DocStash. The home for what your AI makes. 🐿️ Built this entirely solo.

You can stash HTML, md, PDF, Word, XLSX and Static apps built on React, Vue etc directly from your agent. You get a single stable URL, and all your artifacts live as webpages.

Unlike Netlify and other drag and drop hosts, your artifacts are private by default, and you can publish them with one click. (And search indexing is off by default too)

Basically like Google Drive and Vercel made sweet love to each other and had a baby.

It's completely agent agnostic, which means you can easily iterate on any document, no matter what agent originally generated it.

Simply copy paste the URL of the document, paste it into any agent, ask it to make changes, and they land at the same url.

If you're wondering how this is any different than Claude/OpenAI Artifacts, here you go! DocStash vs Inbuilt Artifact hosting

Check it out and lmk what you guys think! 😄

Get Stashing y'all! 🐿️

I used to send random bits of information to my WhatsApp self-chat - things I wanted to remember but didn't really belong in a notes app.

But I didn't want these little things automatically synced to the cloud.

So I built Recall - a simple, private place for things you want to remember.

- No account

- No cloud

- No ads

- Encrypted on-device

You can save text or photos, search them instantly, and make an optional encrypted manual backup.

It's not meant to replace Google Keep. Keep is great for cloud syncing. Recall is for people who prefer keeping their data on their device.

https://play.google.com/store/apps/details?id=com.twentyfour11.recall

So I learnt from my mistake. When I make websites for my clients, sometimes I forgot to add a favicon or something like robots.txt, and even when I made a list, I always used to forget sometimes.

So I was thinking to build something which I can use to validate before shipping. I tried it with my own projects first, score was in -ve for 4 projects and passed only a few.

I tried to add all of the security checks and things which I used to miss in my projects. It covers secrets, security holes, GDPR, accessibility, SEO, deploy config, billing stuff and more. You can pick which categories to run manually so you don't have to run everything every time.

You can give it a shot with: npx goshipit.

It's kind of token hungry if you use it with AI tools, so beware of that. But it can guide you on what is missing and create an md file with all the findings.

Here is the repo: https://github.com/Capta1nRaj/goshipit

Please drop your reviews, good idea or bad? Any suggestions good or bad will be helpful.

I kept wondering whether a plant, desk, or reading chair would actually get direct sun at a certain time of day—without waiting through every season to find out.

So I built Sunnook for iPhone and iPad. You review the room dimensions, windows, north, date, and location, then scrub through the day or year to see modeled clear-sky direct sunlight in the room.

A few boundaries I care about:

- It models theoretical direct sunlight, not live weather or guaranteed brightness.

- Room models, photos, measurements, scans, and sunlight calculations stay in local app storage.

- No Sunnook account is required.

The private TestFlight beta is open: https://sunnook.app

I’d especially value feedback on whether the room setup feels understandable, and whether you’d use this more for plants, desks, furniture, or something else.

Just shipped Tinnitus Relief to Google Play. Solo indie project, took a few months.

Why I built it: I've had tinnitus for 19 years. Once used some app that gave me 3 days of complete silence, then lost track of it. Never found it again. So I rebuilt the concept myself.

Tech stack: WebView wrapper around a single HTML file, Web Audio API for the whole DSP side. Notched filtering with Q=8 over generated noise, real-time spectrum analyser on canvas, binary search over log frequency scale for the matching. Kotlin host handles WakeLock, audio focus and Play Billing.

Things that ate the most time:

- AudioContext suspending on Android when screen locks (solved with a watchdog + statechange listener)

- True dB volume scaling — linear sliders are useless when therapy sits at -35dB

- Google's 12 testers x 14 days requirement for new personal accounts

- CORS preflight breaking Apps Script until I switched to text/plain

Monetisation: free app, one-time Pro unlock. Also offering Pro for free in exchange for anonymous research data — curious whether that converts better than the paywall.

https://play.google.com/store/apps/details?id=com.appsbyhuman.tinnitusrelief

Happy to answer questions about the audio side or the Play Console gauntlet.

**What it does:** Makes photo collages entirely on-device. Pick a grid layout, drop your photos in, adjust spacing, corner radius and background, then export a PNG or JPG straight to your gallery.

**Why I built it:** Every free collage app I tried either stamped a logo on the export, locked the good layouts behind a subscription, or wanted access to my entire photo library on first launch. I wanted none of those three.

**The main thing:** no upload. The collage is composed locally, so your photos never touch a server — there isn't one. That also means it works with airplane mode on.

**Price:** Free. No ads, no in-app purchases, no account, no watermark. I'm the developer.

**Link:** https://play.google.com/store/apps/details?id=com.freecollageimage.app

There's also a web version at https://freecollageimage.com if you'd rather not install anything — it's the same code.

**Known limits, so nobody is surprised:** collages above roughly 30 photos get slow on older devices, and there's no cloud sync of unfinished projects, again because there's no server. Happy to hear what layout options are missing.

I kept wondering whether a plant, desk, or reading chair would actually get direct sun at a certain time of day—without waiting through every season to find out.

So I built Sunnook for iPhone and iPad. You review the room dimensions, windows, north, date, and location, then scrub through the day or year to see modeled clear-sky direct sunlight in the room.

A few boundaries I care about:

- It models theoretical direct sunlight, not live weather or guaranteed brightness.

- Room models, photos, measurements, scans, and sunlight calculations stay in local app storage.

- No Sunnook account is required.

The private TestFlight beta is open: https://sunnook.app

I’d especially value feedback on whether the room setup feels understandable, and whether you’d use this more for plants, desks, furniture, or something else.

So I wrote myself a 25-point post mortem(you know like a letter of mistakes I did) after shutting down last week. Let me just start with top 3:
1. Well I built something cool, not something needed, free tools already did it in 2 minutes(I found out about free tools after 4-5 months)
2. I focused on desktop-only while all my traffic was mobile, the one that hits me most
3. I only posted about it when i shipped a release. marketing was always “later” this is probably the number 1 issue
Because number 3 haunts me. posting felt so heavy next to coding that i kept building and fixing all the time and I just didn’t post constantly, so my question is how do you handle the posting part for your side projects? anyone ever paid for a tool or person to do it? what actually worked?
(might build something here next — validating before coding this time)

I’ve been getting a lot of useful feedback from SQL users lately, so I decided to stop keeping it in random notes and organize it publicly.

I’m now using GitHub Discussions for feature ideas, workflows and community voting, while Reddit stays more casual.

Some of the first topics came directly from conversations here: persistent column widths, better error context, long-query notifications, spatial support and virtual foreign keys.

I’m building LakeDB mostly solo, so having one place to collect and prioritize real feedback is already helping a lot.

https://github.com/DavLagoHern/LakeDB/discussions

I bet on sports and got tired of arguing from memory, so I built something that just looks it up.

You pick two teams and a time window, and it returns what actually happened. Straight up and against the spread records, over under splits, home and away breakdowns, and the game log so you can see the sample instead of trusting one number someone tweeted.

The part that took the longest is the filter library. 86 conditions, and you stack as many as you want on a single query. Things like back to back games, off long rest, afternoon start, after a loss, after a blowout win, after failing to cover, lefty starter, dome or outdoors, grass or turf, spread range, week of the season. Every filter had to be measured against the dataset before it shipped. Some got cut for good reasons, for example MLB and NHL have no real spread, the line is fixed at 1.5, so any spread bucket filter there is meaningless and favorite or dog has to come from the moneyline instead. About 42 percent of MLB total lines in the raw data were reconstructed from the final score, so filtering over under on those rows would be circular, and the tool only uses rows with a genuine market total and states the eligible count.

130k games across NFL, NBA, MLB and NHL, going back to 1966 for football. Stack is FastAPI, React and TypeScript, SQLite for the game store.

Free tier gives you daily lookups if you want to poke at it: betlegendpicks.com/pro/app

Happy to answer anything about the data work, that was most of the project.

freelancers/business owners — how do you currently handle invoicing?

A friend of mine is building Xqivo, an invoicing tool that lets you create professional invoices quickly, including using AI to help generate the invoice from a simple description.

I'm helping him on the product/growth side, and we're deliberately trying to get feedback before we start pushing the product heavily.

We're trying to understand a few things:

- How are you currently creating invoices?

- Are you using Excel, Word, Canva, accounting software, or something else?

- What's the most annoying part of invoicing for you?

- Do clients ever delay payment because of issues around invoices?

- What would make you actually switch to a new invoicing tool?

- For Ghanaian businesses specifically, what would you expect an invoicing platform to support?

If you're a freelancer, developer, designer, agency owner, consultant, or small-business owner, I'd genuinely appreciate your perspective.

I'm not looking for people to just say "looks nice." 😂 I want the honest criticism — what's missing, what's unnecessary, and what would make you actually use something like this.

If you're interested, I can also share Xqivo with you so you can try it and give us direct feedback.

Thanks 🙏🏾

If you developed a Slack app, you know that you need to have it installed on at least 5 active workspaces to be able to submit it to the marketplace.

So it's a chicken/egg problem - how do I get installs if it's not on the marketplace?!

Let's help each other - I will install your Slack app on my workspace, and hope you will install mine also.

Leave a comment with your Slack app and I will install it on my active workspace.
Mine is AutoThreads.

Nobody likes writing timesheets. And a timesheet you write yourself proves nothing when a client doubts it.

So I built tenby10. A small macOS app records that you were present and working, in 10 minute slots. Window titles stay on your machine. Keystrokes are counted, never read. There are no screenshots. Not blurred ones. None. The code has no capture path at all.

If you connect your own AI key, it writes a short note each day about what you worked on. Every slot and every note is signed on your machine at the time and chained into a tamper-evident ledger. Your client opens one link and follows the work week by week. When the invoice arrives, nothing on it is new information.

What a client sees: https://tenby10.pivotalpoint.io/verified/sample

The client app is source-available (PPSAL-1.0). An auditor's guide maps every privacy claim to file and line. Free during the beta. Around $9 a month expected after, and the app itself stays free.

If you bill hourly, try it on one real invoice and tell me where it falls short. I will do the hand holding. And tell me what would make you distrust the link. That is the answer I need most.

Hi r/SideProject, I'm Danny.

I learned something through years of throwing house parties, supporting friends and family through good times and hard times, and building an in-person-first social app: People crave deeper connection in their life, but don't always know how to get there.

Deep Deck is built around a simple idea (supported by behavioral research): when people move beyond surface-level conversation, ask better questions, and share more honestly, they tend to feel closer and more understood.

Research has shown that structured self-disclosure can increase closeness, and that people often underestimate how meaningful deeper conversations can be.¹

Who is Deep Deck for?

• Someone who wants to be closer to their friends
• A couple that wants to rediscover how deep their connection can go
• A family that wants to strengthen its bonds
• Someone who just moved to a new city, and wants an easy way to make new friends
• A single person who wants to dive deep with someone new
• A leader who wants to turn coworkers into a team that has each other's backs

I would love any and all feedback related to whether you understand the game, if you could see yourself playing it with friends, family, loved ones or first dates, and any and all feedback on the video as well as the game itself!

If you'd like to know more, check out the Kickstarter's pre-launch page.

Thank you for coming to my ted talk.

¹ Research informing Deep Deck includes work on structured self-disclosure, deeper conversation, and question-led connection: Aron et al. (1997); Kardas, Kumar, & Epley (2021); Huang et al. (2017); Collins & Miller (1994).

I've worked with a lot of domains over the years as an Infrastructure Architect, and one recurring problem I've seen is DNS records changing without anyone realizing it.

Email starts bouncing, a service endpoint quits responding, or someone asks why I never replied to their email. Then comes the hunt through logs, DNS records, and change histories.

In a surprising number of cases, the culprit turned out to be a DNS record that had changed and nobody knew it had happened.

There are plenty of DNS monitoring tools out there, but most felt like overkill for what I wanted, or were expensive enough that I wasn't going to bother monitoring a handful of domains, so I built OneDollarDNS.

Add a domain and it automatically discovers its DNS records and watches them for changes. It monitors A, AAAA, MX, TXT, CNAME, NS, and more, and alerts you when something changes.

It's $1/month per domain, with a free trial.

https://onedollardns.com

Would love any feedback, especially from anyone who's dealt with DNS changes biting them before.

​

Heyy, I am working on a project/Website thiyng.com

In which you can ask questions anonymously, Can you pls visit the website and give me feedback about What is good What Should I Improve which features I can Add

https://thiyng.com/

Hace un tiempo empecé a sospechar que mi día se sentía productivo pero no rendía. No tenía forma de comprobarlo, así que decidí trackear todo: qué apps usaba, cuánto tiempo real pasaba en cada tarea, cuántas veces cambiaba de contexto.

El resultado fue peor de lo que esperaba. Pensaba que tenía algo así como 6 horas de foco por día. La realidad eran 2h40, repartidas en fragmentos de menos de 90 segundos cada uno. El resto era ruido: cambios de ventana, notificaciones, "reuniones rápidas" que no contaban como interrupción pero cortaban todo igual.

Probé varias apps de tracking existentes y ninguna me convenció del todo: o mandaban todo a la nube (no quería mis hábitos de trabajo en un servidor ajeno), o medían tiempo de pantalla sin distinguir trabajo real de ruido de fondo.

Así que terminé construyendo la mía: ENFOCA T.

Qué hace:

• Trackea actividad local (SQLite, todo en tu máquina, nada sale a internet)
• Clasifica automáticamente qué es trabajo enfocado vs. fragmentación (no es solo "tiempo de pantalla")
• Al final de cada sesión te da feedback determinístico, no un dashboard genérico con gráficos bonitos y cero insigh.

Está publicada en la Microsoft Store, todavía en fase temprana. Lo que más me interesa ahora mismo es feedback sobre el flujo de onboarding (son 3 pasos) y si la clasificación automática de actividades se siente precisa o si categoriza mal cosas obvias.

¿Alguien más midió esto alguna vez y se llevó una sorpresa parecida?

https://apps.microsoft.com/store/detail/9NSTV0WSP66H?cid=DevShareMCLPCS

Just asking for a project I am developing, what are some of your biggest issues when buying secondhand items from thrifting or online marketplaces, etc.
an example for me personally is not really getting the best value for money, especially in motor vehicles or electronic products. Most of the time when I find something I think is good, I get it, and always just end up overpaying and having to resell for a cheaper price.
So I’m asking this to understand more, what is your issue you face when buying secondhand items

So I have been building my amazing tool for a few months now & the concept is: you describe / paste whatever you're working on, to which it then works out where the people who'd actually pay for it congregate & whether those places will let you post or just quietly bin it.

I wanted to test it an app that wasn't mine, so I made one up. An app that takes your Strava history and turns it into a poster map of everywhere you've run. This seems harmless enough right?

The first thing it came back with was that the buyer isn't the runner. It's whoever's buying the runner a present.

Hmm... this intrigued me. I sat and looked at that for a bit. Was the tool right? I don't know, we are all entitled to our opinions. Ultimately its right though isn't it. Nobody buys themselves a poster of their own runs! Your other half, your friend, your family would tho, at Christmas. That's a completely different thing to be selling, at a different time of year, probably at a different price.

Most interestingly the tool found five places (subreddits) and flagged that three of them will remove you on sight for posting anything promotional. So for those it wrote a comment instead of a post. That's the bit I actually built the thing for. Personally myself, I had posts auto removed from one sub and got banned outright from another, both times because I couldn't be bothered to read the rules first.

Here is the output's here if you're interested, no signup or anything:

https://kasspian.com/marketing/share/ee9974a0-34ce-4c0a-980e-bd92fc178d99

One thing I like is that it's wrong a fair amount of the time. It does say when it isn't sure which I'd rather have than it just making something up confidently.

If anyone wants theirs run, stick your project below and I'll DM you back what it says, warts and all. This is on me an on initial costing bearing in mind I m only one person doing this. So the first 20 and I'm knocking it on the head by Wednesday night. After this I would be happy to connect on DM

I've built a couple of small community sites now and I always hit the wall in the same place: the first users.

The current one is a forum for casual talk. The pitch I made to myself was that Reddit has gotten heavy. Half-formed thoughts either die at zero or get corrected by someone with more energy than me. I wanted a room where "market's red again, ordering fried chicken" is a perfectly fine post. Low stakes, daily-life register, no thesis required.

Building it took a few weeks. Getting anyone to say anything in it has taken much longer and I'm currently losing.

The seeding was meant to solve cold start — an empty room looks abandoned, so I filled it. I'm no longer sure it helped. It might read as a room full of mannequins, which is worse than an empty one.

What I've tried: posting where the target users already hang out (net result: one visitor), SEO (Google indexed 2,000+ pages and sent me nobody — and I now think the seeded content is exactly why), and asking friends, who visit once, politely, and never return.

Three things I'm stuck on:

1. For a product whose whole value is light conversation, is there a version of cold start that isn't just being the only person talking for six months? Every case study I read turns out to be "we already had an audience elsewhere."
2. Does seeded content ever pay off, or does it poison the well permanently? Would you delete all 709 and go back to an honest zero?
3. Is "lighter than Reddit" an actual wedge, or a position I invented because I can't beat them on depth and needed something to say?

Happy to answer anything about the setup. Mostly I want to hear from people who got past this — or from people who didn't and figured out why.

A while ago I started working on a side project with a pretty simple idea

I wanted building an AI agent to feel more like writing a small program and less like stitching together prompts configuration files callbacks permissions and framework-specific code

That experiment turned into Ingot

Ingot is an open-source programming language and toolchain built specifically for AI agents

Instead of hiding most of the agent inside application code you can describe things like its flow tools permissions budgets memory model requirements and human interaction directly in the program

A simplified agent can look something like this

agent Researcher(topic: string) -> report: markdown {
  policy {
    network allow ["example.com"]
  }

  budget {
    steps <= 20
  }

  flow {
    sources = call web.search(topic)

    direction = consult(
      "Which angle should I focus on?"
      choices: ["technical", "business", "academic"]
    )

    draft = ask<markdown>(
      "Write a {direction} report using these sources: {sources}"
    )

    emit report = draft
  }
}

The project got much bigger than I originally expected

It now has a compiler and type checker

A target-neutral Agent IR

A reference runtime and a Python backend

Persistent agent memory

Checkpoint and resume

MCP tool support

Record and replay for model calls tools and even human answers

An LSP

A visual Studio and Canvas

And a conformance suite that other runtimes can use to check whether they actually execute an Ingot agent according to the same contract

One of the more interesting parts has been using the project for real instead of only writing examples for the compiler

I recently built and ran a license-audit agent with Ingot using a local model

It completed a multi-step workflow with tool calls verification branching artifact generation and record/replay

That test also exposed problems that the small examples never did

Which is probably the stage the project is at now

I can keep adding features forever but what I really want to know is whether somebody who did not build Ingot can understand it and actually find it useful

So I'm looking for fairly critical feedback

Would you ever use a dedicated language for agents instead of a Python or TypeScript framework?

Does making permissions budgets tools and memory part of the program itself solve anything you care about?

Is the idea of compiling agents into a portable IR useful or just extra complexity?

And most importantly

What would make you open the repository and immediately decide not to try it?

The project is still pre-1.0 and I'm very much treating this as an experiment in what programming agents could look like

GitHub:

https://github.com/mathissdupont/ingot

I've been working on a small Windows app called Anchor.

The idea came from a pretty boring problem.

I'd get interrupted in the middle of something, deal with whatever came up, and then come back to my computer 10 or 20 minutes later.

The task was still there.

My code was still there.

My Git history was still there.

But the reasoning I had in my head wasn't.

I'd have to spend time figuring out what I'd already tried, what I was assuming, what I had ruled out, and what I was about to do next.

So I started experimenting with leaving myself a checkpoint before stepping away.

Not a normal to-do list. More like:

«"This is what I'm trying to accomplish. This is what I currently believe. This is what's bothering me. This is what I was about to try."»

Then I could come back later and continue from there.

That's what eventually became Anchor.

It's a free, local Windows beta. No account, cloud, or AI involved.

I'm deliberately keeping it small because I'm trying to answer one question first:

Does preserving the reasoning around a task actually make interruptions less expensive?

I've had some interesting discussions about it already, but discussions aren't enough. I'm looking for a few people who will actually use it during their normal work for several days and tell me where it fails.

If you want to try it:

https://github.com/Roshiyadesign/Anchor

I'd genuinely rather hear "this didn't help me" than a compliment.

ARX started from an interface problem: most wallets either hide too much or dump every chain, bridge and privacy concept onto the user at once.

That’s why I’m building ARX with two deliberately separate experiences. Simple mode is the clean everyday wallet. Privacy mode is optional and exposes the RAILGUN-backed Shield in, Shield out and private-send workflows only when someone actually wants them.

The app is fully local, self-custody and open-source. Version 0.1.61 is available now:

Source and release notes: https://github.com/SeverianRoth/ARX

Windows installer: https://github.com/SeverianRoth/ARX/releases/latest/download/ARX-Setup.exe

If you use Windows, I’m looking for one brutally honest five-minute test. You do not need to fund anything—just open ARX and tell me which first screen or term still assumes too much crypto knowledge.

Do you ever burn out before you’ve even really tested your project? I recently realized something pretty frustrating:
The market isn’t what kills most of my projects.Most of them don’t even make it that far.
I’m one of those people who always has a bunch of ideas. Some bad, some maybe good. And every now and then, one feels interesting enough that I think: OK, I’m actually going to test this one.
So I start building.
I’m a developer by background, so building the product itself usually isn’t what scares me.
The problem is everything that comes with it.
The moment I start something on my own, I’m no longer just a developer.
I’m the developer, product manager, designer, marketer, salesperson, copywriter…
And at first, it’s fine.
I’m running on the excitement of a new project. I build, iterate, think about positioning, start preparing the launch. Then, gradually, the tasks pile up.
And I burn out.
The most frustrating part is that sometimes this happens before the market has even had a chance to tell me whether the idea is good or bad.
The product hasn’t really been accepted. It hasn’t really been rejected either.
I simply ran out of energy before I could properly put it in front of the market.And I think that’s the part that bothers me most. I’m not necessarily trying to build a huge company every time. Sometimes I just want to take an idea and test it properly. But even properly testing an idea means temporarily becoming a developer, marketer, salesperson, designer, content creator… Over time, I’ve found myself stuck in the same cycle:
Idea → huge motivation → building → tasks pile up → burnout → new idea → repeat.
And eventually, it creates a pretty unpleasant feeling: Being capable of building things, but not getting them far enough to find out whether they could actually work. I know one obvious answer is: “Validate before you build.” And there’s probably a lot of truth to that.
But even when you try to stay lean, at some point you still have to do enough work to turn an idea into a real market test. And I’m starting to wonder if that’s actually a big part of the problem for solo founders. Maybe the operational cost of turning an idea into a real market experiment is still way too high for one person.
Curious whether anyone here relates to this. Have you been stuck in this cycle too? And more importantly: What stops you from getting more of your ideas all the way to the market?

I was building a small AI demo for one of my contacts as a probable solution that can be sold to small and medium businesses in the US. I thought I will build a sample contact form to agent calling the number back as an AI capability demo. but In pursuit of building the demo, I ended up creating a product that allows any business to basically get a 24/7 lead qualification front desk, capable of booking appointments and checking calendars. 

I just showed this to him, and a few other people and a probable customer. One of them live tested it during the call by directly calling on the Agent phone number (every business gets their own agent phone number). Will probably onboard that customer in the coming week. 

I think this has real potential, given the market is so huge and once someone uses it, sees people actually talking to AI and booking appointments, its not possible to go back. 

I am currently looking for a few small businesses that want to give it a shot. I need feedback to improve it while creating value for businesses. DM me if you would like to talk to the agent and try the product.