Been using Loveable for a few months now and genuinely love how fast I can go from idea to working app. But I keep hitting moments where I think — "okay, this is where I need something more surgical."

Curious how others here actually work in practice:

Do you use Loveable as your entire stack, or do you layer in tools like Claude Code, OpenAI Codex, or similar agentic coding assistants alongside it?

My current experience: Loveable is incredible for spinning up UI, scaffolding, and rapid iteration. But when I need to dig into complex logic, refactor a messy module, or debug something subtle, I find myself wanting a tool that can reason over my codebase at a deeper level.

Some specific questions I'm wondering about:

• Do you ever export your Loveable project and then hand it off to Claude Code / Codex for heavier lifting?
• Or have you figured out prompting strategies inside Loveable that make external tools unnecessary?
• Is the "vibe coding only" approach actually viable for production-level projects, or does it have a ceiling?

Would love to hear real workflows, not just theory. What's actually working for you?

Feels like getting users is hard… but keeping them is the real final boss now 😭

So I’m curious:

What improved your SaaS retention way more than you expected?

Not generic advice like “build a better product”…

I mean actual things that noticeably reduced churn or made users stick longer.

Stuff like:

• better onboarding?
• email followups?
• usage based pricing?
• removing features?
• faster support?
• community?
• making the product simpler?

I keep noticing some products with average features still retain insanely well while technically “better” tools get abandoned in 2 days.

Feels like retention is becoming more psychology + habit building than feature building now.

Would genuinely love to hear what unexpectedly moved retention for your product.

I'm an first time founder running my own content production agency where I help businesses get more eye and real $$ through my explainer videos.

If you know how agency works then you probably knows that getting client and reaching out is the most boring work to do. That's why, as in CS student undergrad I'm building my own JARVIS, who can run my system and perform all the day to day tasks while I'm talking talking to him like a old friend on a phone call (imagine tony Stark's Jarvis in iron man movie)

I do not have a complete knowledge about digital or saas products but I do understand it's backend structure. I'm building it on my own and u can say I have built a working model about 30% now.

If anyone has experience in something like this then I would love to connect with and if thing goes well then we can build amazing software for personal use and then I also have an idea to scale.

So i've been going down this rabbit hole of trying to bu͏ild an a͏pp for my small consulting business without having to learn actual coding. I keep seeing ads and posts about these A͏I no-code builders that supposedly can create full apps just from descriptions.

I'm naturally skeptical because it sounds too good to be true, but at the same time i'm spending way too much time on manual tasks that could probably be auto͏mated. My current workflow involves a lot of client onboarding, project tracking, and follow-ups that feel like they should be systematized somehow.

I've looked at a few options but honestly can't tell which ones are just marketing hype vs actually functional. Some promise they'll build and dep͏loy everything automatically while others seem more like fancy form builders.

Has anyone here actually used one of these AI app builders successfully? Like did it actually create something useful that you're still using months later, or did you end up scrapping it and going back to manual processes?

Hey everyone, i'm looking for advice on choosing the right no code platform. I've got a few app ideas that i think could work but honestly i'd rather spend my time on the business side - market research, customer development, strategy stuff - rather than getting bogged down in the technical implementation.

I've tried a couple platforms like Bub͏ble and Web͏flow but found myself spending way too much time tweaking UI elements and debugging workflows when i should be talking to potential customers. It feels like i'm still doing a lot of the 'building' work even though it's supposedly no code.

Is there anything out there that's more hands-off? Like something that can handle more of the development process automatically while i focus on the business validation and gro͏wth side of things?

Currently learning JS through JavaScript.info. Was told I should have a basic understanding of what the AI is doing since it makes so many errors. Butttt I’m skeptical? Am I wasting my time? How much do I REALLY need to know? AI seems to be getting better and better.

I'll go first.

Two things hit me recently.

Speed is the skill. You can get an idea live in days now. That's new. And it means the excuse of "I'm still building" has a much shorter shelf life. The people winning right now aren't necessarily the best builders... they're the fastest at finding out what actually works. Nobody succeeds on the first try. Ship early, find out, adjust.

How you use AI matters as much as what you build. I started treating Claude less like a tool and more like a system. Set up a knowledge base, improved how I give it context, learned how to get consistent outputs. The quality of what I was producing changed noticeably. Most people use 20% of what's available to them.

The tools we have today are better than they were 3 months ago. That pace isn't slowing down. Learning consistently and keeping up with it is the actual edge.

What's yours?

Hi! I'm building an app as a hobby and I want to use it myself and maybe share it with 5-10 friends. That's it. But I keep seeing that I can't share it unless I pay very expensive subscriptions. What would be the best option for me? My app wouldn't be very heavy, think of something like rating restaurants and keeping track of them (not the actual idea, but similar). I was working with .bubble until I stumbled into this 😞

Hey everyone, I know we are all constantly testing new stacks in here, so I wanted to share the exact workflow that finally helped me cross the finish line.

I’m a 26-year-old mechanical engineer, and I just made my first SaaS lifetime sales on my side project. (Full disclosure as per the sub rules: I am the sole founder and creator of the app, Hackamaps). Six months ago, I was juggling my day job and trying to manually learn and type out boilerplate Vite, React, and Supabase code. I was exhausted, moving way too slow, and honestly about to quit. Then I completely changed my approach, leaned into the "vibe coding" movement, and let the AI do the heavy lifting. I stopped acting like a syntax checker and started acting like a director.

Here is the exact "no-code to low-code" pipeline I used to get to my first customers:

Step 1: The UI & Frontend with Lovable I wanted to build a global map for hackers and digital nomads to find hackathons worldwide. Instead of stressing over every single component in Tailwind CSS, I used Lovable. I fed it my vision, and it rapidly generated the beautiful, responsive frontend components I needed. It got me 80% of the way there visually in a fraction of the time. After awhile it became buggy and my senior SWE told me to start from scratch and I took the leap of Faith.

Step 2: Exporting to the IDE & AI Agents Once the Lovable frontend was solid, I moved the code into my IDE. This is where I brought in my AI agents (mostly orchestrating between OpenClaw and NanoClaw). I directed the agents to wire up the complex backend stuff—connecting the Lovable UI to my Supabase database, setting up auth, and writing the logic for the interactive map pins. I barely typed any raw code; I just managed the prompts and the architecture.

Step 3: Focusing on the Customer Because I saved hundreds of hours not fighting with syntax errors, I was actually able to spend my time talking to users, doing marketing, and refining the UX.

The result is a live, functioning app, and a person paid for the membership and also recurring visitors (meaning, simply sticks). It proves you don't need an 80-hour manual coding week to ship a profitable product in 2026. The AI builds the engine; you just have to steer the ship.

For the other solo builders in here: have you experimented with exporting Lovable directly to your IDE yet? What does your AI/No-code stack look like right now for handling the backend?

AI Search is Creating a New Problem

Over the last few months, I started noticing that more people are searching directly on AI platforms instead of traditional search engines.

People are asking ChatGPT, Claude, Gemini and Perplexity things like:

• Best AI automation tool
• Best CRM for agencies
• Best email outreach software
• Best SEO tool for startups

The problem is that most businesses have absolutely no visibility into how often AI systems mention their brand.

Traditional SEO tools still focus heavily on:

• Rankings
• Backlinks
• Organic traffic
• Keyword positions

But AI-generated answers work differently.

These systems decide which brands get recommended, which websites get cited and which businesses become part of the conversation.

And currently, most businesses are completely blind to that layer of visibility.

That was the main reason I built this AI Visibility Tracker.

What This AI Visibility Tracker Does

The workflow automatically tracks brand mentions across:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Google AI Overviews

Instead of manually checking every AI platform one by one, the system automatically runs weekly and collects all visibility data into a centralized dashboard.

The tracker monitors:

1. Brand mentions
2. Competitor visibility
3. Share of voice
4. Citation frequency
5. Top cited URLs
6. Weak performing queries
7. Weekly visibility trends

I built the entire workflow using n8n, APIFY and Google Sheets.

Why I Built This Instead of Using Enterprise Tools

When I started researching AI visibility platforms, most enterprise solutions were charging somewhere around $500/month.

For agencies or large SaaS companies that pricing may be fine.

But for creators, marketers, indie hackers and small businesses, that pricing becomes very difficult to justify.

So I wanted to build a much more affordable alternative that still provides practical insights.

Right now the entire workflow costs me around $6/month when configured for weekly runs.

How the Workflow Works

Step 1: Weekly Automation Trigger

The workflow starts with an n8n Schedule Trigger.

I intentionally configured it to run weekly instead of daily because AI visibility trends usually do not change aggressively every 24 hours.

Weekly tracking gives much cleaner trend analysis while also saving API credits.

Step 2: Brand & Competitor Setup

Inside the Set Node, I configure:

• Brand name
• Domain
• Search queries
• Competitors
• Competitor domains

This step is actually very important because poor competitor configuration leads to inaccurate visibility tracking.

Step 3: AI Visibility Data Collection

For collecting AI visibility data, I used this APIFY actor.

The actor helps fetch ranking and mention data across multiple AI platforms automatically.

Then I connected it with n8n using HTTP Request nodes and bearer token authentication.

Step 4: Data Transformation

Once the API response is received, the workflow processes all the raw JSON data using JavaScript Code Nodes inside n8n.

This transformation step converts raw API data into structured visibility metrics that can easily be analysed inside Google Sheets.

Step 5: Dashboard Automation

Finally, the processed data is automatically appended into Google Sheets where the dashboard visualizes:

• Mention rates
• Citation performance
• Competitor comparison
• Share of voice
• Weekly visibility growth

I also shared the Google Sheets dashboard publicly for anyone who wants to replicate the setup.

How This Solves a Real Problem

One thing I realized while building this is that manual AI visibility tracking is basically impossible at scale.

You cannot realistically:

• Open 5 AI platforms manually
• Test dozens of prompts weekly
• Compare competitors
• Track visibility changes
• Document citations
• Analyze trends over time

Doing that manually wastes a massive amount of time.

This automation converts the entire process into a mostly hands-free workflow.

Once configured properly, the system automatically generates visibility insights every single week without requiring manual monitoring.

Why I Used n8n

I chose n8n mainly because:

• It gives full workflow flexibility
• Easy API integrations
• Supports JavaScript transformations
• Self-hosting is affordable
• Highly customizable automation logic

For anyone interested in rebuilding or modifying the workflow, I shared the full n8n template.

Full Video Tutorial

I also created a complete step-by-step video tutorial showing:

• Workflow setup
• APIFY integration
• Dashboard creation
• Authentication setup
• Google Sheets automation
• Common mistakes
• Optimization tips

Things That Broke During Testing

A few things caused problems initially.

JSON formatting errors were the biggest issue. Even a single misplaced comma inside arrays for competitors or queries can break parts of the workflow.

Authentication setup also caused problems initially until the bearer token configuration was properly configured.

Another important lesson was avoiding daily runs. Weekly automation gives better long-term visibility analysis and prevents unnecessary credit usage.

Why I Think AI Visibility Tracking Will Become Important

Most businesses are still focused entirely on Google rankings.

But AI systems are increasingly becoming recommendation engines.

People are now directly asking AI:

• what tool should I use
• which software is best
• which platform is trusted
• which service should I choose

If your brand never appears inside those answers, you are potentially invisible to a growing category of future traffic and customer discovery.

That is why I think AI visibility tracking will eventually become as important as traditional SEO reporting.

Interested to know how others here are approaching this problem. Are you already tracking AI visibility for your brand or clients?

And which AI platform do you think currently has the strongest influence on buying decisions?

I am stuck in a loop where i spend way too much time polishing the interface before even testing the concept with real users. part of me knows people only care if the app solves their problem but i always get worried an ugly dashboard will tank the conversion rate fr. how much energy do you guys honestly put into visual design before you have verified any user interest?

I am building a no-code platform for creating simple games. Been experimenting with AI-assisted workflows and can go from concept to playable prototype in about 30 minutes now. Curious what tools or approaches have worked best for others. Would love to hear what has actually sped things up for you.

I keep seeing people say “just build a good product”...

But getting the first 10 customers honestly feels harder than building sometimes 😭

So I’m curious what actually worked for real founders here.

What got you your first few SaaS customers?

Was it:

• Reddit
• cold DMs
• Twitter/X
• SEO
• referrals
• communities
• content
• manual outreach
• or something random?

And did those first customers come from:

• people you already knew
• strangers online
• or businesses you contacted directly?

Feels like the first 10 users are mostly hustle + awkward conversations + trial and error lol

Would love hearing real stories because online everyone talks about scaling… but not enough people talk about how they got customer #1.

Everyone talks about “build fast” or “just do marketing” 😭

But I’m more curious about the small things that genuinely changed your SaaS journey.

Could be:

• a tool
• a habit
• a mindset shift
• a workflow
• a piece of advice
• even a random realization

Something that made you:

• get users faster
• stay consistent
• improve conversions
• stop wasting time
• or just avoid founder burnout

Feels like there’s a lot of noise in SaaS right now… so I’d love to know what actually helped real founders here.

What ended up helping you the most?

she built the same automation twelve times. each one has a different name.

the first one was for client onboarding. the second was for a slightly different kind of client onboarding. the third was for a project that seemed different at the time but wasn't really. by the sixth she'd stopped looking at the originals. by the twelfth she was proud of how clean the structure was.

if you asked her what the core workflow was — the actual thing she kept building — she couldn't tell you. she named the use cases. she never named the pattern underneath.

i've been watching this happen for a while now. the twelve automations exist. they all work. they're all slightly different. she maintains all twelve because she doesn't know which one to throw away. the answer is none of them and also all of them: what she needs is the one she built twelve times.

someone asked me recently why their nocode stack was getting hard to manage. i looked at their workspace and counted seventeen workflows. they told me nine of them were "the same kind of thing." i asked them to describe the thing. they couldn't.

the mess isn't a mess. it's an answer to a question nobody asked out loud.

has anyone found a system for knowing when you've built the same thing twice? i still run into people who are surprised when they see it.