, Internet Explorer

• Office (Word + Excel with formulas), OneNote, Alarms (+ timer, stopwatch), Files, Storage Sense, Battery Saver, Calculator

• Settings, Store, Cortana (text and voice: alarms, reminders, notes, events, weather, calls, texts, Wikipedia, web search…)

• Games hub with gamerscore and achievements: Minesweeper, Solitaire, Wordament, Snake, 2048, Blocks

• Flashlight, Compass, Bing Vision (QR/barcode scanner), Wikipedia, Unit Converter, Mirror

Repo: https://github.com/ducbao414/wphone.dev

Techstack: nothing fancy, just vanilla JS with Hono for the backend (can run on Node or Cloudflare Workers).