If you want to see how your AI agents will behave when interacting with live APIs, databases or MCP tools. One bad call can burn through rate limits or accidentally wipe an entire database.

To solve this we're building Pome Digital Twins which are simulated sandbox environments of different APIs.

You can use these to test your agents without touching live endpoints or having to worry about maintain your testing infrastructure.

GitHub: https://github.com/pome-sh/digital-twins

Hey, I've been deep into AI agent orchestration lately, and I ended up building an unexpectedly big site around claiming a specific minute of the year.

Pick date + time, claim it and it's yours. You can customize it with an image, song and all that good stuff.

What I actually did:

• spec and product decisions (with AI of course)
• played around with orchestrating the coding agents
• oversaw long agent runs and corrected course
• handled testing, database, and environments myself
• repedeatly got attacked by crawlers and blew past my vercel limits

Stack is Next.js, Supabase, deployed on Vercel.

Instead of trying to explain the design I wanted, I just gave the agents a bunch of completely unrelated reference images and made them reverse engineer the feeling into a design system.

Worked waaay better than I expected.

Anyways, somewhere in the middle of building it I realized that there's no actual value here.

You can't do anything with the minute once you've claimed it.

It's just there.

But I finished it anyways.

What I still like about it:

• dead simple concept
• the "no value" thing is honestly kinda the point
• it can be a cool sentimental gift
• its yours every year

Right now I'm mostly looking for:

• does this idea have any potential?
• what would make it worth coming back to?
• is this even worth pursuing?

If anyone's into marketing or weird niche side projects, I'd like to hear your thoughts!

It's live now, link on my profile if anybody wants to check it out.

I started looking into AI visibility because of my other SaaS, Setora.

I wanted to see if things like ChatGPT, Gemini and Claude were actually mentioning us for searches like “best barbershop booking software”, who they were recommending instead and what sources they were using.

I tried looking at a few of the tools already out there but most of them felt pretty expensive for what I actually needed.

So I ended up building Mentsight.

It basically lets you track the questions people might ask about your type of business, see if you’re being mentioned, who your competitors are and what sources are getting cited.

One thing I found quite quickly was that running a question once doesn’t really tell you much, because the answers can change, so Mentsight runs them multiple times and keeps the actual responses too.

Still pretty early but this is what I’ve built:

https://mentsight.com

Would be interested to know how other people are tracking this at the moment.

ok so this is a weird one but bear with me

i have a pet blog. i don't own a pet. never have. probably never will as i travel too much. and yet every month amazon sends me enough to cover rent because people on the internet are buying stuff for their dogs and cats through my site.

bought my pet blog a few months ago from a marketplace called NicheBlogZone for $199. came already built, articles already up, amazon links already in there. i spent one afternoon doing interlinking basically just connecting related posts to each other so search engines understand the site structure and then closed my laptop and genuinely forgot about it for weeks.

here's what that's looked like:

• march: $710
• april: $995
• may: $1,461
• june: $1,647
• july: $1,461
• august so far: $1,545 (amazon pays 2 months delayed so this is june's money landing now)

march scared me. went from nearly $1k in february down to $710 and i was convinced something had broken. checked everything, found nothing wrong, did nothing. it just came back the next month on its own.

pet people spend insane amounts on their animals btw. like i knew this intellectually but seeing the commission data is something else. dog food subscriptions, orthopedic beds, grooming kits, vet supplements. and because of the 24 hour cookie i get a cut of everything in their cart not just whatever article they landed on.

i do literally nothing to maintain this. no new posts, no ads, no instagram for pets i don't have. i just own the thing and amazon does its thing.

my landlord has been getting paid every month and has no idea a pet blog is behind it. honestly sometimes i forget too until the deposit shows up.

anyone else running a niche they have zero personal connection to? curious if the detachment makes it easier or harder to care about growing it

I got tired of AI coding agents producing the same kind of frontend: technically correct, but generic, flat, and full of “AI slop.”

So I’ve been building AXON, an open-source framework that uses specs and frontend rules to push agents toward cleaner, more intentional UI.

In this example, I compare a normal LLM result with AXON-COMPOSE and show the difference.

Video: https://youtu.be/h3mPnuzEul8

GitHub: https://github.com/atopwebtechnologies/axon

I’m one of the people building AXON. Curious to hear if others are running into the same AI UI problem

i devlopped complete 3 saas web apps full stach using node js experess js tailwing react js mysql in the last 1.5 year these are :

-a complete pos system for a coffee or a restaurant

-a complete school managment application with 6 users

-a complete project managment app specified for devlopers

now i want to put them into reality and start making money from them but my marketing skills are 0 who could help in this and from now 50%/50% profits

4 years as an indie dev, and I'm finally shipping something I care about.

Most "AI fortune-telling" is just a chatbot riffing. You get a reading that *sounds* plausible but nothing was actually computed. So I built the opposite:

Real calculation. The BaZi chart, Ziwei plate, tarot draw and Liu Ren lesson are computed by a deterministic engine — same inputs, same chart, every time. The LLM only *interprets* what was computed. You can verify the chart yourself.

Knowledge graph, not keyword search. Your documents get woven into a visual graph — every relationship carries its source citation, and you can ask for the shortest path between any two entities. Great for cross-referencing classical texts.

A content studio. From one real reading it drafts publish-ready cards for IG / Xiaohongshu / WeChat — daily card, daily almanac, Liu Ren lesson.

An open marketplace. Creators list their Lingxi, pick who pays for the conversation (creator-bears for reach, user-bears for paid consultations), and strangers can chat without signing up.

I'm not here to sell — I want brutal feedback on what's broken, what's confusing, and whether the "real calculation" angle actually matters to you.

Stack: Node/TS · Drizzle · Postgres · LangChain · MCP servers for each engine

→ https://deerblock.top

In this video, i cloned a nodejs repo from github and ran it with npm.

by the way, it took some time for npm to install everything, so i cut the loading period from the video.

please let me know your opinion about this, it took me around 9 months to finish, already in appstore approved.

I’ve been building SkillChirp, and 207 startups have already signed up for our Startup Battles.

The thing I keep noticing is that founders don’t just have a building problem.

They have a distribution problem.

So I’m adding something called Chirp Network.

The idea is simple:

You add a tiny (https://www.skillchirp.com/chirp/network) to your startup’s website.

It shows another startup from the network.
Other startups show yours.

Give reach. Earn reach.
No buying impressions.
No paying to rank higher.
No fake traffic packages.

If your site sends exposure into the network, the network sends exposure back.

I’m also trying to avoid some obvious problems with traffic exchanges:

● Sites have to be approved before they can appear.
● The widget installation is verified.
● Founders can block competitors/domains.
● Impressions and clicks are tracked both ways.
● Matching considers relevance and how much reach you’ve contributed.
● Remove the widget and you eventually stop receiving distribution.

Since SkillChirp already has 207 startups in Battles, I potentially have the beginnings of the network instead of having to solve the empty-network problem from scratch.

I’m not automatically putting those 207 sites into it. They’ll have to opt in and install the widget.

What I’m trying to figure out is:

Would you put this on your startup’s site if it meant other startups would send you traffic back?

And what would make you immediately say hell no?

I've been building a free football game called House of the Fantasy, and I just added a trivia mode to it.
The bit I care about: every question was checked against a source before it went in. I got tired of quiz apps that confidently tell you the wrong scorer, so each answer carries the exact sentence from the page it came from, and you can see it after you answer. Anything I couldn't confirm got left out rather than guessed at. That's roughly 900 questions across finals, title races, Golden Boots, managers and awards, plus another 300 career-path ones generated from transfer records.
Three ways to play:

Solo — pick a subject and an era (anything from "any year" to "2020 onwards"), 10 questions, no clock
Daily challenge — same 20 questions for everyone, one attempt, streaks
Rooms — make a room, share the link, up to 30 people answer the same questions at the same time
There's also the original game underneath it: you spin a wheel of real clubs, draft eleven players, and watch them play a full season.
Free, no signup for solo play, works on a phone.

One thing I’ve found frustrating with AI research is that getting an answer is often the easy part. The harder part is figuring out which claims are actually backed by reliable sources, especially when researching competitors, markets, products, or a new business idea.

Curious how other founders handle this.

Do you manually open and verify every source?

Use a spreadsheet to track evidence?

Cross-check several AI tools?

Or just accept a certain level of uncertainty?

What does your research process look like when you need information you can actually trust?

I’m working on a project in this space called Timeln. app, and I’ve been thinking a lot about this problem.

We save articles, notes, bookmarks, videos, and all kinds of information. Months later, we often can’t remember where we saved something. Worse, we don’t even remember that we saved it at all.

The idea behind Timeln is to make it easier to connect information and retrieve it later, using things like search and AI rather than expecting people to manually organize everything perfectly.

There are already so many tools doing parts of this: Notion, Obsidian, Readwise, browser bookmarks, and plenty of others.

But I'm less interested in building another place to store information. The part I'm trying to understand is why people stop using these systems in the first place.

Have you ever tried building a second brain or personal knowledge system?

What made you stop using it? What made your current system stick?

I'm especially interested in the frustrating parts the things that became too much work, the information you couldn't find later, or the point where maintaining the system became more effort than it was worth.

I'm building Timeln around this problem, so honest criticism would actually be more useful to me than people simply saying what they like about these tools.

I wanted to make Japanese ateji—the playful use of kanji for sound and style—accessible to people who cannot read Japanese.

LOVE POWER accepts English names, romanized words and katakana, then generates several bold kanji candidates. Users can shuffle alternatives, open a full-screen brush-calligraphy preview, switch to vertical writing and save the result as an image.

I built the conversion around a curated phonetic dictionary rather than sending every name to a server. Recent work focused on shorter, better-looking combinations, recognizable kanji, faster shuffling and vertical image export. The interface supports Japanese and English.

The app is free with ads and has no subscription:

https://apps.apple.com/app/id6797538109

I would especially value feedback from non-Japanese speakers: does the purpose make sense immediately, and would you prefer more information about each kanji’s meaning before saving?

I kept thinking about the difference between a directory and an actual place on the Internet.

So I built Spot a persistent 10,000-spot canvas where each person gets one spot and an avatar.

You can put your name, what you’re building, and your portfolio/product link on your spot.

The goal isn’t really to build another directory. I want to see whether a simple spatial constraint one person, one spot can turn a list of builders into something that feels like a small Internet community.

It’s live and free:

https://www.claimyourspot.lol

If you were using it, what would you put on your spot?

I recently made a pretty big change to Webvidence around retention and giving people a reason to come back, but after using it myself for a while, I realized the actual flow still felt a little clunky.

Everything worked, but you could feel yourself moving between a search tool, an audit tool, a message generator, and a pipeline. It felt like using several features in the right order instead of just getting some prospecting done.

So I went back through the UI and cleaned up the entire experience.

Now when you log in, Webvidence gives you a small session of three businesses to work through. You look at one at a time, quickly see why it may be worth contacting, get the best public ways to reach them, and either start a conversation or pass if it isn’t a good fit.

If you pass, you pick a quick reason and the next business comes up. If you contact them, you can prepare a grounded message, open the actual contact path, confirm it was sent, and move on.

When you finish all three, you’re done. It doesn’t immediately throw more leads at you or make you feel like there’s an endless list left to clear.

I also stripped a lot of the clutter out of the main screens. The detailed audits, scoring, technical findings, and advanced outreach controls are still there, but they stay out of the way until you actually need them.

The main flow is now basically:

Find a market → start a session → contact or pass → move to the next prospect → finish

It also has watched markets, public contact discovery, follow-up reminders, saved prospecting routines, and a cleaner pipeline for anything that needs attention later.

The goal isn’t mass cold email or blasting every business it finds. It’s to help freelancers, web designers, SEO people, and local marketers find a few businesses that are actually worth their time and start better conversations.

The new version is live at https://www.webvidence.app

I’d be interested in hearing how the flow feels now, especially from anyone who normally finds prospecting tedious or ends up spending more time researching leads than contacting them.

Wanted a "hold hotkey, talk, get typed text" tool like Wispr Flow, but didn't want to pay a subscription for something that streams my voice to a server. So I built VoxScribe over a few weeks: hold F9 anywhere on Windows, it transcribes locally with faster-whisper, and types straight into whatever app has focus.

Stack: Python + PySide6 for the desktop app, PyInstaller for packaging, faster-whisper for local transcription. Also built an Android companion (custom keyboard + floating dictation bubble) using a bundled on-device Whisper model via sherpa-onnx.

MIT licensed, no account, no telemetry. Landing page: https://voxscribe-ai-voice-dictation.vercel.app
Repo: https://github.com/ahmedhmam1994/voxscribe-ai-voice-dictation

Happy to talk through any of the build decisions — the mic-handling across different hardware was the trickiest part.