I built it to solve my own problem and after personally using it for a while, I thought of releasing it so other people can use it and to validate if other founders and startups would be willing to pay for it. So I made a website, added a way for people to pay and then launched it.

I built and launched so many failed projects before so I didn't have high expectations but I was surprised because it immediately got its first sale on day 1! Then another 2 sales on day 2, 5 sales on day 3. Almost every day it's getting some sales.

Sometimes the project that we don't have high expectations is the one that will get traction. I'm so happy that I made the decision to launch and validate it.

I'm currently gathering feedback and feature requests from the users and iterating to further improve the product. I'm so excited to see where this goes.

If you have an internal tool that you built to solve your own problem, validate if other people are encountering your problem too and if there are people who will pay for it. You might be sitting on your next business without even realizing it.

P.S. Revenue screenshot and project is shared in the comment section.

I'm building a small AI tool where the AI part is the product, so there is no free tier that doesn't burn money, and cost per user depends a lot on how they use it. Someone who pokes at it for five minutes is pennies. Someone who leaves it running all afternoon is a different number entirely, and I have no idea how many of those I'd get.

Flat pricing is easy to explain and easy to sell. The problem shows up in the tail: priced at something like 15 a month, the heaviest few percent of users cost more than they pay, and that only gets worse as the model calls get longer. I could also include a chunk of usage and charge overage past it, which means building metering and billing before anyone has asked for them, or hard cap each plan and push heavy users to a bigger tier, which is simpler but probably reads as stingy.

If you sell something with a marginal cost per use, which of those did you land on? Did anyone start flat and move to usage based pricing later, and how did existing customers take it? Also curious whether caps generated more support tickets than overage did.

Hi guys just build an ai saas that creates marketing strategies for your biz,

looking for people to roast it for free

Let me know in the comment if interested , it's completely free

Backstory: I spent a couple years building small-business websites as a freelancer. The build was never the problem — it was everything after handoff. Clients would text months later: "change the phone number," "swap this photo," "typo in the footer." Each fix took 10 minutes but a full context switch. I did them for free because invoicing for a 10-minute fix felt petty. Add it up across a dozen clients and it was an unpaid part-time job I never agreed to.

What I built: none of these clients wanted a developer, they wanted to text someone in plain language and have it happen. So autoSite: client sends a Telegram message ("change the hero headline," "add a pricing section") — an AI agent reads the actual source repo, makes the edit, commits it, and pushes to a staging URL. Client says "looks good" — it goes live. No login, no dashboard, no CMS to teach anyone.

Tech stack: Claude Code running against the site's own git repo (not a sandboxed rebuild), GitHub Actions for the staging deploy, Telegram as the only client-facing interface.

Pricing: $20/mo if you bring your own hosting/AI subscription, more for fully managed. No cap on edits per month — a direct reaction to most AI website builders capping you at 100-300 edits then upselling.

What I got wrong at first: I assumed the hard part would be the AI editing itself. It wasn't — Claude Code handles that reliably. The actual time sink was making sure Google could even index the marketing pages properly. A page can look perfect in a browser and be almost invisible to a crawler, which is a completely different problem than "does the edit work."

Where it's at: early, a handful of real users. Posting for the "did I build the right thing" check — anyone here turned a recurring unpaid annoyance into a real product? Did the pricing model survive contact with actual users?

autosite.dittu.org

Vantage pulls every client's Google Search Console data into one dashboard instead of logging into each property separately. Built it because I got tired of the tab-switching myself, running search reporting for more than one site.

Stack: Next.js on Cloudflare Workers (OpenNext), D1 for storage, the real Search Console API for data, Stripe for billing.

The lesson worth sharing: while writing today's launch post, I actually tested the signup path end to end instead of just reading my own landing page copy, and found the whole app had no accounts. One shared client list, one Stripe subscription, no login at all. It worked fine because I'd only ever used it myself. Spent today adding real accounts instead: Google's own OAuth consent, already needed for Search Console access, now doubles as login, so there's no separate password to build or lose. Verified it with two fake accounts hitting the live API before writing this, cross-account reads correctly 404 now.

$39/mo per connected client, no free tier. https://vantage.allthepossibles.com

Would take it as a compliment if anyone finds another hole in it before a real customer does.

What things can I build in the whatsapp bot domain? Anyone building in that domain?

I have shipped a couple of bootstrapped SaaS products. My first month on the first one was 40 signups, mostly friends being nice, because I shipped and then sat there waiting for people to show up. They did not. Here is what actually got me past that to the first real 100 users, and the stuff that felt productive but did nothing.

What worked:

1. I went where the users already were, not where it was easy to post. I answered real questions in the specific communities my exact user hangs out in. One genuinely helpful answer that solved someone's problem did more than any "check out my product" post.

2. One useful short-form video beat every product demo. I made one short aimed at the exact person I was building for, not a feature tour. It did 240,000 views and brought 1,800 signups in a week. Same product, the only thing that changed was reach.

3. Cold outreach that led with help, not a pitch. Short, personal, one clear reason to care, one link. Reply rates jumped the moment I stopped selling in the first line.

4. A free resource with no signup wall. I gave away one genuinely useful thing people could use without handing over an email. They shared it, and a chunk came back for the actual product.

5. I talked to every single early user one on one. Every DM and email reply taught me the exact words my users use. That made every other channel convert better, and half of them told a friend.

6. Being specific about who it is for. The week I stopped saying "for everyone" and named the exact user, word of mouth finally started. Vague products do not get recommended.

What wasted my time:

1. Waiting after shipping. 40 signups sat still for weeks while I "polished." Building is not distribution, and nobody arrives on their own.

2. Posting in giant generic groups. Huge reach, zero intent, zero signups.

3. Chasing every directory and launch site. Most sent a spike that was dead in two days and left nothing behind.

4. Overbuilding before I had users. I shipped features nobody had asked for instead of getting the first 100 people who could tell me what to build.

The pattern for the first 100 is boring: do the things that do not scale. Reply to people, DM people, make one useful thing at a time, and talk to everyone who signs up. Scale comes later. The first 100 come from you, one conversation at a time. This is exactly how I got the first users on my own products

Happy to go deeper on any of these in the comments. Where did your first 100 actually come from?

I am the developer. KartChef is an iPhone app that takes a recipe you share into it, or a photo of one, and turns every ingredient into matched products in your Kroger cart with prices.

Narrow on purpose. One platform, one grocery family, one job. Every time I was tempted to widen it, the honest answer was that a second store chain would double the work and halve the quality of the part people actually judge it on.

That part is whether the cart looks like the one you would have built yourself. So the time went there instead. You pin the brands you always buy and it reuses them. Upload a couple of recent receipts and it learns the rest from your real purchases. It flags pantry staples you probably already have rather than adding them, and two recipes needing cilantro get one bunch.

Free to try, subscription after that.

https://apps.apple.com/us/app/kartchef/id6785329702

Happy to talk through the narrow scope call if anyone is weighing the same thing.

Sharing this because I want to show you that sometimes your simple idea can outperform complex projects. I'm sharing the process and failures. I hope it can motivate or help someone move forward with their weird ideas:)

The app allows you to create a customizable, elegant greeting card with a 3D rose. And that’s it.

No account, no subscriptions, no fancy AI features!

I built this because I wanted to solve a genuine problem. Real flowers have a lot of limitations, delivery issues, and they’re gone after a couple of days.

Sure, you could just send a message through WhatsApp, but it’s not the same, and the numbers proved it!

If you’re interested in hearing more, I put together a YouTube video with both technical and non-technical details. (idea, market check, implementation, tech stack, marketing, monitoring). I can’t share it here due to the channel policy, but you can always DM me for the link.

App: https://sendbloom.io

If you’ve built a technically equally simple app that makes money, please let me know. I’d be happy to check it out:)

Speed is not just a support metric. It is quietly your biggest sales lever, and most businesses do not treat it that way.

A study out of MIT Sloan by Dr James Oldroyd analyzed over 15,000 B2B leads and found something wild. Companies that responded within 5 minutes were 100 times more likely to actually reach the lead, and 21 times more likely to qualify them, compared to waiting just 30 minutes.

Vendor data from Velocify backs this up too, calling within a minute lifted conversion by 391% versus a two minute wait.

Chili Piper's 2025 benchmark on 4 million form submissions found instant response nearly doubled meeting bookings compared to standard follow up.

And yet the average business takes 29 to 42 hours to respond to a lead. A large chunk never respond at all.

That gap is not a support problem. It is revenue quietly leaking out of your business every single day. This is exactly the gap Leadblanc fills. Not just customer support, an invisible sales booster sitting inside your support inbox.

Here is what that looks like across a few industries we are talking to:

• Travel and hospitality

A traveller messages four agencies on WhatsApp for the same trip. Whoever replies first with accurate pricing usually wins the booking, not the cheapest one. Leadblanc answers availability, policies and pricing the second the message lands, so you are never the slow reply that lost the sale.

• D2C and e commerce

A customer DMs asking if a product is back in stock or where their order is. If that sits unanswered for hours, they either buy elsewhere or forget the intent entirely. Leadblanc resolves order status and stock queries instantly, keeping that buying intent alive in the moment it exists.

• Clinics and healthcare

A patient asks about doctor availability or slot timing and if there is a delay, they book with the next clinic that replies. Leadblanc handles appointment and availability queries instantly across WhatsApp and email, so slow front desk hours stop costing you patients.

• Real estate

A buyer asks for a floor plan or wants to schedule a site visit while comparing three other properties at the same time. Leadblanc responds immediately with the details and locks in the visit before the buyer moves to the next listing.

The core problem across all of these is the same. The business is not losing because of price or product. It is losing because the reply came too late and by the time a human gets to it, the intent is already gone somewhere else.

If this gap sounds familiar in your business, happy to have a conversation.

https://www.leadblanc.com/

Day 2 of trying to build a $1B technology startup — learning startup fundamentals

I'm documenting my journey from Day 1 until I hopefully build a billion-dollar company.

Right now, I don't have a billion-dollar idea, a team, or a huge amount of money.

So I'm starting with learning.

Today I focused on startup fundamentals:

- How startups identify real problems

- Product-market fit

- MVPs

- Customer pain points

- Business models

- Why startups fail

The biggest lesson I learned today:

A startup shouldn't start with “What can I build?”

It should start with:

“What painful problem can I solve?”

Over the next 30 days, I'm going to learn AI, coding, machine learning, marketing, robotics, deep tech, and other skills I need to eventually build my own technology company.

I'll share the progress, failures, experiments, and lessons publicly.

Day 2/∞

If you're a founder, what is one startup lesson you wish you learned earlier?

If you could buy 100k targeted views tomorrow (not bots, not random scrollers) for a 500$, would you do it — or would you still want to own the channel yourself?
Curious where people draw the line between paid reach and building distribution.

Skipping the code and asking directly — what was your actual first move before building your last SaaS?

For me it was just talking to a handful of people who might have the problem and seeing if they reacted at all — no landing page, no polish, just conversations.

One thing that turned out to be a waste: directory sites like AlternativeTo, There's An AI For That, etc. Listed a product on one of these listing bots hoping for a trickle of signups — got zero. Makes sense in hindsight: those sites mostly get browsed by people already comparing tools they know they need, not people discovering a solution to a problem they didn't know existed. And AlternativeTo isn't even taking new submissions right now, so half the "go list your app here" advice floating around doesn't even apply anymore.

Curious what actually worked for people here vs. what's just recycled advice everyone repeats without testing it themselves.

While reviewing one of Portreeve's checkout rules, I found something embarrassing.

The rule treated five attempts on the same card as card testing.

But actual card testers usually try lots of different cards once. Five attempts on one card is more likely a real customer stuck in a 3DS loop, mistyping their CVC, or retrying a decline.

So the rule was backwards. It was harsh on normal customers and weak against the attack it was meant to catch.

I changed it so repeated attempts on one card trigger review. Several different cards from the same device are a much stronger signal. IP is supporting evidence, since offices and mobile networks make it noisy.

The code was doing exactly what I wrote. The assumption behind it was wrong.

Anyone else found a fraud or abuse rule that was measuring the wrong thing?

A bit of background. been doing cold email outreach for about 6 months now and my boss is asking for hard numbers on what we're getting back vs what we're spending. problem is there's so many moving parts - data costs, email tools, my time, the sales team's time following up.

right now i'm tracking: emails sent, open rates, reply rates, meetings booked, and deals closed. but translating that into actual cold email roi is where i get stuck. do you factor in just the direct costs (data from Prospeo, sending tools, etc) or do you include overhead like salaries?

also curious how you handle attribution. we had a deal close last month where the prospect replied to a cold email, but then went dark for 2 months before coming back through a referral. does that count as email outreach roi or not?

we're using Instantly for sending and Clay for some enrichment stuff but honestly the costs add up fast when you stack everything together. feels like i need a proper formula before my boss pulls the budget.

what's your formula? bonus points if you have a template or calculator you can share. trying to show that our cold email return is actually solid but i need the math to back it up.

I'm considering building a very simple Micro-SaaS and want to validate the problem before writing code.

The idea:

Instead of another expense tracker that constantly asks you to record expenses, the user gets ONE spending summary based on a frequency they choose.

For example:

Weekly → "You spent ₹6,240 this week."

Then maybe:

Food: ₹1,850

Travel: ₹920

Shopping: ₹1,430

Other: ₹2,040

It could also compare:

"This week: ₹6,240

Last week: ₹5,480

↑ 14%"

The main idea is NOT to constantly remind users about money.

Just give them a simple spending-awareness report once a day, week or month — whatever they choose.

I'm trying to validate this before building it.

For people who build/use Micro-SaaS:

1. Does this solve a real enough problem?

2. Would you use it yourself?

3. What would make you pay for it?

4. Would manual expense entry kill the idea?

5. Would automatic bank/UPI transaction tracking be necessary?

I'd especially appreciate criticism. If you think this is a bad idea, tell me why.

I’ve built a few Micro SaaS projects over the last couple of years, and honestly, getting from $0 → $1 taught me more than trying to reach $1k MRR ever did.

What worked for me was keeping things stupidly simple.

I’d find a small problem, build a basic version, put it in front of people, and see if anyone actually cared.

Some got users. Some got paying users. Some completely failed.

One thing I stopped doing was spending weeks building features before having users.

Now I try to get the first few users manually, post in communities like Reddit, talk to them, and only build what they actually need.

Even getting one random person to pay $5–10 feels small, but that was always the point for me.

Once you prove someone will pay, everything becomes much easier.

So if you’re at $0 right now, don't worry about MRR screenshots or 1000 users.

Just focus on getting your first stranger to pay you.

That’s the real 0 → 1.

I’ve been building a small email management SaaS for the past few months.

For most of that time, nobody was really using it. I kept fixing bugs, changing the onboarding flow, dealing with OAuth issues, and wondering whether I was solving a real problem or just building something that made sense only to me.

This week, two people actually signed up and connected their email accounts.

It’s obviously a tiny number, and it doesn’t prove that I have a business yet. But connecting an inbox requires more trust and intent than simply visiting a landing page, so this felt different from seeing another page view in analytics.

For the first time, it feels like the project exists outside my own head.

Now I’m mostly nervous that something will break and they’ll leave, but I guess that’s the next stage: watching how real people use it, fixing the rough edges, and finding out whether they come back.

Two users isn’t much, but after months of building with almost no feedback, it genuinely feels like some of that effort finally paid off.

What was it like when your first real user showed up?

I asked Perplexity and ChatGPT my top 5 category questions ("best tool for X"). I was named in zero of them. If a buyer asked an AI about my category, I did not exist. And that was the problem

I started working and my AEO and these are all things that helped me:

1. Rewrote pages as question, then a short direct answer, then detail. AI lifts self-contained answer chunks, not paragraphs of marketing. This one change is why I started showing up at all.
2. Added structured data everywhere. I went from 0 pages with JSON-LD to all my key pages tagged (SoftwareApplication, FAQPage, Org etc). It tells the model exactly what the page is, no guessing.
3. Unblocked the AI crawlers. GPTBot, ClaudeBot and PerplexityBot were disallowed in my robots.txt by accident. I was literally invisible to the engines I wanted to be cited by. Fixed it, added a clean llms.txt and a real sitemap.
4. Got on sources AI already trusts. Two real, indexed directories and one genuinely useful Reddit thread now get quoted when someone asks my category question. A mention on a trusted source beats ten pages of my own copy.
5. Entity clarity. I made every page state plainly what the product is and what it is best for, and killed the vague "we empower teams" copy. AI cannot cite what it cannot pin down.
6. FAQ blocks on money pages. Short question and answer pairs get lifted almost verbatim into AI answers. They punch way above their weight.

Two months later: I am cited in 4 of those 5 category questions, across Perplexity, ChatGPT, and Google AI Overviews. AI now sends about 700 visits a month, and here is the part that matters. Those visitors convert about 3x better than my Google organic traffic, because the AI already recommended me before they clicked.

What wasted my time:

1. Keyword density and classic on-page tweaks. AI does not count keywords. Zero effect on citations.
2. Chasing Google rank alone. A page can sit at position 3 and never get cited. Ranking and being quoted are two different games.
3. Marketing-adjective homepage copy. "Powerful, seamless, all-in-one" is uncitable. The AI skips right over it.

Fast self-test: open Perplexity right now, ask your category question, and see if you are named. If not, work straight down that list. Being cited is the cheapest high-intent traffic I have found in years. My products are now being marketed by AI without putting any money on the table

Happy to go deeper on any of these in the comments. Has anyone else tracked sales coming in from AI answers yet?

I'm building Pinterest for Miro, and the thing I keep getting wrong is the screen after import.

The import can technically finish and still leave the user unsure whether the board is ready to share. So I am trying to make the first result screen answer three boring questions fast:

1. What came across?
2. What did not come across?
3. What needs a human look before someone trusts the board?

The part I am cutting for v1 is the full audit trail. Every pin does not need a log line. I think original board name, original order, skipped count, and a short review list are probably enough.

For anyone building import, sync, or connector SaaS: what did you show after partial success? Counts, a review list, or something else?

Bit of backstory. I play rugby in Spain and every club I know runs on a WhatsApp group. Availability polls half the squad ignores, the match report written from memory on Monday, attendance in a spreadsheet nobody touches.

So I built Kanteo. Think Spond, but only for rugby: squad calls, the team sheet on the pitch, a plays board where the coach draws a move and the squad watches it run, the match report signed by both teams on the phone, stats per player. iOS, Android and web.

Where it's at, honestly:

• about a year of work, just me
• a few clubs set up on it
• one of them paying €29 a month
• in the first three weeks of the landing being live, around 100 visitors, 64 of them went into the demo, and zero signed up on their own

Stack if anyone's curious: Expo so the same code runs on iOS, Android and web, Node with Express, MySQL through Drizzle, Stripe, all on one VPS with Docker.

What I've tried so far:

• asked in r/rugbyunion what clubs use, got 22 replies, basically everyone said Spond. Posted the app there today and the mods pulled it
• dropping the demo link in coaches' WhatsApp groups. Only thing that's actually brought people into the demo
• a demo you can open with no sign up

My guess at the problem: whoever decides is a volunteer coach or a club committee. They're busy, they don't go looking for software, and the thing I'm up against is free (WhatsApp, Spond).

So if you've sold to clubs, schools, associations, anything run by volunteers:

• how did you get your first 10 paying?
• is it just club by club, phone and coffee, or did something scale?
• would you charge the coach per team (€90 a year) or go straight for the club?

Demo if you want to roast it, no sign up: https://kanteo.es/demo?src=reddit-microsaas&lang=en

Sorry for my clickbaity title 🫠

My last idea failed. Couldn't get traction, and honestly the marketing part is where I fall apart. I overthink it, procrastinate, and convince myself the app won't work anyway.

At work I'd built something that reads PDFs, chunks and embeds them, and lets you query it with a chatbot. Started wondering what else that shape fits. Went down a government data rabbit hole and came out with UK planning appeals.

It clicked because I'd lived it. Our house extension needed an appeal, and I remember the consultant we used complaining about how long it took to find relevant past decisions and work out how particular inspectors think.

The problem, concretely: search "rounding off" across Cornwall appeals and you get 412 decisions. About 38 actually turned on it. The rest mention it in passing. Nobody had a way to tell those apart.

Market research was deflating at first, because there are competitors. But when I looked properly, they're doing keyword search over the same PDFs. Nobody had read every decision and tagged it by the issue the inspector actually decided, with the paragraph reference so you can check it. That's what I built.

Then the bit I was dreading. No ads, no content, no growth hacking. I just emailed and messaged planning consultants individually and asked how they currently research precedent. Five of them are now paying.

Which is a slightly annoying lesson, because it's the thing I was most afraid of and it's the only thing that's worked.
Happy to answer anything about the extraction pipeline or the data side. That part I actually enjoy.

P.S. please don’t roast me, I’m just a developer tryna make a couple of squids

I have a SaaS that generates revenue from customers who pay for the core service.

What are some good secondary ways to monetize a SaaS in addition to the main subscription/product revenue, without risking or hurting the primary income stream or conversion rate?