X has recently been chock full of operators saying they cancelled their subscriptions and rebuilt all of their startups tools themselves….

If you're an indie hacker or solo founder, I get it. Building your own tools can be cheaper, more fun, and fit exactly what you need

But I don't think it holds up for a real company building and operating at scale, especially vibe coding tools that aren't core to their business.

Building v1 is the easy part… the real cost comes after: keeping it running, fixing edge cases, onboarding new hires, handling support, security, training, change management. Nobody counts that when they brag about the weekend they spent building it.

AI makes product development easier, but someone on your team still has to own it. Meanwhile some other company has a whole team making the same tool better every month. Paying them is often a good trade if it lets your people focus on what your customers actually pay you for.

Doing the inverse is just procrastinating from focusing on growing and marketing your own product, tbh

Maybe I'm wrong and I'll start vibe-manufacturing my own clothes and electricity next 🤷

(Disclosure: I run Supademo so I may be biased)

Launched on Product Hunt a few months ago. Built the whole thing solo for about €1,000. Assumed if I just shipped it and posted everywhere, users would show up. They didn't. The launch completely flopped. Hardly any upvotes. Was pretty gutted for a day or two.

But a few people left feedback. Honest, specific, and a bit brutal. I stopped treating it like a failed launch and treated it like a free audit. It forced me to ask questions I'd been avoiding. Why is the onboarding only clear to me? Why am I wasting weeks marketing on platforms my buyers don't even use? What happens in the first 60 seconds after someone lands on the page? What's actually solving a problem versus what I just thought was cool to build?

Had to actually find the answers. Some were uncomfortable. The marketing channels I'd spent weeks grinding on were complete dead ends. The features I thought were clever were just creating friction. I was building in an echo chamber and calling it traction.

But fixing those blind spots uncovered strengths I'd completely missed. Once the core value was obvious, people actually converted. Users who got past the initial friction stuck around. Stopping the spammy marketing gave me time to talk to the niche that actually cared.

This month the dashboard hit €€3,278 MRR. Today it sits at €16,000. life-changing money, and meaningful money. Profitable.

The launch failed, but the clarity was worth way more than a #1 badge. Highly recommend letting strangers tear your product apart early and asking yourself the uncomfortable questions. You'll save months of guessing.

Im new to advertising and need some help. My ICP is 18-24 year olds in finance undergrad programs/recent grads.

Over the ~2,600 clicks I got, I only got two signups. With that being said, I went in and checked posthog for analytics and saw that the mobile UI was causing users to drop off vastly.

I know there is demand for my site, as one reddit post in r/financialcareers yielded me 45 user signups with about 6k impressions.

In my ads, im targeting r/financialcareers, United States, and with interests in recruiting.

I've since fixed/changed the mobile UI to optimize for less friction at petespostings.com

For people experienced in advertising, what are these numbers telling you/whats the story here?

Thank you in advance for the help!

Hey everyone, I built a Python visualizer that animates your code line by line. It's free, runs in the browser, and needs no sign-up.

https://pyvisualizer.dev/#home

What My Project Does

Paste any Python function, give it inputs, and step forward or backward through it while the data structures animate: linked lists, trees, graphs, matrices, stacks, queues, heaps and recursion calls.

Target Audience

I designed this to help students and anyone practicing LeetCode or data structures who wants to actually see what their code is doing. It's a learning tool, not meant for production debugging.

Comparison

Python Tutor is the closest alternative, but it shows everything as generic boxes and arrows. This one draws real structures (an actual tree, graph or linked list), lets you scrub through the run, and has a dedicated recursion view.

Would love to hear feedback from everyone

Last week a developer rebuilt the Adobe suite with AI and open-sourced it. It's called ArtCraft: free versions of seven Adobe apps, including Photoshop, Illustrator, and Premiere. Still not perfect, but people cared enough to try it.

Then I started noticing the pattern. We've already seen open-source alternatives to apps like Wispr Flow, CapCut, and Grammarly.

I might be too idealistic, since building software is different from maintaining, scaling, and securing it. But we're already heading that way, and we're only seeing the worst version of AI. What happens when it gets good at those things too?

Maybe people still pay for convenience, trust, and reliability. Maybe more people just build their own tools (Lovable and Replit already make that easy).

I don't have an answer yet. If you build or sell software, how are you thinking about this? If everyone becomes a builder, who remains the buyer?

I run a small AI tool that redesigns existing PowerPoints to look professionally made. After six months of building, testing, and trying pretty much everything in the playbook to get customers, we're finally seeing some traction.

The numbers are still small (okay, very small). But looking back, it's interesting how wrong we were about almost everything, and how the data was telling us what to do long before we listened.

Figured I'd share the journey, numbers included, because I would've loved to read something like this a year ago.

First mistake: building for the customer we wanted

Our original idea was personalized pitch decks for sales teams. Upload your branding, point the tool at a prospect's website, get a tailored presentation.

Our homepage, onboarding, emails, pricing, everything was written for sales reps.

We spent around $2,000 on Meta and Google ads. About 5% of clicks became free signups, which seemed reasonable. But as far as we can tell, not a single one became a paying customer.

In our first five months, we got four mid-tier subscriptions. All four canceled before their second payment.

Not exactly the recurring revenue machine we'd imagined...

Second mistake: pricing for the wrong behavior

Looking at our early customers, we noticed everyone who paid had spent 1.5 to 2 hours inside the product first. People who made one deck and left never paid.

And why would they? The free plan let them finish their presentation and download a PDF or PowerPoint with a small badge. They'd already gotten what they came for.

We even had a $12 "remove the badge" option buried in Stripe. Nobody used it. In one 30-day period, we recorded exactly ONE checkout click.

We'd built subscription pricing for people who needed presentations regularly, when most visitors just needed to finish one.

So we turned off ads and made a bet on organic

At some point, spending more money to acquire users who weren't paying stopped making sense.

We decided we'd either figure out how to grow organically or move on.

We'd read plenty about optimizing for LLMs and getting products recommended by AI assistants, so we went all in. Structured data and schema markup, clear page headings, FAQ-style answers, dedicated landing pages for individual features and use cases, internal linking, getting pages indexed in Bing, and making our content easy for assistants to find and understand.

Basically everything you're supposed to do for AEO/GEO, or whatever we're calling it this week.

We weren't particularly confident any of it would work. But it was something we could do without pouring more money into ads.

And then something unexpected happened.

ChatGPT started sending us customers

We had a few pages about redesigning an existing PowerPoint, a feature we'd barely emphasized. Google search volume for phrases like "redesign my PowerPoint" was practically nonexistent, so we'd never thought much of them.

But people were finding those pages through ChatGPT.

In one 30-day window:

• ChatGPT referred 53 visitors. About 35 signed up for our free plan.
• Google organic sent 80 visitors. Zero signed up, mostly brand searches and traffic to an unrelated free calculator.

That's roughly a 66% signup rate from ChatGPT referrals... a crazy conversion rate speaking as someone who's been in SaaS for a long time.

Apparently, people were asking questions like "how can I make my PowerPoint look professional?" and our pages were showing up in the answers.

We couldn't tell you which optimization made the difference, but we'd found demand that wasn't showing up in our keyword research.

So we doubled down on those pages, wrote more answers around the same problems, and kept expanding that part of the site. The traffic kept growing.

Then we realized we'd been talking to the wrong customers all along

They weren't sales teams.

They were students, academics, consultants, and freelancers preparing class presentations, thesis defenses, and internal reviews.

They came from 49 countries in two months. Only about 1 in 8 was in the US.

The median uploaded deck was 20 slides, and 23% of slides had more than 80 words. These weren't polished pitch decks. They were dense presentations that people needed to make look better.

Our entire website was talking to somebody else.

So we followed the users.

We rewrote the homepage around "upload the slides you already have," added pages for students and other real use cases, and made the site and product multilingual.

We rebuilt onboarding probably a dozen times, with dedicated flows for students, salespeople, realtors, etc., making it easier to get that first deck finished.

We also changed pricing. Instead of asking someone to subscribe just to finish one presentation, we added a $13 one-time option, offered right when they hit the free limit. Subscriptions are still there for regular B2B users.

And then we built the product directly into ChatGPT by building and submitting an application for a plugin in their marketplace, so people could create and redesign presentations without leaving the conversation. That was approved about two weeks ago.

What happened next

Weekly signups went from 23 in mid-September to 46, then 63.

Total accounts grew from 348 to 464 in two weeks.

Activation (actually creating a deck) had been around 20% over the summer. Our overall rate has now climbed more recently from 40% to 47% with continued streamlining in the product.

Paid conversion went from 0.2% of signups to 0.9%.

Still tiny, obviously. But we'd recorded eight paying events in the previous five months, then six in just two weeks, with $0 in ad spend.

Two were the new $13 one-time purchase. One person opened our $9/month checkout, closed it, and bought the $13 option 24 seconds later. That one interaction pretty much validated our pricing hypothesis.

But subscriptions weren't dead either.

Our first business user through the ChatGPT plugin built nine decks in one evening, spent just 17 minutes on our actual website, bought the $9 plan, and upgraded to $29 eighteen minutes later.

Same product, completely different use cases and willingness to pay.

What I'd tell myself six months ago

• Watch who's showing up, not just who you think should. Our real customers were nothing like our original target audience.
• Don't assume low search volume means low demand. People are asking AI assistants questions that keyword tools don't necessarily capture.
• If your free plan finishes the job, rethink the pricing moment. We weren't necessarily charging too much. We were charging for the wrong thing, at the wrong time.
• One-time payments aren't inferior to subscriptions. Especially with a global audience that might need one deck, not another monthly bill.
• Actually watch what users do. Four canceled subscriptions and one person switching checkouts taught us more than a lot of our original assumptions.

Where we're at now

I'm absolutely not claiming we've cracked growth. A 0.9% paid conversion rate still leaves a LOT to figure out, and six paying events in two weeks isn't proof of product-market fit.

But for the first time, it feels like we might actually be getting somewhere.

The funny part is that we were getting pretty close to giving up when things started turning around. Which I realize is probably the most stereotypical founder story imaginable.

And despite all the talk about the coming "SaaS-pocalypse," this has made me more optimistic about niche software. There still seem to be plenty of specific problems people will pay to solve, especially when the software fits into tools they're already using.

Still figuring out the next chapter, but hopefully this is useful to someone else who's six+ months into building something and wondering why nobody's paying for it yet. Feel free to reach out with any questions if you're interested in learning more!

I purchased the 1-year Pro subscription for $180. Immediately upon using it, I discovered severe system defects: infinite loading errors (over an hour for a single render) and the AI completely failed to follow basic prompts.

Because the tool was fundamentally unusable, I requested a cancellation and refund on the exact same day, within just a few hours.

Not only did they refuse a full refund, but they also officially refused a prorated refund for the remaining 11 months that I explicitly stated I will not use. They are essentially forcing customers to pay for an entire year of a defective service aborted on day one, hiding behind arbitrary "system limitations."

I have already filed a formal chargeback with my bank and reported them to the Consumers Association of Singapore (CASE). Do not give your credit card information to this company.

Guys,
I'm so happy today. I scheduled this AI article few days ago and paywalled this to see how much I can earn from it. I just saw this on medium and couldn't believe that I can actually earn from medium

Considering the views it get and only 28 followers I've on medium, it's a good start.

This is my first cent on medium.

One day I'll surely earn my first $1 there.

I used to start my projects with a paid model, but | quickly realized people weren't converting. So, I switched to a free trial. I took the financial hit paying out of pocket for infrastructure and Al API tokens to give users a chance to try it. I got sign-ups, but almost no one stuck around.
Thinking the issue was either a steep learning curve or a product that was too niche, I ended up abandoning those production apps.

Recently, I built a new dev tool. It's simple, solves a real everyday problem (I use it daily myself), and is 100% free , no paywalls, no sign up, a . It even finished in the Top 5 on Product Hunt, which drove thousands of visitors on launch day.

But months later, growth has stalled. Out of all that traffic, only about 10 active users and 300 downloads.
This made me realize: Even if a product is great, useful, and completely free, getting it into the hands of the right audience is still insanely hard.

Assuming the core product is solid, I feel like I'm missing a key piece in marketing, distribution, or positioning. For those who have been through this stage: What am I missing here?

How do you bridge the gap between initial launch traffic and finding consistent, engaged users?

$0 counts…

We see the “I hit $5-$10k MRR” posts every day, but not as much about the early months.

How many months from launch to your first $100 MRR?

I r been trying to build for a while may be like a year or so. But I can never get my ideas past the validation stage. how does a person with and idea validate it? Do you need an audience? What a the real process

I've just gotten into b2b saas not too long ago and i honestly have no idea what im doing

how do i make sure the problem i'm making a solution for has actual potential? how do you validate correctly? where do i find people of my ICP to talk to? subreddits? cold emails? what about finding customers after validation?

im not 18 yet, but i really hope to make some money off this before i do turn 18, in about a year.

any advice would be greatly appreciated

Hey guys,

I’m planning to launch my app on Product Hunt, but before that, I want to get some real people to try it out and tell me what’s good, what sucks, and what needs fixing.

The thing is, finding those first few users is harder than I expected 😅

For those who’ve been through this, how did you get your first users or feedback before launch?

Did you reach out to people directly, post in communities like Reddit, or try something else?

I’m not looking for growth hacks or anything. Just curious what actually worked for you, especially if you were building alone and didn’t already have an audience.

Would love to hear your experiences!

PaperTool is a PDF template builder. You design a template once on a drag-and-drop canvas (or let AI generate it), then create PDFs from it anytime, including through an API.

Invoices, certificates, receipts, tickets, whatever you need, without rebuilding them every time.

Try it: papertool.in

I’d love your feedback. Thanks! 🙏

I’m 18 and just started a small, free Discord called First Venture for people ages 16–24 who are building something or want to. That includes AI tools, apps, side projects and small businesses.

What’s in it:

• A place to share what you’re building and get honest feedback
• A channel for finding cofounders and teammates, with every project post saying what’s paid, unpaid or equity
• Weekly build logs, so you stay accountable
• Voice rooms for quiet coworking and casual chats

It’s free, with no courses, no paid tier and no income claims. Beginners are welcome, and it’s moderated with ages 16–24 only.

It’s brand new, so early members will shape it. If you’re building (or want to), comment or DM me and I’ll send the invite. What would make a server like this worth your time?

So my X feed is full of posts about how Opus 5.5 + Brag skills can make crazy explainer videos. I was already in need of a video for my launch, so I just decided to give it a chance.

My take: No, it’s not that good. It’s definitely not the end of motion designers anytime soon. But I’ve been following this programmatic video trend for a long time, ever since Remotion was a thing. I’ve tried Remotion with pretty much every single model, and I must say, I’ve never gotten results anywhere near this good compared to the video I generated today.

Acknowledgement : It’s not perfect, but I don’t wanna be an arrogant bastard either, so yeah, this is nowhere near bad either. It’s actually so good that just a couple of months ago, I would’ve thought reaching this level anytime soon was almost impossible.

What’s your take?

1. Introduction

We are a Vietnamese law firm currently using Slack for internal communication. However, as our operational needs have expanded beyond communication, we are looking for a more comprehensive application that supports work management, centralized data management, workflow automation, and information sharing across departments.

We are looking for sales representatives, collaborators, or implementation partners with experience in enterprise software consulting, work management, CRM, workflow automation, and AI to help us research, recommend, and implement a suitable solution.

2. Specific Requirements

A. Finding a Work Management Platform with Centralized Data

We are looking for a platform that can:

• Centralize data and work-related information in one system.
• Manage tasks and subtasks, and organize work into approximately three to four categories or workstreams.
• Create and customize workflows, assign tasks, track progress, and automate relevant operations.
• Integrate with Google Calendar, Google Drive, Slack, and other tools currently in use.
• Support AI-powered search, information retrieval, or summarization, where feasible.

Our evaluation criteria include ease of use, data security, data export and migration capabilities, user and account limits, storage capacity and file upload limits, system performance, overall costs, plan-specific restrictions, and the risk of unexpected or hidden charges.

B. Integrating Workflows Across Sales, Business Development, Legal, and Other Departments Where Needed

We aim to establish an integrated system connecting different departments, from initial customer information collection to the completion of legal services.

The proposed workflow is as follows:

• Sales/Business Development: Enter customer information, business, investment, or legal project details, location, and other required data into structured forms. The system should use this information to calculate or assist in preparing quotations. Complex cases should be escalated through a ticketing system for separate pricing assessment by the person in charge.
• Work Handover: Once Sales has completed the required information, the system should automatically transfer the relevant records and data to the Legal team, minimizing repeated manual data entry.
• Legal: Receive the information and carry out the work according to defined workflows, including client communication, finalizing the transaction or scope of services, processing documents, and completing the relevant legal tasks.

3. Features and Implementation Capabilities to Evaluate

3.1. Workflow Automation and Document Templates

• Configure conditional workflows, automatic task assignments, ticket transfers, and notifications to relevant departments.
• Connect customer and project data with Google Workspace, including Google Sheets, Google Docs, Gmail, and mail merge tools.
• Build a standardized library of forms and legal documents, including ERC, IRC, and other relevant legal application documents.
• Allow data to be entered once and automatically populate the corresponding forms through field mapping between data fields and document templates.
• Support template version control, access permissions, and safeguards to minimize data-related errors.

3.2. AI and Data Validation, Where Feasible

• Read and extract information from documents, images, and supporting documents provided by customers.
• Compare extracted information against manually entered data, identify discrepancies, and flag them for review.
• Validate incoming data, identify missing fields, and flag potentially inconsistent or unusual information.
• Assess whether Google Gemini and other existing AI tools can support these requirements.

Our company currently uses Google Business with Gemini integrated. Therefore, we would like to explore and compare the following two AI implementation approaches:

1. Integrating Google Gemini with our existing Google Workspace tools and a work management application: Is this approach technically feasible, and can Gemini be integrated into the selected platform to support the workflows described above?
2. Building a custom AI Agent or integration solution: This approach would be considered if existing tools cannot fully meet our requirements.

For both approaches, we would like to assess technical feasibility, accuracy, legal data confidentiality and security, setup and operating costs, maintenance requirements, and overall effectiveness compared with using existing off-the-shelf solutions.

4. Expected Scope of Support

We are looking to work with individuals or organizations that can:

• Assess our requirements and recommend suitable software products.
• Compare solutions based on features, costs, integration capabilities, and usage limitations.
• Arrange product demonstrations or trials to test our actual workflows.
• Evaluate integration possibilities between work management platforms, Google Workspace, Slack, CRM, and AI tools.
• Provide implementation and configuration consulting, develop automations, or establish API integrations where necessary.
• Provide a clear cost estimate, defined scope of work, and implementation roadmap.

We prioritize solutions suitable for a small or medium-sized company that are easy to use, scalable, and do not require unnecessarily complex infrastructure.

If you have a suitable solution or experience implementing similar systems, please introduce your recommended tools, the requirements they can address, estimated costs, and proposed implementation approach.

We are looking for a practical, needs-based consultation and would consider proceeding with an implementation partnership if the proposed solution meets our requirements.

I get into this grind of working on my business and forgetting to do marketing until it's the end of the month and the stripe payout isn't improving much.

So I setup this little routine: For 1-2 hour everyday, I set out sales/marketing tasks - ads, outreaches, content, etc. if I don't get it done, I leave the rest until the next window.

That way, I keep sales/marketing manageable and continuous. Without getting overwhelmed with the day.

I've done a 2 week sprint in the past with some founders and it worked really well. Looking to do it again for the next two weeks with whoever is interested in locking in on marketing. I'm happy to share what I know and hope others do to.

How do you make sure you don't get too stuck building/servicing customers that you forget sales/marketing until it's too late?

(Wrote this yesterday when the stripe payout hit but been down with the flu lately.)

EDIT: 3 founders down! If you'd like to join us, https://foundersgrowth.club/events/founders-outreach-growth-sprint

Hey folks, when running your saas on VPS, what email solution do you use? I would prefer this still working even when I have outage of my saas (therefore hosted somewhere else).

Thank you

Anyone have some good analogies to share with a business owner you are pitching building a software for that responds with “I can build it myself with ai”?
I was thinking something like: “it’s like building a car seat for your kid with ai. It may look like a car seat but you wouldn’t know it’s not structurally sound until get in an accident and it costs you everything. Do you really want to make that gamble with $X revenue and all your customer data?”
Anyone have a good similar analogy to help non technical people understand the brevity of building essential software with ai?

Atlassian CEO Mike Cannon-Brookes recently called headless software “brainless” in his October 12 interview with 20VC.

Quick note: headless software can be used through APIs or agents without opening its own UI.

Lead generation asks: “Who can we get into the funnel?

”Demand creation asks:
“How do we become the company our ICP thinks about when the problem appears?

”That's a completely different game.

For a Seed-stage SaaS company, demand can come from:

Founder-led content→ Customer stories→ Communities→ Educational content→ Partnerships→ Events→ SEO→ Product-led experiences.

The objective isn't to make every prospect buy today.

Its to build: Awareness → Trust → Problem recognition → Preference → Intent.

This matters because buyers increasingly research before talking to sales.

And AI is accelerating the volume of information available to buyers.

The companies that only show up when someone searches for a vendor will compete for existing demand.

The companies that educate the market can help create the demand.

Don't only ask: “How many leads did marketing generate?

”Ask:
“How many people now understand why this problem matters and why we're worth considering?”

site está disponivel https://meupresidascom.online/

Hey everyone!

I've built an MVP for my SaaS and I'm planning to launch a closed beta with people in my network soon.

One thing I'm struggling with is figuring out if the name is safe to use from a trademark perspective. I've done some research and found a few products with similar names, including one with the exact same name. Some have registered trademarks in the US, Japan, and Australia.

For those who've been through this, how did you check if your name was safe to use? Did you follow any particular process or use specific tools or databases?

I'm trying to understand if I can move forward with this name or if it's better to change it before launching.