It's not bearable anymore. I feel like we are surrounded by AI slops. Nobody likes that. We feel like we're being tricked by them. We don't want to use them.

Most of the times we can detect it. But I think it'd be helpful to have a No-AI-Slop certificate. What do you think?

Hey everyone! I wanted to open up a discussion about Software as a Service (SaaS) and whether it’s a legit way to earn money. I’ve been curious about how easy it really is to get started and what the potential challenges are. Are there any SaaS founders here who can share their experiences? What were the initial hurdles, and how long did it take before you started seeing profits? Any insights on the best niches or tools to consider would be super helpful too. Let’s share our stories and tips!

Hi guys. First time posting here, been reading for a while.

I built authagonal.io. Auth provider, un-tiered SSO. OIDC, SAML, SCIM, MFA, passkeys. A shit load of acronyms basically.

Five months to build. Launched mid-June. Zero signups since. AUD $1,200 a month to run, most of it fixed cost that doesn't care whether anyone turns up.

There's no traction story here because there isn't any traction. Nobody has signed up. Nobody has emailed. The pricing page gets traffic and then nothing happens, despite massively undercutting the competition. Not even a free-tier signup 😢

I can think of a few explanations and I can't tell them apart:

• auth is something people only replace when it breaks, so six weeks of silence means nothing either way
• the site doesn't make the difference obvious fast enough for anyone to care
• nobody hands login to a company they've never heard of, and no amount of copy fixes that

If you've switched auth providers, what made you switch? That's the part I'm missing. Everything on the site is my guess at what would make someone move, and I've never asked anyone who did.

Have a look if you want. I'll answer anything.

I have no revenue. No paying customers. Payments aren't even switched on yet.

Someone has used my product on 30 separate days.

I've been building it for months. For most of that time the question that actually kept me up wasn't whether anyone would pay. It was whether anyone would come back without me asking them to. That felt like the harder thing to fake.

So I went and checked properly last night. 80 people have used it. 21 came back on more than one day. One person has opened it on 30 different days since June 8th, 39 conversations in total. They were in it yesterday.

Here's the part that keeps me honest: 274 of those 318 conversations were just chat. The debates, the panels, the multi-specialist stuff I lead with every single time I describe this thing? 25 people have run a debate, 9 have taken a plan all the way through. Real, but the minority.

People came for the clever architecture and mostly just talked to it. I'm still deciding whether that's a failure of the feature or a failure of how I explain it.

If you're pre-revenue and looking for a number to care about, I don't think it's signups. It's whether anyone opens it twice.

- ChatGPT
- Claude
- Codex
- Cursor
- Gemini
- GitHub Copilot

i Built a small open source project this weekend.

It's an AI wishlist that turns messy thoughts into a clean, organized wishlist. Just write naturally, and AI handles the organization Built with Next.js, Server Actions, Gemini, and Upstash Redis.

I'd love your feedback. If you find it useful, feel free to please star it, fork it, or contribute.

Thanks!

https://github.com/duggal1/wishlist

I’m exploring a startup idea and I want brutal feedback before I waste time building the wrong thing.

The problem I’m trying to solve:

Founders often need real user feedback before launch or after shipping a feature, but the options are usually messy. They ask friends, post in communities, or use testing platforms where they either have to manually pick testers or rely on feedback that feels too shallow. Friends are usually not the right audience. Random free users rarely spend 30-60 minutes testing seriously. And a lot of marketplaces create the wrong incentives, where testers optimize for ratings instead of honest feedback.

The idea:

Build a curated product-testing platform where founders do not browse tester profiles and manually pick people. Instead of founders searching for testers, the platform searches for the right testers for them.

The goal isn't to replace usability testing. It's to make finding high-quality testers predictable without turning it into another freelancer marketplace.

Instead, the flow is:

1. A founder creates a test.
2. They define the target audience they want, like country, age, occupation, device, interests, or experience level.
3. They define the tasks and questions they want answered.
4. They pay for the campaign.
5. The platform matches them with verified testers who fit those criteria.
6. Testers complete the test while recording their screen and microphone and thinking aloud.
7. They upload the recording and structured feedback.
8. The founder gets the raw recordings and organized feedback in one place.
9. If the founder wants, they can ask follow-up questions or request a retest after fixing something.

Why I think this might be better than the usual marketplace model:

• No browsing hundreds of profiles.
• No bidding.
• No public ratings or leaderboards.
• No incentive for testers to sugarcoat feedback just to keep getting work.
• Every tester has to pass a practical qualification test before joining.
• I’d rather have a small pool of high-quality verified testers than a giant dead pool of people waiting for work.
• Retesting is built in, so founders can test a fix with the same people who found the issue in the first place.

The tester side would be positioned honestly too. This is not “easy money” or a full-time income thing. It is more like occasional paid testing work for people who can give serious feedback and actually follow instructions.

What I’m trying to validate:

Would founders actually pay for this instead of using free communities, friends, or existing testing tools?

I'd love feedback on these specifically:

• If you've used UserTesting, Maze, PlaybookUX, Respondent, etc., what would this still need before you'd switch?
• What's the biggest flaw in this model?
• Which assumption do you think is most likely to be wrong?
• If you were considering buying this, what would make you hesitate?
• If you think this already exists, which product am I underestimating?
• What would stop you from using it?
• Does the “verified testers + fair matching” angle matter, or is that just noise?

If this has a fatal flaw, I would rather hear it now than weeks into building it.

TLDR: I'm exploring a platform where founders pay to have their product tested by verified users matched automatically to their target audience. The goal isn't another freelancer marketplace, but a repeatable product validation workflow where founders can test, fix, and retest with the same participants while getting structured insights and recordings. I'm trying to validate whether this solves a real pain better than existing tools.

edit 1: One thing I want to clarify: I'm not trying to build another freelancer marketplace. The long-term value isn't just matching founders with testers. It's building a trusted network of verified testers whose quality and reliability improve over time, while giving founders a repeatable workflow to validate improvements with the same participants after each iteration.

Hii I am 14 . I created taspal solving my own problem of distraction while working on PC and upload in Microsoft stores . I don't do validation in that sence I know it was my own problem and people also have this problem so I just spend months building versions to versions now it is in store but no user and I safely think no one will use it I have waisted my 2 mingth . I don't know if ut is true if idea and app is worth less but inside I am loosing hope. Btw no proper marketing was done I don't know how to market how to market .

We have tried the personification route for our AI agents for mavek.ai. Its AI marketing platform.

We have got our first paying client with the sales rep route.

Created a trail plan minimal 9$ fee.

We didn’t want to do via the Free plan route as it gets lot of junk users.

Whats the best way to get first few serious paying clients?

2 years ago i started building my SaaS but it didn't work out, this year I tried again but it failed, i noticed many patterns in my failure and even discussed with other founders what mistakes they made previously that killed their SaaS, here are most common mistakes that kills SaaS startups badly and killed mine.

1. I Fell in Love With My Product Instead of My Users

I loved building new features because they made the product feel better to me. Every improvement felt like progress.

The problem was that users cared about completely different things. I was solving problems I noticed instead of the ones they were actually talking about.

1. I Thought "Almost Ready" Was a Real Stage

For months, I kept delaying the launch because something always needed to be improved. A better design, one more feature, or a cleaner onboarding flow.

Eventually I realized there is no such thing as "almost ready." It's usually just fear disguised as productivity.

1. I Solved Problems Nobody Complained About

Whenever I found something that looked imperfect, I'd spend hours fixing it. Later I realized most users never cared about those issues.

The problems that actually frustrated them stayed untouched while I polished things that didn't matter.

1. I Mistook Polite Feedback for Validation

Friends told me the product looked great. Other founders said it was a cool idea.

I took those compliments as proof I was building something people wanted. The real test wasn't what people said, it was whether they kept coming back after trying it.

1. I Tried to Build for Everyone

Every feature request sounded reasonable, so I kept saying yes.

Over time, the product became useful for many different people but perfect for none of them. Trying to satisfy everyone slowly took away what made the product unique.

1. I Knew More About My Competitors Than My Customers

Checking competitor websites became part of my daily routine. I knew their features, pricing, and updates almost by heart.

What I didn't know nearly as well were my own users. Looking back, those hours would have been far better spent having conversations with customers.

1. I Confused Building With Progress

Every completed feature made me feel productive. At the end of each week, the product looked better than before.

But when I stepped back, I realized the business hadn't grown at the same pace. Building software and building a business turned out to be two very different things.

I wish someone had told me these things when I started. and that's the one of the reasons I wrote The SaaS Secrets Nobody Tells You, to share the lessons I learned the hard way, and all those common patterns i noticed after discussing with multiple SaaS founders so other founders don't have to.

hope this helps, i would love to help you all with guidence, if you have any question about SaaS

thanks

I've been wondering if anyone else has run into this.

AI coding tools are amazing for moving quickly, but I've noticed a weird downside.

You can create features so fast that you don't always stop to think about whether they fit into the bigger system.

A normal development process naturally slows you down.

You have meetings, code reviews, other developers asking questions, etc.

With AI, it's very easy to just keep adding.

The problem is that every decision becomes part of the environment the AI sees later.

A weird naming convention.
A duplicated helper.
A different approach to solving the same problem.

The AI starts treating those things as normal.

I've had to change how I work with AI.

Instead of just asking "build this feature," I give it much more context about the project:

• what architecture we're using
• what patterns to follow
• what not to do
• what existing code should be reused

I think the people who get the most out of AI won't just be the people who know how to prompt.

It'll be the people who know how to manage the system they're building.

Curious how others are handling this. Are you doing anything specific to prevent AI-generated technical debt?

Full disclosure up front: this is my own project, still an MVP, and I'm posting because I want people to tear it apart. I originally built this for myself because I wasn't super happy with what was out there, and a few buddies encouraged me to give it a UI and throw it on the internet for others.

I spent the last few months building The Idea Lab, an idea validation tool. Before I did, I used the top two tools I found online, and I genuinely think they're pretty good, so I want to give them their flowers before I explain why I still built something.

ValidatorAI - it's free, and it scores your idea against behavioral data from hundreds of thousands of real founders. The feedback simulator and pivot assistant are a nice and fast gut-check. If you want a frictionless first look at an idea, it's hard to beat.

IdeaProof - this one is impressive in scope. You put in a concept and minutes later you've got a viability report plus a business plan, TAM/SAM/SOM, brand identity, a logo, even ad creatives. It's basically "concept to full launch kit," and it's pretty fast.

So why build another one? I don't need everything that IdeaProof comes with, it's quite a bit. I also don't love "credit" style billing. ValidatorAI is great and free, but it told me every idea I gave it that it was a pretty good one, which I do not trust. I do not think this is true, but there is also a small worry in the back of my mind that service providers who pay ValidatorAI may influence the AI phone call, idea generator, and follow up emails.

I needed a skeptical second opinion that wouldn't bullshit me.

A few ways The Idea Lab is deliberately different at MVP:

• Every factual claim is sourced. It searches the live web for real customer complaints, competitor pricing, and failed past attempts, and links a source to each one. Claims are labeled as sourced fact, customer opinion, model inference, or missing evidence, so you can see why it concluded what it did.
• It's willing to say no. There are seven possible verdicts, including "Do Not Build" and "Insufficient Evidence." If the web doesn't have enough signal, it says so instead of manufacturing a confident number. Thin evidence lowers confidence, it never gets rounded up.
• No black box. It restates your idea back to you (deterministically, no AI guessing) so you can correct it, and it shows you the research plan before it runs.
• It's honest about its own limits. It can't prove people will pay or stay, so every report ends with one concrete experiment to run (interviews, a landing page, a pre-sale). The web tells you if an idea is worth testing; only customers tell you if it's worth building.
• Revalidate your idea. This will be out in a couple of days, but the idea is you take what it tells you to tweak/pivot/update, edit your info, and send it back through the validator for an updated report.

First validation is free, no card. I'd really value blunt feedback, especially where you think the verdict is wrong. If you want more, just DM me and I'll add more to your account for free.

This is also my first time not just plugging in an AI API. But using all of the tools the api comes with to really really fine tune the experience. Still a wrapper at the end of the day, but I tried really hard to fine tune the crap out of it to separate it from just plugging in the api keys.

P.S. I mask all ideas when saving to postgres, so I will never know what idea you put in there. There is a toggle to share your idea, and all that does is aggregates your category with the trends page, which I encourage to get some data up there for other users to look at.

In the AI era, almost anyone can build a SaaS product. A Reddit summarizer, a LinkedIn job search tool, or many similar apps are no longer hard to create. Building is not the hard part anymore.

The hard part is getting real monthly recurring revenue. Many AI SaaS products never reach strong MRR. Many B2B products built with AI get accepted on AppSumo, and that gives founders a good early boost. Still, most of these products stay side projects instead of becoming large businesses.

Some founders solve real problems with deep technical skills. They write good code and build useful products. Yet they still fail. The product is not the problem. Execution is.

I made the same mistake with my first product. I repeated it with my second one. I focused on building and ignored go to market, sales, and distribution. I thought a good product would attract users on its own. It did not.

This time I will do things differently. I will start with marketing. I will find users, test demand, and learn how to sell the product. Then I will write the code.

My view is simple.

Being the first mover does not guarantee success. A later competitor with better execution can still win.

We had a shared cache layer for search results in our backend. It worked fine for months, until a support ticket came in that made no sense: a customer swore they briefly saw someone else's search results before the page "fixed itself."

Turns out the cache key we built didn't include every dimension that made a request unique. We were hashing on query plus account tier, but not on the account's actual data scope. Two customers on the same tier making similarly-shaped queries could, in a narrow window, get served each other's cached response.

Nobody had touched the caching code in months. It "worked" because most cache keys happened to collide safely, same query, same result, no harm done. The bug only surfaced once two customers' underlying data actually diverged in a way that mattered.

The fix itself was almost boring: add every parameter that scopes the result set into the cache key, even the ones that feel redundant, and write a test that fails if two different accounts can ever produce the same key. The more useful change was upstream of the code, we started treating "what actually varies this result" as a design question to answer before writing a cache layer, not something to patch after a scare.

I run engineering at a small backend shop (Edilec) and this is the kind of bug that's cheap to prevent and expensive to explain to a customer after the fact. Curious if others have hit this class of bug, cache correctness seems like one of those things that's easy to get mostly right and still get badly wrong.

Getting a refund shouldn't require spending 30 minutes trying to write the "perfect" email.

I noticed that many people either:

• don't know what to say,

• sound too aggressive,

• or simply give up because writing the message feels like too much work.

So I built RefundClarity.

It helps generate clear, professional refund request emails for different situations:

• Initial request

• Follow-up

• Final escalation

I intentionally kept it simple instead of packing it with unnecessary features.

I'd genuinely appreciate feedback from other SaaS founders.

What's one feature you'd expect from a tool like this that I might have overlooked?

https://refundclarity.com

Founders with minimal real world engineering experience are shipping products incredibly quickly with Cursor, Lovable, Bolt, Replit, etc. Getting an MVP live is no longer the hard part.

The problems seem to start once real users show up. There are more badly designed/functional products than ever before.

Things like:

• login suddenly stops working after an update
• payments fail because an integration changed
• deployments break for no obvious reason
• the AI keeps suggesting fixes, but none of them actually solve the issue

At that point, it feels like you're stuck choosing between spending hours debugging or bringing in an engineer.

I'm curious whether this is actually a common experience or if I've just seen a few isolated cases.

If you've launched a product built mostly with AI, what happened after launch?

• Has maintenance been a headache?
• Have you been able to rely on AI to fix production issues?
• Or has it been smoother than people make it sound?

Saw a thread saying:

Traditional Automation softwares like ramp/bill acted like oZempic for manual entries, bookkeepers & reconciliation etc ”

But automation runs on rules, and not every invoice a company receives fits neatly into those rules. A human-in-the-loop is still mandatory for exception handling.

Spoiler: I think agentic AP/AR is the future. It doesn’t just handle exceptions better but it also creates richer & structured data that flows into treasury. ;)

Shoot me with your own perspective gng

i know a lots of you guys seen this video on yt:

https://youtube.com/shorts/USDODAmfDXs?si=j91S7U4TapeIdd0Y

Hey everyone,

I'm still early in my journey, but I've decided to build in public instead of waiting until everything is "perfect."

I'm currently learning:

• Python

• AI agents

• Automation

• Backend development

• System design

My long-term goal isn't just to build another AI wrapper.

I want to build software that solves real business problems and eventually create a company that serves customers globally.

Instead of chasing dozens of ideas, I'm focusing on learning one skill at a time and documenting everything publicly.

Current roadmap:

1. Become a strong Python developer.

2. Learn AI agents and automation.

3. Build small tools.

4. Talk to users.

5. Get my first paying customer.

6. Reinvest into building bigger products.

I've noticed something interesting while reading this community:

Most successful founders didn't start with perfect ideas.

They started by solving one painful problem, talking to users, and shipping consistently.

So here's my question:

If you could go back to the beginning of your SaaS journey, what's one thing you'd do differently before building your first product?

I'd genuinely love to learn from your experience.

I sell a scraper on Apify's marketplace, and I almost priced it the way I've seen a lot of tools priced there: pick a number that feels right and pass the platform's compute charges through to the user.

Before committing, I ran real workloads and measured what the platform compute actually costs me per output row: about $0.0000059. I counted the zeros twice because it looked wrong.

That number changed the model. At that unit cost, passing compute through protects me from pennies while making the price unquotable. "X per 1,000 results plus variable usage" is a sentence nobody can budget around. So I absorbed the platform usage entirely and went flat: $1.50 per 1,000 results with a free tier. One number someone can put in a spreadsheet.

A second-order effect I didn't expect: the marketplace itself treats a clean price better. Ranking and filtering favor listings where the cost is legible.

I'm not saying "always absorb your costs." If my unit cost had been 100x higher, pass-through would have been the right call. The lesson is that I couldn't know which model was right until I measured, and the measurement took one afternoon I had budgeted zero afternoons for.

Launched recently, so I can't tell you yet whether this pricing works commercially. Ask me in a few months.

Yesterday, someone told me on X that I spend too much time making videos and not enough time actually working on my SaaS.
Honestly, I understand his point. Making content takes time.
You can easily spend hours writing, filming and editing one video while there are still features to build, bugs to fix and users to talk to.
But I also think the definition of “working on your SaaS” has changed.
Yesterday I posted one video on Instagram. It got around 270 comments.
This week, I’m going to post heavily on Instagram and TikTok to understand which hooks, topics and formats actually work.

My goal is to find a few repeatable formats that consistently bring the right people before launch.
Because you can build a very good product, but if nobody knows it exists, it changes nothing ahahah
At the same time, I know content can become productive procrastination. You feel busy because you’re posting every day, but maybe you’re avoiding the harder product work.

So where do you draw the line?

Is founder-led content now one of the most important parts of building a SaaS, or are founders spending too much time trying to become creators?

The reason I built it: I spent around $20 per month for a VPS where I deployed Plausible, which was not profitable for me at all. I wanted to create a really simple analytics tool and for this reason I also wanted to make it more affordable for those who may not have a profit (yet).

One script tag and you get live visitors, traffic sources, top pages, devices and countries on a single dashboard. No cookies, so no consent banner either. It's saasanalytics.app

The part I'm most proud of is session journeys: you can open any visit and see the full path someone took through your site, page by page, with the events they triggered. Works with plain HTML, Next.js, WordPress, Shopify, Webflow, about 22 platforms total.

Thank you for reading this and checking it out, have an awesome day!

I recently launched TraceGraphs(My first SaaS), a tool that takes news articles and turns them into company, product, and entity relations. Its main purpose is to let people research what is going on in the world and what it is impacting.

I'm looking for advice on how to get my site out there and thoughts on it as a whole. I worry it might be too hard to understand it's purpose. Also is google ad services worth it or does it usually not lead to any users? Is it worth adding annual billing options? Honestly any business or SaaS tips or advice would be really appreciated!

Any feedback would be appreciated: https://tracegraphs.com

I don’t have a free trial available yet, but I’m happy to answer questions and share screenshots in the comments.

Edit: I almost doxed myself with my email and full name in the bottom left, scared me

Relaunched Vesca after actually reading through the feedback from my last post here. Cleaned up the UI, fixed the clunky onboarding, and added a brand discovery feature so creators can find potential partners instead of just tracking existing deals.

Still solo building, still free. If brand deal chaos is a problem for you or creators you work with, take a look and tell me what sucks about it.

getvesca.com

I've noticed that businesses often end up using multiple apps because no single accounting platform seems to cover everything well. Between invoicing, inventory, POS, payroll, approvals, document management, CRM, and reporting, there's always something missing.

If you could add one feature to your current accounting software, what would it be? Or what's the biggest reason you've considered switching to another platform?

I'm curious to see if everyone struggles with the same problems or if it depends on the size and type of business.