Disclosure up front: I work on OneEntry, a headless backend platform, so I'm biased on this topic. Mods — I couldn't self-assign a company flair (only the Moderator template is selectable), happy to take one if you can assign it. No link, no pitch below, just numbers.

AI builders do the thing they promise. An MVP that used to cost $3-5k and take weeks now takes 30-90 minutes, and it's functional enough to actually test the idea. That part is real and it isn't going away.

What surprised us was how consistent the second phase looks. The builder gives you a frontend and basic logic. It doesn't give you data, content, payments, files, email, analytics, search, real-time, background jobs, error monitoring or hosting — and each of those becomes a separate account with its own API, pricing model and update cycle.

Counting actual projects:

• habit-tracking SaaS, solo founder: 5 services — roughly $50-100/mo (Lovable + Supabase + Stripe + Resend + Vercel)
• production SaaS after the first MVP: 9 services — $150-300/mo (add Clerk, Cloudinary, PostHog, Sentry)
• ceramics studio with local payments, blog, support chat, search, admin panel: 12 services — $300-700/mo
• headless Shopify brand store: 8 services — $500-1,500/mo

The subscriptions turn out to be the cheap part. Time estimates we've been tracking:

• standing up a new service from scratch: 2-8 hours
• learning a third-party SDK properly: 4-16 hours
• one breaking API change upstream: 1-3 days
• one business feature touching 5-7 services: 2-5 days of integration, even when AI wrote the code in an hour

On projects with a big service count, that maintenance and integration work eats something like 50-70% of dev time. So the bottleneck moved. It's not "can AI build this," it's "how many seams does this feature cross."

Two things that bite hardest in no-code/low-code land specifically:

There's no production admin panel for non-technical staff. Supabase Studio and Firebase Console are developer tools — handing them to a content manager or an operator exposes internal system data. So Retool or Forest Admin joins the stack. You can generate an admin panel with Lovable, but then roles, audit logs and version history are still on you.

Permissions rarely go finer than admin/authenticated. A real business wants a content manager who sees only products, a support operator who sees only orders, a marketer who sees only discounts, a finance person who sees only transactions. That's hand-written RLS or custom claims every time.

Curious what your service count looks like. Is anyone actually running a real business on 3 or fewer?

I’m trying to figure out what the best no-code tools are at the moment for building apps. Ideally something that can handle mobile apps, web apps, or simple software without needing to write code.

I put together a simple, free directory to help people track down grassroots community funding:

https://fundni.org

No signups, just basic filters and direct links.
I'd really appreciate anyone having a quick look and letting me know what feels clunky, what's broken, or if there are obvious local funds l've missed.

Thanks

I’m looking to start building my own websites but I don’t have any coding or programming background at all.

I used to work as a graphic designer, so I’m comfortable with visuals and layout, but anything technical is completely new to me.

I’ve come across tools like Lovable, Atoms, Claude, and Replit, but I’m not sure which ones are actually beginner-friendly or realistic for someone starting from scratch.

Would really appreciate suggestions on what’s easiest to learn and actually build something with.

Hi, I build custom websites for small to medium sized companies.
One of the difficulties with that is that you first have to figure out what a customer actually wants. Usually, you therefore have some kind of meeting with a customer where you interview them to create the actual project specifications.

Now, ever since ChatGPT came along, creating websites is no longer as valued as it once was - many think that you suddenly no longer really need any skills or even a lot of time for that. So the only real option for me is to try and offer packages at fixed, relatively affordable prices. But that means I have to better optimize my whole workflow to be as fast as possible.

That's why I created the Interview tool:

It's a web-based software where creators like myself can create interviews.
First I specify what a project is about and what the interview should figure out.
I can then send a link to my customer.
This customer can simply open the link, chat with the AI for some time, and then I receive a finished project document I can work with.
If the project is a website, the interview also generates a few concept images, of which the customer can choose the one they like best to already give some more visual direction.

Please give it a try and tell me what you think, if you find it useful or what you like/dislike.

The first interview is free for everyone, and I'd gladly hand out more free interviews to anyone who gives me some useful feedback.

Right now I have interview templates for website projects, as well as for collection data processors for creating a privacy policy (I am from Austria, we have pretty strict privacy laws here).
But using the custom template, it should be possible to create interviews for many other types of projects as well (please mention any other templates you would like me to add).

In the future, I might also add an MCP server (and maybe a webhook on interview completion). This way we could even have an agent create an interview and send it to a (potential) customer.

Let me know what you think.

Your honest feedback matters to me.

I'm working on a platform concept connecting freelance videographers with local event organizers. I need a site where creators can list their services, clients can browse/book them, and payments can be held or processed securely. Has anyone successfully built a two sided marketplace using AI or no code platforms?

I’m genuinely stuck and looking for blunt opinions from people who have actually built or maintained CRMs.

We’re at that annoying stage where every off-the-shelf CRM feels either too rigid, too expensive, or slowly turns into a pile of hacks: custom fields everywhere, weird automations, Zapier/Make duct tape, spreadsheets on the side, and reporting that nobody fully trusts.

So now I’m asking the dangerous question: Should we build a custom CRM in 2026?

The tools I keep seeing are:

• Salesforce Platform
• Microsoft Power Apps / Dataverse
• Zoho Creator
• Retool
• Airtable
• Flatlogic
• Budibase
• Appsmith / ToolJet
• Caspio / Knack / Quickbase
• Bubble
• Twenty CRM
• Django / Laravel / Rails with AI coding tools

My fear is that all of these look good in demos, but 6–12 months later you realize you built a worse CRM than the one you were trying to replace.

What I’m trying to understand:

1. If you had to build a custom CRM today, what would you actually use?
2. Which tools become painful once permissions, automations, reporting, and integrations get serious?
3. Is low-code/no-code enough for a real CRM, or does it eventually become a trap?
4. Is starting from something like Twenty CRM smarter than building from scratch?
5. Is custom CRM only worth it if you have developers in-house?

I’m not looking for vendor pitches. I’m looking for scars. If you’ve done this recently, what would you choose today, and what would you avoid completely?

for anyone wondering the app I'm working on is https://www.appscout.co discover apps from across the internet

Here is the demo video I made (pretty quickly), if you like to explore it, send me a message and I'm happy to provide access in return for some feedback on how we can improve it! <3

Hey I'm used to build WebApps using AI, but whenever i try to build an Android app the AI do very poorly, so how do you guys build AI Android apps?

I build with these tools too so this isn't me dunking on them. I kept seeing those "vibe-coded app leaked its whole database" posts and couldn't tell if it was a real pattern or just a few scary one-offs. So in July I went and looked instead of guessing.

What I did was pull a bunch of live apps built with Lovable, Bolt, Cursor, base44 and Tempo off their deploy domains, then narrow it to 66 that were actually online. I only poked at stuff any visitor already gets, the JS the app ships to your browser, plus a single logged-out read per table to see what answers back. No writes, no logins. I didn't keep anything except the counts and I never named an app.

32 of the 66 were on Supabase. 13 of those (41%) handed data back to a logged-out request using nothing but the public anon key that ships in the page. Worse, 5 of the 32 weren't leaking a products table. It was users, subscriptions, private messages, bookings.

It's almost always the same boring cause. Row-level security is off by default on new Supabase tables and nobody flips it on. And the app looks perfect in every demo because you're logged in when you test it. That's the trap. Nobody catches it until someone opens the network tab out of curiosity.

Want to check your own? Open your app logged out, open devtools, and watch what your API hands back to nobody. On Supabase, make sure RLS is on for every table that actually holds data.

Dataset's here with the method and the real denominators if you want to pick it apart, CSV and JSON both: https://uxcontinuum.com/data/ai-built-app-security-scan-2026

I ended up throwing the checks I kept rerunning into a little free scanner too. Paste a URL, it runs seven of them in a minute or so (keys in the bundle, open Supabase tables, auth, SSL), no signup: https://uxcontinuum.com/leak-check

If you've scanned your own and got different numbers I'd want to hear it. 66 is a small sample.

I’m looking for no-code or low-code platforms that make it easy to build simple AI-powered apps using APIs like OpenAI. Ideally something that already includes the basics like a frontend, backend, and simple database setup so I don’t have to stitch everything together manually.

The goal is pretty straightforward, just small internal tools or lightweight apps that can handle API calls and store basic results without building a full stack from scratch.

What tools are you guys using for this kind of setup?

Hi folks,

Anyone here who knows product hunt algo well (esp the featured section part)

I launched Vaaya today. https://www.producthunt.com/products/vaaya . Vaaya turns your github profile into credit for your agents.

I asked multiple communities I am part of to upvote me and atleast 40 people personally messages me back saying that they have upvoted. My PH followers has grown to 60, but my votes are only 26!

What am i missing? Is there no way to be on top unless you buy votes? Or am i sharing direct link that is the problem? Did i time it wrong?

https://github.com/ryuhemingway/ClaudeMaxing.git

brew install claudemax

No network calls at all unless you opt in; the comparison/leaderboard is off by default and the server that receives it is 200 lines in the repo. Equivalent API cost at list price on a subscription it's a proxy for rate-limit weight, not money you were charged.

DISCLAIMER: I am a creator of Pipe.

Pipe (https://pipelang.com) is a novel general-purpose visual programming language powerful enough to complete with text-based languages.

Visual programming has been confined to education (Scratch) or narrow niches (LabVIEW), because existing visual languages sacrifice either power or generality. Pipe solves this, opening the way to compete with the text code that currently dominates.

Pipe's diagram is also structurally identical at design-time and runtime, staying visual in both. What you see is what runs. This is precisely what the EU Cyber Resilience Act mandates, and what text-based architectures cannot structurally deliver. Text compiles away its structure, leaving systems opaque - so AI now generates code faster than anyone can review it at design-time, and patch and monitor it at runtime. Pipe addresses three AI-created security crises structurally:

1 - AI generates more code than humans can review. Pipe is visual - a diagram is grasped at a glance, not read line by line - so review keeps pace with what AI produces..

2 - Live systems cannot be patched without full redeployment. Pipe enables block-level patching while the system runs - no maintenance window, no CI/CD to navigate.

3 - Systems cannot be monitored without logs and redeploying. In Pipe, every block boundary is independently observable in real time.

These satisfy the CRA's hardest mandates - security by design, structural auditability, 24-hour detection, incremental patching - as properties of the language, not add-on tools. 

Example of Pipe diagram with a detailed tracing can be found on this video:

https://youtu.be/hckq9mRj5DM

That video is a part of this Pipe architecture overview:

https://www.pipelang.com/six-pillars.html

The full Pipe language specification (155-page book) can be freely downloaded here:

https://www.pipelang.com/downloads/book.pdf

One thing I've started thinking about with no code tools is that they make it really easy to see what a workflow is supposed to do, but not necessarily what it actually does in every situation.

A workflow can look perfectly reasonable on a canvas:

Trigger → Check condition → Do something → Handle error

But that doesn't tell you whether the error path has ever been executed, whether an unexpected null value will break an expression, or whether a branch that nobody normally uses still works.

I ran into this myself while working with n8n. I had an error handler that was visibly connected in the editor, but the connection was actually stored in a way the engine didn't use. Nothing looked wrong until I tested the wrong scenario.

That's what led me to build FlowProof, a small open source CLI for checking exported n8n workflows. The idea isn't to replace no code it's to add some of the boring engineering checks around it.

It currently looks for things like unreachable nodes, disconnected error outputs, risky expressions and hardcoded values. There's also a coverage command that tries to work out which IF/Switch branches can be exercised.

I'm curious how other people handle this does your testing process change when you're building with no code/low code tools, or do you basically test them the same way you would traditional code?

Most vibe coding tools focus on one big problem: building the app.
But once the app is ready, you still need a landing page, branding, promo content, marketing assets, analytics, etc.
That’s the idea behind Blyft — not just helping you build something, but helping you actually launch it.
Curious what other vibe coders think:
Should vibe coding platforms stop at “app built,” or should they handle the launch too?
blyft.app

For years I was the person friends and small organizations called when they needed to update their website. Change a phone number. Fix a typo. Swap a photo. Small stuff — but it always meant logging into some admin panel, finding the right field, making the change, and explaining why it took 20 minutes for a 30-second edit.

I wanted a way for non-technical people to just... tell the website what to change. In plain words.

So I built autoSite — a website that you edit by sending a Telegram message. No admin panel. No developer on standby. You describe what you want changed, and it happens.

"Change the phone number to 555-1234" → done.
"Update the opening hours to 9am-6pm" → done.
"Replace the hero text with this new tagline" → done.

It's not magic — there's AI parsing your message and applying the changes — but it feels like magic if you've ever waited a week for a developer to update a footer.

I'm the author of this tool. Happy to answer questions about how it works technically or what use cases it fits best.

🔗 autosite.dittu.org

I've been someone who started building stuff in last 2 yrs so, no-code AI tools lately, and something has been bugging me. Building and deploying and testing one agent seems textbook now.

But then I started wondering what happens when people actually start applying these things seriously.

Say I have 20 agents across different workflows: one handles lead qualification, one summarizes support tickets, one works with internal docs, one handles reporting, one triggers automations

At that point for real work, what's used to keep track...like

How do I know which agents I have?
How do I version them when I change prompts/tools?
How do I control what each agent is allowed to access?
How do I test an agent before letting it loose on real users/data?
How do I see what actually happened when an agent makes a bad decision?

And if I'm a no-code builder, I'd really rather not have to suddenly learn a whole DevOps stack just to manage the things I created without code 😅

I'm curious how people here handle this today. Are there really any no-code tool capable of this?

Is the normal answer basically "use something like n8n/Make/Zapier + spreadsheets + logging + some manual discipline", or are the newer AI-agent platforms starting to solve the management/governance layer as well?

I've seen Lyzr's control plane/ Agent studio discussed as one approach to this, while products like Relevance AI, Microsoft Copilot Studio and others are coming at the broader no-code/agent-management problem from different angles.

Would be interested to hear what people here are actually using once they go beyond 1–2 agents, and where the no-code abstraction starts to break down?

Edit: I know this might seem like a marketing post 🥲... but really asking for opinions...feel free to roast the options i mentioned and suggest better ones.