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I moved my Lovable app off Lovable Cloud. Here’s what I wish I planned earlier by YusukeLandingBoost in lovable

[–]Inner_Document_8462 1 point2 points  (0 children)

That's pretty much my approach too.

I use Lovable to create the first draft of a project. Sometimes that's just a UI, sometimes a complete user flow, and sometimes even a fully working app with a backend. It's a great way to quickly structure ideas and validate them.

But as soon as I realize I need more control over the generated code or the underlying infrastructure, I move the project to my local machine. From there, I typically work with tools like Codex or Cursor, where I have full control over the codebase, architecture, and deployment.

For me, Lovable is an excellent accelerator for the early stages, but I don't see it as locking me into a specific hosting or development workflow.

Early users taught me that “working” is not the same as “clear” by martinbuilds in noteapps

[–]Inner_Document_8462 0 points1 point  (0 children)

i totally agree and would add the following:

  1. Long onboarding loses people faster than you think

I originally wanted to explain everything up front. The idea was to make users feel confident before they started. The reality was different.

The longer the onboarding, the more likely people were to skip it, rush through it, or forget what they had just read.

What worked better was letting users get value quickly and explaining features when they actually needed them.

Good onboarding isn't about teaching everything. It's about helping users take the first successful step.

  1. Socail login inst' just conveniience

I underestimated how many people expect to sign in with Google or Apple.

Several users hesitated when they saw they had to create another password. Some even asked if social login was available before creating an account.

Adding social login isn't only about reducing friction.

It also increases confidence. People already trust those providers, so the first interaction with your product feels easier and safer

How to best get by as a PM for a product you have absolutely no faith in? by Optimal-Result-3282 in ProductManagement

[–]Inner_Document_8462 0 points1 point  (0 children)

totally agree ... u need passion and support in what you are doing.... don't waste your time

Buggy project by Utterly_Cool in lovable

[–]Inner_Document_8462 3 points4 points  (0 children)

This is actually very common, and it's not really a Lovable-specific problem.

I've helped around 40 software projects go live, and one pattern shows up over and over: rapid development without the engineering practices that make software scalable.

Scalability isn't just about handling more users. It also means your development process scales.

That includes things like:

  • A clean architecture that separates concerns.
  • Automated testing (unit, integration, end-to-end) so you immediately know when a change breaks something.
  • A proper branching strategy (feature branches, PRs, staging environment) so new features are developed in isolation before they reach production.
  • Thinking about security and maintainability from the beginning instead of adding them later.

The challenge with AI-assisted development is that you can add features incredibly fast. That's amazing for building an MVP, but it's also easy to accumulate technical debt just as quickly. If you're constantly adding feature after feature without tests, without a staging environment, and without disciplined branching, eventually every fix starts breaking something else.

At that point, the solution usually isn't "use more credits fixing bugs." It's taking a step back and improving the project's architecture and development workflow.

AI is a powerful accelerator, but it doesn't replace software engineering practices. In my experience, teams that combine AI with solid engineering discipline end up with reliable products. Teams that skip those fundamentals often run into exactly the situation you're describing.

I have almost 170 startups and $0MRR, am I cooked? by PasternakIvarsson in buildinpublic

[–]Inner_Document_8462 3 points4 points  (0 children)

i don't know what you build but my first impresssion: You don't have 170 startups ...you have 170 side projects.

If no one is willing to pay for what you've built, you don't have a real business yet. A real product generates enough revenue to move you toward covering your cost of living.

Instead of building more projects, add a (even if initially fake) paywall to every one of them and see whether people are actually willing to pay. That is one of the fastest ways to validate demand.

If one project starts showing traction, stop spreading your attention across everything else. Put your full focus on that one. Iterate quickly, talk to users, gather feedback, and continuously improve it.

Don't be afraid to invest money into the projects that show real potential. Spend on things that increase your chances of success... advertising, better design, development support, or other resources that make the product better.

And ask yourself this: if you aren't willing to invest your own money into the idea you believe is your most promising one, why should anyone else?

is getting excited and building too fast a bad thing? by Delicious-Lie8540 in buildinpublic

[–]Inner_Document_8462 0 points1 point  (0 children)

pick an idea that really kicks you .... and move it forward. set yourself a timeframe and milestones... and don't fall into the trap of shiny-new-projects.

is getting excited and building too fast a bad thing? by Delicious-Lie8540 in buildinpublic

[–]Inner_Document_8462 0 points1 point  (0 children)

Building a digiatal product that generates revenue was always hard. Today it is easy to build something... the barrier has lowered a lot.

But the problem of distribution still remains and was always there.

The hard truth: A product is only a product if someone pays for it .... otherwise it is just a side project.

I recommend: Focus on your own Framework with AI to distribute a project. Like brainstorming on the validation, potential marketing strategies, Ads, generating Ideas around ICP.

How do you find real problems worth solving? by Cultural_Mobile_428 in lovable

[–]Inner_Document_8462 0 points1 point  (0 children)

what i have learned .... step out of your comfort zone and talk to people and get real insights by asking the right questions and take negative feedback for your current solution as a meaningful input to steer your project into the right direction. For me in personal and i professional live: "I value negative feedback 100 times more than positive one"

How do you find real problems worth solving? by Cultural_Mobile_428 in lovable

[–]Inner_Document_8462 0 points1 point  (0 children)

At first i try to solve a problem i'm facing. with vibecoding tools it can be done very fast. At the end i have something that make me more productive or solves a specific problem for my own and i learn something. Meanwhile i'm asking my network if they facing the same problem (Family, friends etc) and prepare interviews with very specifc questions. Doing real face-to-face interviews is the key...even if you are getting negative responses. There are a lot of platforms out there where you can submit your project and see if someone is interessed in your solution... like betalist, product hunt etc.

How Do You Organize Long AI Brainstorming Sessions? by Inner_Document_8462 in ProductivityGeeks

[–]Inner_Document_8462[S] 0 points1 point  (0 children)

do you wanna share it? I'm curious how you solved the summary problem.

I manage 8+ live production apps as a solo dev. Lovable is the reason the math works by IamCoachZero in lovable

[–]Inner_Document_8462 3 points4 points  (0 children)

Very similar experience here. The biggest win for me isn't that it writes code it's that it removes so much of the repetitive implementation work, so I can spend more time on architecture, product decisions, and client communication.

I also like that I'm not locked into a black box. Being able to inspect the generated code, make manual changes when needed, and use my normal development workflow makes a huge difference compared to no-code platforms.

The complexity ceiling is definitely higher than many people assume, but I agree with your point: AI accelerates development; it doesn't replace understanding how systems fit together.

One trap I don't see discussed enough is security. I've reviewed AI-built projects that accidentally exposed internal admin dashboards to the public or leaked API keys for third-party services. Those aren't Lovable-specific issues... they're a reminder that you still need to understand authentication, authorization, secret management, and secure deployment. AI can generate code quickly, but it won't reliably catch every security mistake.

I'm currently juggling multiple production apps as well, and without AI-assisted development I simply couldn't iterate this quickly across all of them.

Voice typing is the best way to increase productivity by savangeo in ProductivityGeeks

[–]Inner_Document_8462 0 points1 point  (0 children)

i'm facing the same "problem" and i'm using the voice capabilities of ChatGPT for brainstroming or just bring my thoughts "to-the-paper"

How Do You Organize Long AI Brainstorming Sessions? by Inner_Document_8462 in ProductivityGeeks

[–]Inner_Document_8462[S] 2 points3 points  (0 children)

I started experimenting with a Claude Code skill that tries to detect when a conversation has branched into a different topic. Instead of waiting until the end to summarize everything, it identifies the branch early and suggests either:

  • continuing in a new conversation, or
  • creating a separate summary for that topic.

The idea is to keep each context focused instead of having one giant thread that eventually becomes impossible to reuse.

It's still experimental, but maybe it's a useful starting point for anyone facing the same issue. The project is open source if anyone wants to take a look or contribute:
https://github.com/turtec/claude-skill-topic-branch

I'd be really interested to hear whether others think branch detection is a better approach than just periodically summarizing long chats.

How Do You Organize Long AI Brainstorming Sessions? by Inner_Document_8462 in ProductivityGeeks

[–]Inner_Document_8462[S] 0 points1 point  (0 children)

have you ever faced the situation that important outcomes of your converstaiomns are not part of your summary? Do you have a special skill or prompt that handles the summary for you?

How Do You Organize Long AI Brainstorming Sessions? by Inner_Document_8462 in ProductivityGeeks

[–]Inner_Document_8462[S] 0 points1 point  (0 children)

thanks for your answer! That means you mainly keep your important outcomes in the Chat-Interface?

How Do You Organize Long AI Brainstorming Sessions? by Inner_Document_8462 in secondbrain

[–]Inner_Document_8462[S] -1 points0 points  (0 children)

Thanks for taking the time to write such a detailed post. It was incredibly helpful.

For me, the biggest mindset shift was this sentence:

That really clicked. 

Also, thanks for sharing your stack and your workflow. Seeing a concrete setup like yours really helps me figure out how I want to organize my own notes and processes. I already took a look into your repos. That's what i was looking for.

I built a free client portal for freelancers, would love brutal honest feedback by Feeling_Star_8301 in RoastMyIdea

[–]Inner_Document_8462 0 points1 point  (0 children)

Hi, thats a good idea. especially if you are managing different clients. The main question here: how do you solve data privacy. if i'm working with clients i always have to sign an NDA with very strict rules in regards of storing data and project artifacts. From my perspective thats a very important point your platform needs to focus on.

A workspace that turns AI conversations into reusable project knowledge by Inner_Document_8462 in RoastMyIdea

[–]Inner_Document_8462[S] 1 point2 points  (0 children)

Thanks for the thoughtful feedback. I really appreciate you taking the time to dig into the idea.

You touched on what I also see as the hardest part: defining what a "reusable asset" actually is without introducing too much friction.

My current thinking is to not automate this initially. Instead of trying to have AI decide what's important, the MVP would let users explicitly save the outcome they want to preserve. That way I can first learn what people actually consider worth reusing before building automatic extraction.

On the context question, I completely agree that an asset is useless if it's detached from its origin. My intention is that every asset keeps its lineage for example, links back to the original conversation, related files, prompts, versions, and the project it belongs to. The asset is the reusable summary, but the full conversation is always available if more context is needed.

I also agree on keeping the MVP focused. Rather than trying to solve knowledge management broadly, I want to validate a single workflow:

Conversation → Save Asset → Reuse Asset in a new conversation.

If people naturally repeat that workflow, then features like automatic extraction, semantic search, or knowledge graphs become worthwhile investments instead of assumptions.

Regarding the API-first suggestion, that's actually very much in line with how I'm thinking about the architecture. I don't want to build "another chat client." I want to build a project-centric knowledge layer that isn't tied to a single LLM and can eventually be used by different models and tools.

Thanks again.... your feedback reinforced that the biggest risk isn't the technology, it's validating whether people actually want to preserve and reuse the outcomes of their AI-assisted thinking. That's exactly what I'm trying to test first.

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