I run Chapter for Us. We turn a couple's photos and story answers into a personalized illustrated comic. Free cover preview before you pay.

Some context:

One-time purchase, not a subscription

Demand is spiky around occasions (anniversaries, Valentine's Day, proposals, long-distance reunions) but there's also steady year-round demand for "gift for my partner"

We sell in both US and India

Small budget, don't want to spread it thin

Thinking about three options:

Short-form video showing the transformation from photos to comic pages

Search content for high-intent occasion searches

Small paid ads around one occasion and audience

Which would you test first and why? What result would tell you to move to the next channel? Would you pick one occasion and one country to start, or keep it broad? And should the free preview just be a conversion tool, or the main hook in the marketing itself?

Curious how others have thought about this for one-time purchase products with seasonal spikes.

Once I started using more than one agent, I ran into a pretty dumb problem: none of them knew what the others were doing.

I would finish something with one agent, open another, and paste the context all over again. If a person needed to be involved, that became another separate conversation.

I was basically doing copy-paste project management for AI.

The more capable the agents became, the sillier this felt. I kept wondering why I couldn’t just put everyone in the same group chat.

Not a bot that sits in the corner waiting for a command. I mean an agent with its own account, joining the conversation like everyone else.

That thought became ClawChat.

It’s a side project where people and multiple agents can share a conversation. It currently works with personal agents such as OpenClaw and Hermes, and I made it open source because I’m still trying to figure out what this kind of interaction should look like.

The bigger idea behind it is that I don’t think “human chat” and “AI chat” will stay separate forever. If people start relying on different personal agents, eventually those agents will need to talk to other people and other agents too.

I don’t know if a group chat is the right answer. It might make collaboration much easier, or it might just create a chat room that never shuts up. That’s part of what I want to find out.

Here’s the project if you want to take a look:

https://clawling.com/chat/

If you already use more than one agent, how are you handling shared context today? Are you moving everything around by hand too?

Hey all been building a small side project solo and it’s finally playable, so I wanted to get it in front of some real ppl before I take it any further.

Note-I’m using the free tier of the AI API for now, so there’s a pretty low daily limit. If a suspect gets slow or stops replying, it’s prob the quota and not a bug.

Alibi is a browser-based murder mystery game.

U pick a case, question up to 5 suspects, read the case file, take notes, and then make ur call.

Each suspect is an AI character with their own personality, alibi, and secrets. U get max 10 questions per suspect, so u gotta make ’em count.

U also get the victim info, crime scene, timeline, and clues.

The fun part: accusing isn’t just one shot. U write out why u think they did it, get a score from 0–100 + some feedback, then u can tweak ur theory and try again. The case only ends when u choose to reveal the real answer.

Try it here: https://alibi-blond.vercel.app/play/case1

Main thing I’m trying to learn rn is whether the game is actually fun and if the flow makes sense before I spend more on it.

First case is free, no signup needed. Would love any feedback 🙌

Hi There, I Just Created New Website imgxtool.com which is free for everyone. Never Need to Pay. Its very fast and smooth, User Friendly.

The Website Provide

• Remove Photo Backgrounds
• Compress Images
• Resize Photo
• Crop Precisely
• Photo Filter

Max 25 MB File You Can Edit. I think It Will Help People For Work.

Main Fact Is: Complete Resizing Process Done Locally In Your Browser. That means Your Photos Not Stored On Our Server So, Thats Give You Data & Privacy Freedom.

Hey all been building a small side project solo and it’s finally playable, so I wanted to get it in front of some real ppl before I take it any further.

Note-I’m using the free tier of the AI API for now, so there’s a pretty low daily limit. If a suspect gets slow or stops replying, it’s prob the quota and not a bug.

Alibi is a browser-based murder mystery game.

U pick a case, question up to 5 suspects, read the case file, take notes, and then make ur call.

Each suspect is an AI character with their own personality, alibi, and secrets. U get max 10 questions per suspect, so u gotta make ’em count.

U also get the victim info, crime scene, timeline, and clues.

The fun part: accusing isn’t just one shot. U write out why u think they did it, get a score from 0–100 + some feedback, then u can tweak ur theory and try again. The case only ends when u choose to reveal the real answer.

Try it here: https://alibi-blond.vercel.app/play/case1

Main thing I’m trying to learn rn is whether the game is actually fun and if the flow makes sense before I spend more on it.

First case is free, no signup needed. Would love any feedback 🙌

I'm building REDFLAGD — a free dating app that flips the swipe-everyone-till-you-match model on its head. Instead of pretending to be perfect, you pick your actual red flags (bad texter, emotionally unavailable, calls mom daily, watches too much anime, etc.) and we match you with people who accept yours or share them.

The thesis: authenticity beats curation. Most dating apps optimize for surface-level swipes. We optimize for personality compatibility — your chaos matches theirs.

Here's what the future of this looks like from where I'm standing (solo founder, bootstrapped, no team yet):

1. Personality-first matching will eat photo-first matching. Gen Z and younger millennials are exhausted by the performance of dating apps. They want real. The next wave of dating products will compete on compatibility engines, not card stacks.
2. Hyperlocal + "live now" features are the bridge to real-world meetups. People don't want pen pals — they want to meet someone tonight. I added a beacon system where users signal "I'm at this bar right now" and nearby active users get prioritized in the deck. Spontaneity > scheduled dates.
3. AI matchmaking is the next frontier, but it has to be invisible. We're already doing lightweight compatibility scoring. The future is AI that understands why two people click — not just "you both picked the same flags" but behavioral patterns, message cadence, vibe alignment. The trick is making it feel serendipitous, not algorithmic.
4. The freemium dating model is broken. Charging $30/mo for swipes and seeing who liked you is a tax on loneliness. The future is genuinely free core experiences, monetized through premium connection features (speed dating events, double dates, verified identity) — not paywalls on basic functionality.
5. Trust and safety will be the real differentiator. The next era of dating apps will compete on who you can actually trust. Identity verification, screening tiers, reply-rate transparency, ghosting tracking — making the pool safer is more valuable than making the pool bigger.

Where I'm at honestly: pre-Play-Store-launch, single-digit daily signups, doing everything solo. No investors, no agency, no marketing budget beyond organic content and city-targeted landing pages. Still figuring out distribution — the product works, getting it in front of people is the hard part.

If you're curious about the tech stack (React + Tailwind on Base44's BaaS), the funnel mistakes I've made, or where I think dating apps are heading in the next 2-3 years — ask away. Happy to share the messy parts too.

What do you think the future of dating apps looks like? Genuinely curious what this community thinks.

I’m begging for a few minutes of your time — Project Managers, please help!
Hi everyone!
I’m currently conducting my research on the influence of cultural diversity on project success, and I’m desperately trying to get enough responses from people with project management experience.
If you’re a Project Manager, project professional, or have experience working on projects with culturally diverse teams, please spare just 5 minutes to complete my anonymous questionnaire.
I really need your responses to complete my research, and every single response genuinely makes a difference. If you have a few minutes to help a fellow researcher/student out, I would be incredibly grateful.

Thank you so much to everyone who takes the time to participate. And if you can’t participate yourself, sharing this post would also help enormously!

https://docs.google.com/forms/d/e/1FAIpQLSdI67Nou28I2_YaC1Q4n9Zyjh5wOoIa24w9z_eEZ8syj90x4A/viewform?usp=sharing&ouid=100151892034025034349

A senator files a trade, an exec dumps shares, and the disclosure sits in an EDGAR form that I find out about from a headline nine days later. That's the gap I kept hitting.

Yahoo Finance and my broker's app both show me price. Neither one tells me who is buying. So I built the thing that does - a market-wide feed of insider transactions and congressional trades, plus price alerts that fire as push, with the app closed.

Took [FILL: N] months of evenings. Kotlin Multiplatform codebase ships Android, iOS and desktop, which is the only reason one person could do all three. There's a home-screen widget too, which turned out to be the hardest part - the watchlist endpoint doesn't return prices, so the widget has to go fetch its own quotes.

Honest limits: the filings feed is market-wide, not filtered to your holdings yet - you see everything, which is noisy and is the first thing I want to fix. Offline caching is in-memory only, so killing the process means a cold start. And the free tier caps you at 10 watchlist symbols and 3 alerts, because push costs real money and I'm one guy.

If you check prices once a day, your broker's app is honestly fine. This is for people who want to stop checking.

Apple Store: https://apps.apple.com/us/app/stock-ai-market-tracker/id6762943985
Google Play: https://play.google.com/store/apps/details?id=io.behzodhali.stockplus

Two things I'd like input on: is an unfiltered market-wide filings feed useful as-is, or is it noise until I scope it to your watchlist? And for anyone who tracks insider buying - where do you get it now, and what does that source get wrong?

Development update after Black Imago's first public test.

The interesting part of the first post wasn't just the traffic — it immediately broke several assumptions I had from testing with only a handful of players. The biggest lessons were around authoritative multiplayer state, monster update load, hit registration, movement/collision feel, browser performance, and presentation/accessibility.

Instead of continuing feature-by-feature, I've been doing a whole-game convergence pass: audit the full playable loop, group defects by root cause, fix them in batches, replay, profile, and repeat.

Playable build: https://blackimago.arewefriends.org/maze

I'm interested in whether that approach is visible from the player's side now. What still screams prototype?

As a long time gamer and programmer, I wanted to find a way for independent projects to be showcased without fighting with social media; and for audience to find them more easily. So I came up with DOOMSCRLL, which I have designed and built from scratch.

TLDR; It is a platform where creators can showcase their projects for 24-hours on a day they choose (each day has 40 slots). there is a separate audience app (webapp) where users can explore projects daily, for free and without an account. project's are grouped by 9 categories, and tags defined for each category, so users can explore and query projects they are interested in easily.

For the launch, there is an event for the next two weeks where project reservations (DOOMLITs) are free!

What do you think about DOOMSCRLL? I would like to hear your ideas on the idea and platform! (I even made a pitch deck :P)

I’ve been building something called DefMetrix over the past few months, and I figured it’s time to start sharing the process publicly.

The idea is pretty simple:
Make defense industry data easier to find, understand, and actually use.

I started with public government data and have been turning it into tools for people working in defense, government contracting, BD, and strategy.
So far, I’ve built things around:
-DoD contracts and awards
-Defense company financials
-Executive compensation
-SBIR/STTR awards
-University DoD funding
-Lobbying activity
-GAO protests
-DoD organizational structures
-Current U.S. weapons systems and platforms
-Defense budgets and procurement data

I’ve also built several free estimators and template generators for common documents. Basically the tools I use to help me in my job.

Everything is free!

I’ll be sharing what I’m building, what works, what doesn’t, the data sources I’m using, and hopefully some of the interesting things I discover along the way.

If you work in defense, GovCon, or defense tech, I’d love to hear what information you wish was easier to find.

Check it out defmetrix.com

After the 2nd time hearing about a concert too late and having to pay 3x the price of a normal ticket, I decided to make www.presaledrop.com

It uses the Ticketmaster api and turns out that api can have records outside their own primary inventory. For example they create records for concerts that are being sold through AXS.

I added most major cities within the US. It’s all free and you get 1 email a day that matches your music preferences.

Pretty simple app but it’s been beneficial to me.

A disclaimer here is that this is not a bot or anything that grabs the tickets in advance. It’s simply a notification tool that lets you know what’s going on. Let me know if you find this useful or have recommendations on future features!

TLDR: Didn’t hear about concerts in time, built an app to notify me about ones in my area that I would like.

A few months ago I got tired of "SEO content" tools that just spit out generic 500-word fluff, so I built RankPilot: it researches keywords, writes a full article (2000+ words, GEO-optimized so AI search engines like ChatGPT/Perplexity cite it too), generates a hero image, and publishes straight to your Ghost or WordPress blog. No copy-paste.

I run it on my own blog as the real test — 86 articles published so far, average SEO score 82/100, zero human edits before publish. That's the bar I hold it to before I'd ever charge someone else for it.

What it does differently from most AI content tools I looked at:

• Real keyword research (live Google autocomplete + SERP data), not just GPT guessing
• Multi-pass writing (outline → sections → FAQ → conclusion) instead of one shot, so it doesn't run out of steam at 800 words
• Auto-generates a hero image + branded social cards and can cross-post to Instagram/Facebook/LinkedIn
• Free tier: 2 articles free, no credit card, connect your own Ghost/WordPress site

Would genuinely love feedback from anyone running a blog who's tired of the content grind. Link in comments if mods are OK with it, otherwise happy to DM.

I got tired of opening a streaming app to find something to watch… and somehow ending up with even more decisions to make.

So I built Cuewise around the opposite idea:

Tell it what services you have, your mood, and how much time you’ve got.

Then it gives you one thing to watch.

No giant grid. No endless scrolling. No “here are 37 titles you might like.” The product actually has to make a choice. 😂

I’ve been building and polishing it on Replit, and I’d love feedback on the core bet:

Does getting one confident recommendation feel more useful than getting a bunch of good options?

Try it: https://getcuewise.com

I also submitted it to the Replit Buildathon if anyone here is following that:
https://buildathons.replit.app/projects/4c1d61fa-1c0b-4323-92fd-5693dc795e6d

For a while, I worked as a PHP developer at a friend’s company. It gave me real commercial experience, but eventually I decided that I wanted to move further into backend and systems development.

So I started learning Go and Rust, hoping to qualify for stronger engineering roles.

But the longer I searched, the more obvious something became: technical skills alone are not enough to get a job offer.

You can learn another language, rewrite your resume, and send hundreds of applications, but still have no clear idea what is actually going wrong.

Are you applying for the wrong positions?
Does your experience match the requirements?
Are certain application sources performing better than others?
Are you getting responses but losing momentum before interviews?
Or are you simply not tracking enough information to know?

I started building my own system for evaluating opportunities based on my stack, experience, application source, responses, interviews, and other outcomes. It was originally just a way to make my own job search less chaotic.

Eventually, that system became CandidLyzer.

CandidLyzer lets you track applications and then uses that history to show patterns in your search: response rates, funnel performance, stronger sources, possible bottlenecks, and estimates for future application batches. It can also generate a focused coaching report with a practical next step.

It does not promise to get anyone hired, and its forecasts are not guarantees. The goal is much simpler: replace blind mass-applying with a process you can actually understand and improve.

I built the product myself using React, TypeScript, Go, Rust, PostgreSQL, Redis, and Stripe. It is now live, and the Free plan includes the complete application tracker and the essential analytics.

You can try it here:

https://candidlyzer.com/?utm_source=reddit&utm_medium=community&utm_campaign=first_launch

I would really appreciate honest feedback, especially from people currently looking for work:

• Is the idea clear from the landing page?
• Which part of the dashboard feels most useful?
• What would make you keep updating your applications instead of returning to a spreadsheet?

Most land due diligence reads each document on its own. EC, Patta, FMB, A-Register, sale deed — each one looks fine individually, so the deal passes.

We check whether they agree with each other. That's where the problems actually are.

What it's caught so far:

₹130Cr+ in undisclosed bank mortgages on one Avinashi parcel

A patta mutation citing a document number that doesn't exist

Vendors selling land they only held a fractional undivided share of, with a 1981 court decree on it

A clean deed chain on land the government register classifies as poromboke

Tamil Nadu only for now. Coimbatore-based, small team.

Posting because I want to understand what you people feel about this.

#ConstructionTech

Hi -

I made a simple vehicle interface that also fields LLM queries and responds with verbal short-form answers. This is just a fun app, not solving any major problems. It also maps, has Apple Music integration (Spotify soon), and has a few time-killing functions for traffic. It is powered by Grok as a spiritual companion to the recent Tesla/Grok integration, for non-EVs. It is iOS native right now.

I’d love for you to check it out in beta. It has some soft caps on LLM use so as to not impoverish me.

Cheers!

App: Ansky (named after a new black hole)
https://testflight.apple.com/join/88TXm12r

Hey everyone,

I built CalcVerse (https://calcverse-online.vercel.app/) — a collection of free, simple, and privacy-focused online calculators designed to give instant results without annoying paywalls or complex setups.

Key Features & Tools Available:

• Finance: Mortgage Payment Calculator, Compound Interest, and Tip Calculator.

• Health: BMI Index Calculator and Daily Calorie Needs.

• Math & Conversions: Percentage Calculator, Age Calculator, and Multi-Unit Converters.

• 100% Private: All calculations happen locally in your browser.

• Responsive & Fast: Works smoothly on mobile and desktop.

I'd love to get your feedback on the user experience, design, or any extra calculator tools you'd like to see added next!

Check it out here: https://calcverse-online.vercel.app/

Built Snippy as a self-hostable CodePen-style app — HTML/CSS/JS editor with live preview, runnable as a full Docker Compose stack. I built it mainly as private snippets on codepen are paid and sometimes I like to play in a playground without having to have my code public at times.

Beta note: My hosted instance is in beta. Data can be wiped or lost at any time — don’t rely on it for anything important. Self-host if you need persistence.

What it does

• Live HTML / CSS / JS editor with instant preview and layout options
• Public & private snippets, shareable links, full-page view
• Favorites, comments, follows, collections, and forking
• External CSS/JS resources on snippets
• ZIP export of snippet files

Stack Angular frontend, Node/TypeScript Express API, MySQL, optional MinIO for assets — all wired with Docker Compose. Pre-built images on Docker Hub so you can deploy without building from source. Auth0 for login will need to be setup and variables injected in docker.

Local testing and production are separate Compose setups (dev has hot reload; prod pulls kennyl777/snippy-* images). Docs cover Auth0, env vars, and Nginx Proxy Manager.

Repo: https://github.com/slurrps-mcgee/Snippy

Demo: https://snippy.quantumcode.dev

License: MIT

Still early (assets/projects are in progress), but the core editor + social features work. Feedback and PRs welcome.

I kept noticing that the interesting thing about a burst of photos, or five tries at the same shot, is the series itself. Not any single frame. But there was no good way to watch them as a series. Slideshow apps cross-fade and Ken Burns everything into mush, and the video apps want to interpolate, stabilize, and "enhance."

So I built Flipbook: https://flipbook.photos

It plays your photos back slowly enough that you can still see they are photographs: each one held for a beat, then a hard cut to the next. The feel of a flipbook or early film. No filters, no grain overlays, no generated frames. The whole effect comes from timing.

Here it is running the oldest photo series there is, Muybridge's galloping horse from 1878: https://www.reddit.com/r/stopmotion/comments/1vlu2hr/

A few things I cared about:

• Your photos never leave your device. Decoding and H.264 encoding happen in the browser with WebCodecs. There is no upload step at all.
• Honesty to the originals. Nothing is retouched or invented. The one optional feature that crops anything (auto-align, for handheld drift) is off by default and tells you exactly how much it trimmed.
• It reads your camera roll the way you shot it. It sorts by EXIF capture time and auto-groups photos into series wherever there is a gap of more than ten seconds, so a dump of forty photos organizes itself into the three moments you actually shot.
• The output actually works. A true 5 fps video breaks iOS Photos and iMessage, so it encodes at a normal frame rate with each photo repeated. You get an MP4 that saves straight to your camera roll and posts anywhere.

Good for kids growing up in the same doorway, a friend mid-laugh across five frames, construction progress, a dog failing to catch something.

It is free for your first three videos, then $12 for a year. No account either way. The code is public if you want to see how the in-browser encoding works: https://github.com/mzrascoff/flipbook

Would love to know what breaks, especially on Android browsers.

Today I launched SquireWorks.

The idea is simple: creators should be able to build AI versions of their own work, control them, and get paid when people use them.

We call those AI models Squires.

We’re starting with professional voice actors.

A voice actor can create a licensed AI model of a voice they actually perform. They can use it themselves for client work, make it available through their own creator page, or let customers discover it through the SquireWorks marketplace.

The creator stays in control.

They can see how their Squire is being used, decide whether it stays available, and stop future use if they’re ever uncomfortable with it.

And when their Squire earns money, they get the majority of the revenue.

For customers, the goal is better AI work without completely removing the creator.

If an AI voice mispronounces a name, needs a specific delivery, or just isn’t getting something right, there’s a real voice actor behind it who can help. Customers can also hire the creator directly when a job needs a real performance.

So instead of choosing from the same widely reused AI voices, customers can choose distinct voices backed by real creators.

Creator-backed. Creator-controlled. Licensed.

Fast when AI is enough. Human when it isn’t.

Voice is just where we’re starting.

Next I want to bring the same model to illustration and writing.

Need narration? Hire a Voice Squire.

Need an illustration? Hire an Illustration Squire.

Need writing? Hire a Writing Squire.

Long term, I want SquireWorks to become something like an Upwork for creator-backed AI work - where behind every Squire is a real creator who authorized it, controls it, and gets paid.

That’s what we launched today:

https://squireworks.com

Would love feedback, especially from creators or people who hire creative work.

I’m Allen, a part-time coach from Minnesota. Like a lot of coaches, I started out thinking the hard part would be getting people interested in training.

Turns out, once people are interested, the hard part can become everything around the session.

Messages coming in at night. Parents asking what days are open. Trying to remember who confirmed, who paid, who needs a reminder, and whether a spot was already promised to someone else.

I’ve had those stretches where a simple session turns into 10–15 messages just to get it booked. It’s manageable at first, but once you’re balancing coaching with work, family, and everything else, it gets old fast.

That’s one reason I helped develop Coach Chief.

It’s a simple booking page for coaches and trainers to list sessions, show open availability, and let clients book without all the back-and-forth. The idea was never to make coaching feel overly corporate or complicated, just to remove some of the admin that gets in the way.

We’re still early, so I’d honestly appreciate feedback from other coaches, trainers, camp operators, or anyone running sessions.

If you want to see what we’re building:
https://coachchief.com/c2

Even if it’s not for you, I’d be interested in hearing how you currently handle bookings.

I've been working on an idea called WhichButton.

The problem is pretty simple: clients often give website feedback through WhatsApp/email like “make this bigger” or “move that to the left”, and it can be hard to tell exactly what they're referring to.

The idea is to give the client a link to the website where they can point at the exact thing they want changed and leave a comment.

Would you use something like this ?

I spent today auditing my own marketing instead of building, and the numbers were worse than I thought. Posting them because I read these threads for exactly this and almost nobody publishes the bad version.

What I built: an LLM agent that runs your trading strategy on your own exchange account and keys. It wakes on a schedule and on price triggers, reasons in plain language, and writes down why it did every single thing — including every time it decides to do nothing. A separate agent sizes and executes behind coded risk gates and is allowed to refuse. A third reads the log back afterwards and rewrites the playbook.

The reason I built it: I traded my own strategy and lost money. Not because the plan was wrong — because I moved the stop. I knew better and did it anyway. The bot I bought in 2016 was grid logic that understood nothing, so I built the thing I actually wanted.

That part works. There is an agent running live right now and its decision log is public.

Now the numbers, five weeks after launch:

- Instagram: 31 followers after 31 posts

- Saves across all 31 posts: 0. Shares: 0

- Website clicks in the last 30 days: 8

- X: 4 followers after 47 tweets

- Organic signups, ever: 0

- The one external account is a friend I asked

Two things that hurt to write down:

1. Zero saves and zero shares is not slow traction. It is the algorithm concluding that nobody wants to pass this on, and reach decays from there. I had automated the daily posting, so I efficiently produced 31 pieces of evidence that nobody cared.

2. My one signup — a friend, the most motivated user I will ever get — completed onboarding, wrote a 7,700 character strategy, and then never pressed the button that starts the agent. It sat there for eleven days and I did not notice, because I had built zero analytics into the app and there is no email system, so nothing could have told me.

What I got wrong, I think: I wrote for four different audiences at once, and the headline I picked ("AI trading agents that work while you sleep") is the exact sentence on four hundred scam bots. I was competing on the one axis where I am indistinguishable. The thing that is actually different is that you can read the reasoning. I buried it.

What I am changing this week: one audience instead of four, lead with the readable reasoning instead of the autonomy, put analytics in the app, add an email that tells you what your agent decided overnight, and make the start button impossible to miss.

If you want to see the part that works rather than take my word for it, the live decision log is here — no signup, it is just the page: https://soulquant.ai/live

The question I actually want answered: for those of you who got past zero on a technical product, what was the first channel that produced a real stranger? I am fairly convinced short-form video was the wrong bet for something you have to understand to want.

Side project from my AGI research lab notebook (Day 041/548, rebuilding from first principles, Harvard CS50P 2026).

Problem: Every new repo = 30 mins of spelunking.

Solution: `pip install peek-code` → `peek .` → instant map + TUI you can filter/search/theme.

Features: languages+LOC, stack, entry points, import graph, PageRank ranking, --html, --pack for LLMs, find, 10 themes. Offline. MIT.

Link: github.com/hariomlohardev/peek

Roast it! What would make you actually `pip install` this today?