Currently playing around with @bolt.new after being inspired by @gabe and building a bunch of mini apps, mainly for fun. Haven't pushed any to production yet but so far I'm enjoying it bar the odd hiccup where I have to roll back a few times to fix a stubborn error.

I've also looked into @Lovable and it seems pretty cool but wanted to see what people had to say about it. Is there any reason to pick one over the other and which one have you settled on?

Hey PH

I want to share something that's been sitting with me not a product launch today, but a shift in thinking that I think every founder here should stress-test.

I've been having a lot of fun exploring AI and using tools like @Cursor, @bolt.new, @Lovable, and @Warp to learn how to build and make some apps for myself! I'm also noticing a tremendous amount of growth in folks creating their own apps using these same tools which has me wondering... if a company wanted to acquire someone's app or tool that was built via vibe coding, would it matter how it was built? Does the method of how it was built impact the valuation?
In my idealistic eyes, I'd like to think it doesn't. As an acquisition is often much more than just the tech but also the user base, brand, and even team behind the product. If anything I think that acquiring a product that has been "vibe coded" and putting them into capable engineering hands would only enhance the product...or a least make the code base cleaner.
I also believe that talent that is able to create stunning products with AI is currently a small percentage of folks, and that companies should be investing in acquiring that talent (either independently or via product acquisition) so that they can stay ahead in innovation while learning how to implement AI tools more efficiently in their orgs.
Very curious to hear what you all think!

I work at an early stage startup and I'd estimate 70-80% of our codebase is vibe coded (510k lines). To be clear, it's not 1 shot "build this feature." More like, "implement get_slim_documents for Jira in the exact same way we did it for the Confluence connector."
Comfort with AI coding tools is actually something we gauge during interviews/work trials. Looking at our peer companies, it's exactly the same.
My hypothesis/assertion is that companies founded ~2022+ are fundamentally intertwined with "vibe coding." In 5 years, programming will connote vibe coding more than it will connote non-AI assisted work.
Am I crazy? Pigeon-holed in the SF startup world? Naive? Would love to hear more thoughts/diverse perspectives on this.

Hi, I m an app developer who s shipped many projects the old-school way (hand-coding) for over a decade. Recently AI tools have exploded - speeding up my production like crazy.

What s happening:

- Idea to MVP: Creators focus on ideas while AI writes most of the code.

I'm what you might call a gringo vibe coder.

No dev degree. No traditional background. Just me, Cursor, Claude, and AI... figuring things out together.

Rick Rubin said it best: "In the past, for music, you had to go to the conservatory and study for years... then when punk rock came along... if you had something to say, you could say it." He calls vibe coding the punk rock of coding.

about to Launch a product for creators after building for a few weeks to months.
Started as a way to get into vibe coding and just got real useful real quick lol.
But the goal is still that - mix my skills and knowledge as an engineer with the good parts of AI coding.
So i learned a few of what to need and have

• Claude.md file

• best coding practices section

• pretty heavy compartmentalization & file structure separation

• certain ways to prompt

• ask for implementation plan before telling it to code

But i feel like all i learned is about directing prompts - im wondering...

what are you guys finding are the best .md or deeper ai vibe coding tricks that are helping you save time? be more efficient? debug ai less or help it get it right the first time? whats your vibe code tips and tricks?

Here's my hacked-together, messy, voice-based dev environment:

1. Voice-driven loop with screen-shotting so the LLM in the loop can see what's in my terminal and editor. The prompt varies depending on what I'm trying to drive with this loop.

2. A few tool definitions that give read access to files and URLs.

3. A tool the LLM can send a block of output to that generates keyboard events, so the LLM can drive any editor/terminal.

4. A separate process watching a directory and constantly making LLM-driven git commits. (git autosave).

I have some pieces of this running most of the time. But I'm lazy, and doing other stuff, and I also try to use a variety of editors and tools, to see what's good lately. Which ... no stability, so my hacked-together stuff is always broken.

I don't want to replace @Windsurf / @Cursor / Claude code. A seriously good agent and expert-system dev toolkit is a lot of work.

I've never coded. Not a single line. But I m tired of just watching cool ideas fly by. So here I am turning a wild idea into something real with AI

as my co-pilot.

My toolkit? ChatGPT, Cursor, Replit.