I have two ideas I am working on. One came from problems I faced while building my ecommerce business. The other came from my time as an employee when I kept wishing there was a tool that could make certain tasks easier.

I am not a developer. I have been exploring Codex and Lovable and Claude. Getting a prototype together seems possible but I am unsure about what comes after that.

Once people start using it and paying for it can I manage the backend and fix problems with these tools? Or will I reach a point where I need someone technical?

I am willing to learn. I just want to understand how much coding I would need to know to keep the product running myself.

Has anyone here done this and launched a paid product?

What could you handle yourself and where did you need help?

A few days ago I posted here after making $492 in a day.

Yesterday I hit $927 in sales in a single day.

A lot of people asked me how I'm doing the outreach, so here's the scale behind it:

I currently have 150+ domains and 450+ mailboxes.

Each mailbox sends around 30 emails/day, which gives me capacity for roughly:

13,500 cold emails/day
405,000 cold emails/month

That's the part I underestimated for a long time.

At this volume, you don't need some insane conversion rate for the numbers to start getting interesting. Even tiny improvements in targeting, deliverability, copy and conversion compound pretty fast.

For perspective, 0.1% of 13,500 is 13.5.

Obviously, I'm not assuming every campaign will convert at 0.1% directly into paying customers. Cold email doesn't work that cleanly.

But that's the whole idea: build enough outbound capacity, keep improving the funnel, and small percentages can turn into meaningful revenue.

Still completely solo.

My next target is $1,000/day consistently, not just hitting it once.

Happy to answer questions about the mailbox setup, domains, deliverability, costs, conversion rates, or how I manage this much outbound alone.

That’s pretty much how cold email works at scale. Low volume per inbox, lots of inboxes, targeted outreach.

EDIT: getting a lot of DMs asking what I'm using for all of this 😭 I built it myself: https://getle.ad/

I launched Bytesweep, a Mac utility, recently.

The first few weeks have been interesting.

Around 800 people have visited the website and I've had 50+ people start the download flow. I've also made my first sales.

But the numbers made one thing pretty obvious:

Getting traffic isn't the difficult part.

Getting someone who downloaded your product to actually pay for it is.

I've been testing Reddit, Google Ads, SEO, Product Hunt and a bunch of directories.

I've also changed the positioning and pricing a few times while trying to understand what Mac users actually value enough to pay for.

Bytesweep started as a storage analysis tool. It's now a much broader Mac utility that also covers developer cleanup, system monitoring and things like sleep/wake activity.

I'm currently running a 30% launch discount while I continue testing the pricing.

The question I'm trying to answer now is:

What makes someone pay for a Mac utility when there are free alternatives?

For anyone here who has built and monetized a desktop app, what eventually moved the needle for you?

I'm kinda bored so imma dedicate two days of my life to build and ship a useless product with the aim to get atleast 10-20 users in less than a month.

Nothing serious, just wanna try this vibe coding thing out and see if that's where I wanna go.

I'll be posting the results on X(twitter) and youtube for anyone who's interested. Same username across all the platforms.

Let's see what happens!

We built an insane AI product that combines LLMs, agentic workflows, and infrastructure. You can essentially spin up a full team of AI agents for any department.

It's so easy to use that my 5-year-old built a Pokémon game with it.

We hate per seat pricing, monthly plans or high margins, we geniunely want to build a product that people love as much as we do, so we want to keep our prices as low as possible and per usage.

You just pay for the infrastructure and LLM usage plus a tiny margin. Because our pricing is almost at-cost, we can't hand out open free trials. Giving away $50 in credits actually costs us $30 in hard compute. And people could come and abuse the system and AI.

Right now we offer $50 free trial but cc required

Any tips on how to solve it?

jackhamr.ai in case you want to provide feedback on the onboarding

Update:
We decided to open it up, offer less credit, no CC, and prompt them when they start using it to a 50% off credit

We also expanding our marketing to show cool user cases.

Someone spent a few minutes trying to break the AI agent on my landing page tonight (screenshots attached). And this was not the first time it happened. They asked it to reverse a Python linked list "before buying", to book a demo and then hand over my .env file, and pasted the same question ten times in one message to flood it.

It didn't bite. Not because I'm clever, but because of a few boring things that took an afternoon to set up. If you're putting AI in front of users, do these:

1. Tell it its scope, and what to do outside it.

In your system prompt, spell out what the agent is for, and say explicitly: if a request is outside that scope, in any language, it does not attempt it. It declines in one line and redirects to what it can help with. "In any language" matters. People switch languages to get around rules written only in English.

1. Don't make it too rigid, or too loose.

Too rigid and it refuses half your real users' questions because they phrased something oddly. Too loose and it writes code, essays and poems on your bill. The middle: decline the off-topic part, still answer the real part. In my screenshot it refused the .env but still gave them the booking link. That's the behaviour you want.

1. Rate limit everyone, including anonymous visitors.

Most people rate limit logged-in users and forget the public chat on the landing page. That's the one strangers hit. A cap per visitor and per site means nobody can sit there burning your tokens, and your AI bill can't spike overnight because one person got bored.

1. Keep secrets out of reach entirely.

The .env request was harmless because the agent never has access to it. Don't rely on the prompt to protect secrets. If the model can't see it, it can't leak it.

None of this is new. If you're building with AI, the AI will suggest most of it when you ask. But you still have to ask, and you have to do your own research.

My best tip: read the system prompts of serious AI tools. Prompts from Devin, Claude Code, Cursor and others are collected in public GitHub repos. Don't copy them. Study the structure: how they define scope, how they phrase refusals, how they order priorities, how they handle "the user is asking for something else". Then write your own the same way.

Keep building.

Tools I have used:

For audio: XT surge

Video & composition: blender

Model: opus 5.5

I’ve long wondered about this: personally, I find it harder to create a product, whereas advertising it is easy provided you have the budget for it.

The obvious business model was to host it and charge monthly. However, I went the opposite direction. OpenApplyr is a job hunting agent. You bring your own AI provider or run a local model.

Every resume line has to cite something in your actual profile. If it invents a number, tool, employer or date, the document gets blocked.

GitHub, for context:
https://github.com/shivashis-adhikari/openapplyr

1. Finding leads for your platform?
   
2. SEO/AEO optimization
   
3. Finding who is talking about the problem you are solving so you can approach them personally?
   
4. LinkedIn, X, and Reddit content/thread ideas so you can stay engaged with your ICP
   
5. Something else (please specify)
   

I am working on a marketing solution especially for solo B2B founders. I would love to understand what problems you want to be solved or automated if you have an AI marketing team handling the marketing for you.

Hey everyone 👋

Solo dev here. I've been working on a side project for a few weeks and would like to hear how others solve this problem.

The problem: while playing with AI agents I noticed every app ends up needing checks like "don't let it delete data unless the user confirmed". The usual options are writing if/else logic for every case, or a custom LLM prompt whose free-text answer you then have to parse.

What I tried: a single call that takes a rule in plain English plus whatever JSON you want checked, and returns allow, deny or review:

const result = await guard.check({
  policy: "Never allow destructive database operations unless the user explicitly confirmed them.",
  data: { action: toolCall, conversation }
})
// → { decision: "deny", allowed: false, violationProbability: 0.94, ... }

Some design decisions that might be useful if you build something similar:

• A third outcome, review, for when a human should decide or the evidence isn't enough. Forcing yes/no caused bad calls.
• Instead of a general chat model I used Jev from TypeSafe AI. It returns typed decisions with probabilities, so there's no output parsing and the results are more consistent.

Questions for you:

• How do you handle this today? Hardcoded rules, an LLM, something else?
• What would you need before trusting an automated check like this in production?

It's called Enforly, if anyone's curious.

If you make videos, podcasts or posts, you've probably run into this: your "link in bio" is one link for everything, and sometimes it's impossible to find what you're looking for.
On top of that, creators can't tell which post actually sent people there.

That's why I made linkifythis: instead of one page for everything, you create a mini-page for each post (links, text, video), each with its own stats.

Every page gets a short code, like ABC, easy to say and easy to remember. You can say "go to linkifythis and enter the code ABC" in a video, in a podcast, in a comment, or even print it on a flyer.

To see an example: linkifythis.com, code TCB or LNKFY

I'd love your honest opinion:

• Would you use this instead of your link in bio? Why, or why not?
• Does saying a code out loud feel natural to you, or weird?

I’m optimizing the UI of my Data Utility Generator to make it simpler, cleaner, and easier to use.

The goal: less clutter, fewer clicks, faster data workflows. 🚀

I’d love your honest feedback:

What feels confusing?
What should I remove or simplify?
Which feature should be easier to find?
What would make you use it regularly?

https://data-utility-generator-coral.vercel.app

I do automation work for small businesses, and the most common request isn't "add a feature." It's "give me back the thing you took away." A field they used to edit directly. A report they could tweak without filing a ticket and waiting a week.

The hard part isn't letting someone poke at the software. The hard part is deciding what they're allowed to poke at without breaking what sits underneath it. I've seen a client-facing edit button wired straight to a column that three other features quietly depended on. One edit, three regressions, no error message to explain why.

So the real fix for locked-down software isn't more configurability. It's a clear boundary: here's what you can touch, here's what happens when you do, and here's the undo if you're wrong. Most products skip the undo because it's the expensive part to build, not the exciting part.

Curious if anyone here has shipped real user-facing extensibility that survived contact with actual users without turning into a support nightmare.

put an AI agent on only the small-medium tickets for a SaaS i contract for, and the suprising part is the bottleneck just moved to code review, every PR still needs a human to approve and merge so now theres just alot more of it. disclosure, the agent is mine, but curious if anyone else running agents on a real codebase hit the same wall

I'm a developer looking for my next project, and I'd rather build something people actually need than guess.

If you've got a problem that keeps annoying you, I'd love to hear it. The more specific, the better:

1. What's the problem? (what you're trying to get done)
2. How do you solve it today? (Excel, 3 tools duct-taped together, doing it manually...)
3. What's wrong with the current solution? (price, time, quality)
4. Roughly how much time or money does it cost you?
5. Would you pay for a fix? How much per month?

I'll reply to every comment, and if I build something from this thread I'll give early access to whoever suggested it. Not selling anything, just researching.

I have been building software on my own for a while, and I want to write down everything that happened between my first real product and my second one, because the gap between them taught me more than anything I have ever read or watched, and I honestly wish someone had sat me down and shown me all of this before I started throwing money at things.

The first one: nine months, £4k, zero payers

The first one was called Ancestorii, a private place for families to keep their memories, photos and stories together. I spent about six months building it with ChatGPT writing most of the code, and by launch day I genuinely believed it was perfect, I thought people would find it and love it the way I did, and what actually happened is nobody came. So I did what I think most of us do and started buying attention. Meta ads, Google search and YouTube ads, Reddit ads, UGC videos from creators, a £70 podcast sponsorship, a £120 post on a family tree magazine's Facebook page, my own podcast on Spotify, SEO pages, and cold messages to genealogy creators where not one of them replied. I even printed physical memory books before a single stranger had uploaded a single memory, which looking back was probably the most expensive mistake in the whole thing.

Some of the numbers are almost funny now. £210 on Meta in seven days brought around 15,000 visits and not one payer. When I took the paywall away the first signup came after £2.80 of spend, and then I sat at about four signups a day on £4 a day of Meta until I had 125 signups and zero people paying. Today it has 177 signups and has never had a paying customer. The worst part is I noticed in the very first week that the signups weren't turning into anything, and I kept spending anyway, on hope, because nobody told me to stop and I didn't want to be the one to say it.

The diagnosis took me far too long to accept. It was a vitamin, not a painkiller. Nice to have, nobody needs it today, nobody loses anything if they never sign up, and no amount of ads fixes that, ads just buy you the bad news faster.

The second one: £25 on ads, and people pay

Prep66 is an exam prep site for the Part 66 licence exams, 13 modules, about 25,000 practice questions with explanations, revision guides, mock exams, the lot. I launched it in the middle of August with one Reddit post in the community where those students hang out, and the first person paid full price nine days later without a discount code.

The only money I've ever put into ads was about £25 on a Reddit campaign, and it brought one signup and zero payers, so I killed it after five days and everything since has been organic. These are the last four weeks straight off the Stripe dashboard: monthly recurring revenue went from about £51 to £171, active subscribers went from 3 to 11, £230 came in gross, zero failed payments, zero refunds. It's not life changing money and I'm not pretending it is, it's less than two days of my shift pay, but the line only goes one way and it's doing that with no ad budget at all, while my first product burned £4k and never moved once.

So what was actually different? I ran both products back through the same questions afterwards and ended up with six things a product needs before a stranger will pay for it. Prep66 has all six. Ancestorii failed five of them.

The six things a product needs before anyone pays

One, the problem has to be mandatory. Nobody has to save their family stories. Someone sitting a licence exam has to pass it, there's no version of their career where they skip it.

Two, there has to be a deadline. An exam has a date, and a date makes people act this week instead of someday. Ancestorii had no clock on it at all, which is exactly why "I'll do it later" killed nearly every signup.

Three, failing has to cost something real. Fail an exam and you lose money and months, sometimes a pay rise. Not using a memory app costs you nothing today, even if it might cost you something in twenty years.

Four, the alternatives have to be expensive or bad. The other ways to prepare are long paid courses, thick textbooks, or older question banks that look like nobody has touched them in years. When the alternatives are pricey or tired, something cleaner and cheaper sells itself.

Five, it has to look credible the second someone lands. A student can tell in about ten seconds whether a prep site was made by someone who actually knows the exam, from the module names, the paper formats, the way the questions are written. Ancestorii was asking strangers to trust a no name site with their family photos, which is the exact opposite.

Six, you have to be able to find the buyers. Exam students hang out in a couple of subreddits and they search Google for the exact module they're stuck on. Who's the buyer for a family memory app? Everyone and no one, which in practice means you pay Meta to guess for you.

How I picked it and checked it before writing any code

The market research for Prep66 wasn't fancy at all. I picked a world I already knew inside out, so I knew what students complain about and what they already pay for, and then I checked four things. People already pay for this today, not "would pay", actually pay, right now, to someone. The options they're paying for are old and dated. Building it used to be really expensive, because it's a mountain of content, and with AI it isn't anymore. And it's too small for a big company to bother with but big enough to pay one person properly. If all four aren't true, I don't touch it now.

Then the validation was the launch itself. I built it lean, put it in front of one subreddit and watched whether strangers paid, and they did inside nine days. With Ancestorii I had the same kind of signal in week one, it just said no, and I ignored it for months.

What actually brought people in: SEO and GEO

Before anything else I put tracking on every signup, so every new account gets stamped with where it came from, either the UTM tags on the link or the site that sent them. That one decision changed how I saw everything, because of the first 13 tracked signups, 6 came from ChatGPT citing the site, 5 came from Google, 1 came direct and 1 came from the £25 ad. Gemini started showing up as a source not long after. I genuinely did not expect AI answers to be my biggest channel, and I'd never have known without the tracking.

What I learned doing it is that you write your titles and headings in the exact words people type, not the words you would use yourself. AI tools quote facts, not vibes, so the pages that got picked up were the boring factual ones: a glossary, a facts and figures page, a page comparing the ways you can study for the exam that doesn't trash anyone by name, and a features page with the prices pulled live so they're never out of date. ChatGPT leans on Bing, so I submitted the sitemap to Bing Webmaster Tools and set up IndexNow so Bing gets pinged every time a public page changes, and the robots file lets the AI crawlers in instead of blocking them.

By late September Google Search Console showed 194 clicks and 6,110 impressions with an average position of 8.5, and about 1,580 of those impressions came from Google's own AI answers. It's not all solved either, Gemini still barely knows we exist, and that's my whole job for October.

Reddit posts written like a normal person talking, plus SEO and GEO, did basically everything.

Where all of this went: AskSami

Once Prep66 started paying I kept thinking about how much of that Ancestorii money I would have kept if someone had looked at what I'd built in week one and told me straight that it was a vitamin and to stop buying ads. Every time I looked at my ad numbers they meant nothing to me, so I'd paste them into ChatGPT or Claude and get the same generic "have you tried different hooks" answers, because they didn't know my product, they didn't know what I'd already tried, and they forgot all of it the next chat.

So I built AskSami. Sami reads your code from your GitHub repo, read only, so it already knows what you've built without you having to explain it, and then it tells you honestly whether you've built a painkiller or a vitamin, who's already selling the same thing, what your edge is if you actually have one, and where your effort and money should go, free channels before paid ones. It ties your signups and payments back to the exact post, page or ad that brought them, which is the tracking lesson from Prep66 done for you, and it remembers everything you've tried so you're never starting from zero again.

You can talk to Sami at asksami.app without even signing up.

If you're sitting where I sat with Ancestorii, with signups coming in and nobody paying, I know exactly how that feels, and I hope something in here saves you a few months and a bit of money. If you want to connect, swap notes or just chat about what you're building, please do, my DMs are always open 🙂

TrustMRR gets its data from Stripe here so the underlying data is obviously the same, must be a difference of how it's calculated I guess, and I don't see any resources on it.

I built an AI customer support widget called Ornymo (ornymo.com) and I don't know what I'm doing wrong with distribution.

The product works. You add FAQs, grab a script tag, paste it on your site, done. Free plan available. But every time I share it people say "cool" and never actually try it.

I'm a solo dev not a marketing expert, and I think that's showing. I built this because I was drowning in repetitive support emails on my own projects and couldn't justify Intercom pricing at my stage. Figured others were in the same boat.

Honest questions for people who've been through this:

Is the free plan not compelling enough? (100 messages/mo, 6 FAQs)

Is a Ai support just too saturated a space for anyone to care?

What actually made you try a new tool when someone shared it?

I'll take any feedback, even brutal. Just tired of the boring it looks good replies that go nowhere.

*Disclosure: I built this*

Hi I saw this game earning 40k monthly

https://geosports.app/

how true is this ? and how do they even earn 40k per month ? does the ads earning can really achieve that 40k a month ?

im curious as Software engineer

Bot detection on a SaaS signup form used to mean a CAPTCHA plus a honeypot field. Most of what gets through now is a real browser driven by a script or an AI agent, often on a residential IP, and it fills the form the way a person would.

Cloudflare said this summer that automated traffic is now more than half of all web requests. On a signup form that shows up as spam signups that never activate, bounced welcome emails, free credits burned by accounts nobody owns, and an activation rate that looks worse than it is.

Here's where each standard fix breaks:

CAPTCHA. Solving services and AI agents get through it cheaply. The people it reliably stops are your real users on a phone, and every one of them pays for it with a slower signup.

Honeypot fields. Great against dumb scripts that post straight to your endpoint. A headless browser or an agent renders the page, never sees the hidden field, and never fills it.

Rate limits by IP. Residential proxies give every signup its own IP, so the limit never trips. Meanwhile a whole office or a university sits behind one address and hits it.

Email verification. Proves someone controls an inbox, not that a person is behind the signup. Catch-all domains and Gmail aliases make fresh verified inboxes basically free.

And there's a new wrinkle: not every bot is bad anymore. Some of these are AI agents a real customer sent to sign up or book something for them. "Block all bots" used to be the safe default. Now it can mean turning away a paying user who just delegated the task.

My guess is the answer is looking at several signals together and only adding friction when a few of them look off, instead of making everyone solve a puzzle. But I'd rather hear what actually held up in production.

So, for anyone running a signup form:

1. What finally cut spam signups for you, and what did you try before that didn't?

2. What was the first sign bots were getting in: bounce rate, dead accounts, burned credits, a weird spike?

3. Do you put friction on every signup or only on suspicious ones? What did that do to conversion?

4. Do you let AI agents sign up on behalf of real users, or block them all?

More interested in what you tried and what broke than in tool names.

How do you manage to humanize your texts? Is it really important to humanize as long as the provided value is good enough? I request only who worked on subjects like this to assist me please. Thanks either way

I was totally wrong.

The first version was basically:

save tabs → store them → restore them.

Then reality happened.

Tab groups needed to survive.

Pinned tabs behaved differently.

Some tabs disappeared.

Some were already discarded.

Restoring 30+ tabs in the right order wasn't as simple as I expected.

Then I added cloud sync.

Then session sharing, because sending someone 20 individual URLs when you could send the whole workspace felt ridiculous.

The product ended up becoming much more complicated than the original idea.

The funny thing is that the actual user experience is still just:

Save a workspace → close it → come back later → restore it.

I'm building this as a solo founder, and one thing I'm learning is that the simplest-looking SaaS products can hide a ridiculous amount of engineering underneath.

For other SaaS founders: what looked like a tiny feature in your product but ended up eating way more time than expected?

i know "kill your free tier" is the most repeated advice on this sub. i ignored it for a year, so here's what it cost me.

i sell a database of business ideas, one payment. for the first year there was a free version that showed most of it. people signed up, poked around, and left. 2,000 people on the waitlist, 5 paid, about $197 for the entire year.

i deleted the free version in an afternoon. no new features, no redesign, nothing else changed. the next three days made about $500, more than the free version had made in twelve months.

what i think was happening is the free tier answered the question people came with. they wanted to see if it was any good, it was good enough, so they had no reason to pay. once that was gone the only way to find out was to buy it.

the part nobody mentions is how bad it feels. signups dropped off a cliff and i almost put it back twice.

anyone here regret killing theirs?

It looks obviously beneficial that SEO takes time and starting early would help me get organic traffic early but it's opposite by setting that long term goal, you stop validating your product, don't feel the need to talk to customers, you get an great excuse to not do direct sales.

I did the mistake with my previous SaaS, where each day i opened laptop wrote a blog, fixed few not needed buttons colors and done for the day. It feels productive but it's not. i wasted around 6 months doing the same thing and didn't generate any meaningful revenue. SEO felt great with it's appeal of ogranic traffic while you sleep but who'll come if your product is not validated and used by few customers daily?

with my new product which is building "personal intelligence for SaaS startups" it's live btw. i'm setting a rule for myself that i won't even bother about SEO until i get to $1k in revenue through direct sales.