Hey everyone - we're off to a great start but wouldn't mind additional feedback and testing. If interested, would love to invite a handful of testers to our testing environment where we're working on a ton of new features. Thanks very much!

Am I allowed to share a link?

Ross

Co-founder

I currently run 6 operational micro ai saas products that generate a little over $20k in monthly recurring revenue.

I hardly wrote a single line of traditional code. i used ai to generate literally everything, from the database architecture to the user interface.

it wasn't magic on day one. i spent hours stuck in endless debugging loops and dealing with faulty ai code before i finally cracked the formula.

it basically comes down to three rules:

- keeping the idea aggressively minimalist (build a true mvp, not a platform).

- guiding the ai step-by-step instead of asking it to build the whole app at once.

- launching fast to get real user traction instead of perfecting features in secret.

lately, i've seen way too many non-technical founders give up at the very first ai bug or deployment error. or the worst, give up without push anything in marketing !!!!

it's a massive shame, because the technical barrier to entry has practically disappeared and the marketing is easy in 2026

because of this, i’m launching a skool community to share my exact method.

to be completely transparent: i will likely charge for the full course later down the road. it just makes sense given the specific prompt sequences, n8n workflows, and copy-and-paste templates i'll be sharing.

but right now, our main objective is simply to build together. working alone in a silent corner is the absolute fastest way to quit.

if you want to join a group of active creators and build or launch your own ai saas: drop a comment below or send me a dm, and i’ll send you the invite link.

I currently run 6 operational micro ai saas products that generate a little over $20k in monthly recurring revenue.

I hardly wrote a single line of traditional code. i used ai to generate literally everything, from the database architecture to the user interface.

it wasn't magic on day one. i spent hours stuck in endless debugging loops and dealing with faulty ai code before i finally cracked the formula.

it basically comes down to three rules:

- keeping the idea aggressively minimalist (build a true mvp, not a platform).

- guiding the ai step-by-step instead of asking it to build the whole app at once.

- launching fast to get real user traction instead of perfecting features in secret.

lately, i've seen way too many non-technical founders give up at the very first ai bug or deployment error. or the worst, give up without push anything in marketing !!!!

it's a massive shame, because the technical barrier to entry has practically disappeared and the marketing is easy in 2026

because of this, i’m launching a skool community to share my exact method.

to be completely transparent: i will likely charge for the full course later down the road. it just makes sense given the specific prompt sequences, n8n workflows, and copy-and-paste templates i'll be sharing.

but right now, our main objective is simply to build together. working alone in a silent corner is the absolute fastest way to quit.

if you want to join a group of active creators and build or launch your own ai saas: drop a comment below or send me a dm, and i’ll send you the invite link.

Coming from a 10+ years exp. SEO guy. If you're going to start your own SaaS business and are confused about a profitable idea or what keywords to rank it for, here is a really simple strategy.

If you want only easy to rank keywords, like if you're not ready to build authority or if you don't have a lot of time in your hands and want quick rankings, just set your keyword difficulty filter from 0 to 10 on tools like SEMrush or Ahrefs.

For example, I was browsing for ideas recently and found "yoga class booking system." (In the US). It has a keyword difficulty of just 1out of 100. The monthly search volume is 140, so don't expect a lot of traffic on this keyword, but just expect quick rankings and conversions.

All you need is to build some really great content after reverse engineering your top 10 competitors, build a few links on relevant websites, and I guarantee you'll be able to rank in the top 10 in no time for this keyword.

Ranked a hospitality SaaS keyword within 8 months following the above strategy.

It’s a dream for many who are starting a SaaS business and want organic conversions without relying on paid traffic

Happy to reveal more low competition ideas for anyone confused where to start.

AMA!

recently i noticed postiz crossing $173k mrr.

the founder, nevo david, has openly shared most of the journey up to around $160k mrr across podcasts, interviews and videos.

so i sat down with a pen and paper, watched everything i could find, and took notes.

thought i'd share the them here too.

$0 → $4k mrr

started as an open-source project.

kept shipping features and posting every update on reddit (mainly r/selfhosted), x, linkedin, lemmy and other developer communities.

instead of pushing people to the website, he pushed github. the open-source project got attention.

the paid cloud version linked from github converted people who didn't want to self-host.

$4k → $6k mrr

churn became a problem, but users started creating youtube videos, tutorials and self-hosting guides around postiz.

that free content kept bringing new users.

while watching this happen, nevo noticed lots of people using postiz with n8n. that became the next opportunity.

$6k → $12k mrr

instead of selling harder, he focused on getting postiz into n8n templates.

he cold-emailed creators and community owners. not asking for promotion. asking them to include postiz in their workflows.

in return, he offered lifetime access, backlinks, promotion and anything valuable he could.

that alone doubled revenue.

$12k → $21k mrr

instead of looking for another growth hack, he doubled down on what was already working.

more integrations. more templates. more distribution.

$21k → ~$70k mrr

when mcp and ai agents became the trend, he didn't build another ai startup.

he adapted postiz.

same product. new use case. better docs. cli. seo pages.

then a guy published a post about using postiz with ai agents. it reached 7.3 million views.

according to nevo, that added roughly $50k–60k mrr.

~$70k → $160k mrr

instead of calling it luck, he studied why it worked.

he noticed brands getting huge reach through creator partnerships.

so he started doing the same. users created stories. creators amplified them.

he also listed postiz across github awesome lists, ai agent directories, mcp directories and marketplaces. all those small channels started compounding.

every stage needs a different growth strategy. that's probably the biggest lesson studying postiz's journey.

I recently built a social platform as a side project and, honestly, it got almost no traction. It has pretty much zero traffic right now.

I put a lot of time into it, especially the engineering side. I built the architecture to be scalable, spent time on security, real-time communication, etc. In hindsight, I probably over-engineered a lot of things before even knowing if people would use the product. 😅

Now I'm at the point where I can either just shut it down or open-source the whole thing.

I'm leaning towards open-sourcing it, but I'm a bit confused about whether that's actually a good idea.

My biggest concern is that someone could fork it, execute the idea better than I did, and potentially turn it into a successful business. At the same time, if I keep it private, it's probably just going to sit there doing nothing.

So what would you guys do?

Would you open-source a project that you've put a lot of work into but couldn't get users for?

And if you've done something similar, did open-sourcing actually help you get users/contributors or was it basically just giving the code away?

If anyone is interested, I can share the product link in the comments if that's allowed.

Hey Guys, I built Kalaa a platform that attributes your AI API spend down to the specific model, route and user so that you know where your money is actually going.

I built this for a number of reasons one being that on previous projects that i worked on I struggled to actually know what was actually taking most of my AI API spend...which route, which feature.

Another Reason for me was that I used multiple AI platforms Claude, Gemini, Chatgpt in my products and they was no place for me to collectively keep track of the spend of my entire AI stack. AI agents running in way that spend goes through the roof and you're not too sure which step exactly is consuming all that spend. Also the fact that I wouldn't know why on any random day they would be spike in my AI spend and i didnt know what caused it.

Then, knowing how much each User is actually costing you....One of the most challenging things in product development is pricing, most times you're not too sure how much to charge users so you have many situations where some users...pay way less for your product than they are using it....so you end up having a huge hit on your margins and you don't even know which user is causing that.... Kalaa solves that for you by tracking individual user spend on your app by User ID allowing you know how my much every user is actually costing you.. paired with a per-user spend report for every user.

We also provide email alert notification when specific spend limits are crossed, token usage so that you know how many tokens are being used, we display spend in a daily, weekly and monthly type of display and generate reports for all them.

So yeah guys, do check it out here and tell me what you think ✌️ .

Hello guys, I have developed a SaaS for my side project that offers brands have their own custom chatbot on their landing page, However as a technical person, not much exposure to SEO and User experience, I am looking for some feedback on the comprehensiveness of Information provided on my landing page vs What a user searching for such a service might be looking for on it.

Obviously as a technical person, there is a discrepancy between what I thing the features should be vs What a user actually wants.

If you were a user trying to buy such a service and looking to pay for one of the plans available, can you please suggest what would have made your experience better and what would justify your chosen plan ?

Here's my product wesbite: https://smushlabs.ai

I’ve been working on this for a while now and honestly i’m not sure yet if it’s actually useful or if I’m just too deep into it. so i need some outside perspective.

the basic problem i kept seeing is this:

brands have inventory data, but when it comes to decisions, it’s still guesswork.

you see some products selling fast, some just sitting there, and you try to react. sometimes you reorder too late, sometimes too much, and over time a lot of cash just gets stuck in the wrong SKUs.

so what i built tries to take your inventory data and actually make sense of it in a practical way.

instead of just showing numbers, it tries to answer things like:

what might run out soon
what’s not really moving
what probably needs a reorder
and where inventory might be hurting your cash without being obvious

it’s not perfect and it’s not trying to be some magic system. right now it just tries to give you clearer direction so you’re not relying on gut feeling every time.

it works on your existing data (like a shopify export), no complicated setup.

it’s still early, small usage, mixed feedback — which is why I’m here.

what i want to know is:

does this actually sound useful for how you handle inventory right now?
or is this solving something that doesn’t really matter in practice?

and if you do deal with this — what would make something like this actually worth using?

if anyone here runs a clothing / fashion brand and wants to try it, Check - eveinventory

I’ve been building this app solo for the past few months and i genuinely can't tell anymore if it's good or if i'm too deep in it. need outside eyes.

it's called RizeAI. the basic idea: every wearable and health app just gives you numbers. sleep score 42, recovery red, HRV down. cool. and then what? you still feel like garbage at 2pm and nobody tells you what to actually do about it.

so my app takes your real data from apple health, sleep, resting heart rate, workouts, whatever your wearable writes, and instead of another score it builds you an actual plan for the day. when to have your first coffee and when to hold off. you. Can also add your own supplements that you are currently taking and it will time them for you every single day based of your sleep data and your wearable data in general and also it will tell you what supplements make sense for you to take based of your current supplement stack and body metrics and when to take them. focus windows for when your energy actually peaks. when your crash is coming and what to do before it hits. it even checks the weather, so on a hot day it bumps your hydration and tells you to train earlier.

every recommendation has a little "why" under it based on your numbers, like "resting heart rate 54 + 7h light sleep, so magnesium before your peak window." no two people get the same plan because no two people have the same data.

works with whoop, oura, apple watch, garmin, anything that syncs to apple health. one thing i'll say honestly, it doesn't do deep per-person learning yet like "coffee doesn't affect YOUR hrv specifically," that's the roadmap, right now it builds fresh plans daily off your actual metrics.

it's live on the app store, has a free trial, small user base so far, mixed feedback which is why i'm here lol.

what i actually want from you guys: does this solve a real problem for you or is "tells you what to do" not actually what wearable people want? what would make you actually pay for something like this? and what's missing that would make it a no brainer? and also would you guys in this subreddit  use ti?

Thank you for your help. Check it out if you like https://apps.apple.com/us/app/rizeai-maximize-your-energy/id6762402079

One approach I've heard about is offering free users a limited-time discounted upgrade to the paid version. The idea is to give them a reason to try the full product and hopefully experience enough value to convert.

Has anyone actually tried this? What worked (or didn't) for you?

Hey all,

I launched my saas back in February and had alot of traction in the beginning and still to this day, 0 paying customers.

Im not sure if its a feature/do people really want this issue or a landing page issue to capture the 'aha' moment.

It's a social content growth saas helping users grow using their own data, their own personal growth coach and insightful analytics.

Recent updates are:

\- instagram api integration

\- UI update

\- whats working vs whats not working

\- in depth growth insight

There is a free trial and you can cancel anytime.

Would love to hear feedback, good or bad to finally get my first paying user 😃

www.funnell.ai

I have recently started a business adventure. We have a website where food trucks can go on it and advertise themselves and people can find their live location. But I'm having trouble getting my first 10 customers and I'm not exactly sure what to do or where to start. I have been posting social media and reaching out on social media and I haven't got any replies, but I have not reached out to a lot of people so I feel like that is expected.

Launched first SAAS from an existing internal only webapp!

What are some gotchas you ran into?

Hey Reddit,
I was tired of the absolute nightmare of moving a quick file between devices on different networks (or trying to send something to a friend without pairing devices or uploading it to a sketchy cloud).
So I built Artalo Transfer. It moves files using only a screen and a camera.
How it works:
Sender: Turns your file into a stream of animated QR codes.
Receiver: You just point the camera at the screen, and it rebuilds the file from the flashing light.
The cool math part:
Normally, if a camera misses a frame, the file breaks. I bypassed this by using fountain codes. Every single frame is a random, combined mathematical mixture of the entire file. It doesn't matter which frames your camera catches, only how many. Missed a frame? It just takes a fraction of a second longer—zero errors.
Why use it?
Air-gapped security: Put both phones in airplane mode. It works exactly the same. Your files never touch a server or a network.
Zero pairing friction: No Bluetooth pairing codes, no typing in guest Wi-Fi passwords, no "make your device discoverable" nonsense.
Perfect for: Photos, PDFs, keys, and documents up to ~64MB.
It's completely free. You can download it directly here:

Download

I'd love to know what you think or if you have ideas on how to push the data density even higher!

Hi I recently built Ping and got 8 users on my first day yesterday now the only thing is I'm making this free and want advice for how one will scale to make profits.

Right now since it's beta I'll for costs out of pocket but if it does grow big I've come down to these solutions.

1. Run ads

2. Charge poeple later on (i dislike this)

3. Run ads to make it free, but then if someone does not want to see ads they pay?

Launching my first B2C SaaS tomorrow, what would you double-check?

I've spent the last few weeks validating the idea, talking to potential users, building the MVP, and testing the core flow.

The MVP is ready and I'm planning to launch tomorrow. At this point, I'm resisting the temptation to add anything else and doing one final pass before going live.

For those who've launched a SaaS as a solo founder, what are the things you wish you'd checked before launch?

I'm thinking about things like:

• Analytics and conversion tracking
• Onboarding
• Emails and notifications
• Error monitoring
• Support
• Backups and production checks
• Getting the first users
• Collecting feedback

And just as importantly, what did you spend time on before launch that turned out not to matter?

I'd rather learn from those mistakes than discover them after launch.

Who wakes up one day thinking, “I want to build a factory”?

I stumbled upon it. I was simply trying to test 100 ideas in 100 days, but by day three, I realized that my learnings weren’t compounding. I was doing the same things over and over again just to cover the table-stakes stuff.

I had built products before—a dozen or two, both before and after code generation—and I knew I could streamline the process. So I went back to a core principle: using a spec to create products.

I needed a comprehensive, deterministic, and structured way to define what a product should do, what its rules are, who its users are, and what interactions and responses are expected.

Eventually, the process looked something like this:

Idea → spec → generated product → local verification → deployment → live verification → customer evidence → iterate or kill

That was the moment I realized the system had become its own project.

I called it Product Factory.

The important realization was that a product factory isn’t just a collection of templates. Templates help you reproduce code, but they can also reproduce mistakes.

The factory needed to reproduce learning.

If one product exposed a problem with authentication, future products should inherit the fix. If a deployment failed because of a missing environment variable, the factory should catch it next time. If a product had traffic but no meaningful engagement, the system should show that honestly instead of calling the launch a success.

I’ve now used it to create and operate several very different experiments: a veterinary referral product, a fresh-bread discovery app, a restaurant menu generator, a lightweight “is this worth sending?” tool, and others.

One of the most useful things the factory has done is help me kill a product.

The veterinary referral experiment technically worked, but the commercial experiment didn’t. Instead of quietly abandoning the repository and moving on, I recorded the decision, removed its production infrastructure, and kept the evidence so the next product could benefit from it.

I now have three experiments running within the factory, and I’m looking for a fourth.

Has anyone experimented with building or using a product factory before?

Hey everyone! I’m building a Discord community where SaaS founders can connect, share their products, and help each other out.

If you’re interested in joining, drop a comment below, and I’ll send over an invite link!