Is vibe coding the problem?

The short answer: not the way people mean it. The usual complaint is that vibe coding floods the world with products nobody wants. But in Reddit builder posts from 2025 and 2026, founders who say they built with AI tools are about half as likely to be stuck on getting customers (11.5% against 22.4%). That’s not because they’ve solved it. It’s because most of them haven’t got that far: 57% of the stuck ones are stuck on the build itself, and what breaks is security, databases, deploys and code they can’t follow anymore. The few who posted revenue weren’t doing any worse than everyone else.

Below: how many builders use these tools and which ones, what they get stuck on, what the posts actually describe, whether the products make money, and a checklist I’d run before launching anything I vibe coded.

How many builders use AI tools, and which ones

Far more than say so. Only 2.13% of builder posts in 2026 say outright that the founder built the product with AI (“I vibe coded it”, “built it with Cursor”, “I can’t code”), up from 0.22% in 2022. People don’t usually mention their tools, so treat that as a floor. A wider measure, any post that names an AI coding tool at all, went from 0.1% to 4.8%.

Which tools come up has changed fast:

Claude Code went from nothing to the most-named tool in a year: 0.3% of builder posts in 2025, 2.3% in 2026. Codex rose the same way (0.1% to 1.3%). Cursor held steady at around 1.7%. The app builders that made “vibe coding” a phrase, Lovable, Bolt, v0, all peaked in 2025: Lovable fell from 1.2% to 0.9%. The talk moved from tools that build an app for you to agents that work in your code. These are mentions, not users, and a lot of mentions are comparisons and complaints.

What they’re stuck on

For posts from 2025 and 2026 where the founder names what they’re stuck on, here’s the split. The ± is the 95% margin.

More than half the stuck founders who built with AI are stuck on the product itself, against about a quarter of everyone else. Every later stage is lower for them: getting customers, launching, running the business. That isn’t a sign they’re better at selling. It’s where they are. Building got easy enough to start, and not easy enough to finish.

Part of this is how people write. If you mention Cursor in a post, you’re probably talking about the build, so naming the tool and being stuck on the build go together. But the gap is wide, and everything else in the data points the same way.

Where the build breaks

Founders who built with AI write longer posts (282 words on average when stuck on the build, against 195), so I counted mentions per 1,000 words rather than posts. This is 409 AI-built posts stuck on the build, against 8,880 from everyone else:

Security comes up 2.4 times as often, the most of anything. Then code they can’t maintain, databases, deploying and bugs, all well above everyone else. Payments (1.4x) and scaling (1.2x) are closest to normal. Nobody here is stuck because too many users showed up. They’re stuck making the thing stand up properly in the first place.

What the posts actually describe

Counts only go so far, so I read a sample of these posts. The same few stories come up again and again.

It works until it gets big. The first screens come fast. Then, somewhere past a handful of features, the AI starts losing track: a fix in one place quietly breaks something “two files away”, and a founder who can’t read the code can’t tell why.

They don’t know how their own app works. One founder put it plainly: they built an assistant with Claude, then realised they had no idea how their own app worked. Others ask how to make it “secure, production-ready” without knowing where to start. That’s fine for a prototype and frightening once people pay.

The unglamorous parts are hard. Logins, payments, user accounts, email. Landing pages are easy; a full product with real accounts is where people say the tools “get confused”.

Security nobody checked. API keys sitting in the browser, a paywall you can skip, a database anyone can read. One post told the story of a founder whose app went viral and shut down within a week because people were bypassing the paywall and burning through his API keys.

Getting it off the builder. Moving from an app builder to real hosting, or from a prototype tool into a code editor, is its own project.

Do products built with AI make money?

I read every Reddit title from 2025 and 2026 where a founder stated their monthly revenue (that’s How much do indie founders make?). Of those 390 founders, 16 said in the post that they built the product with AI tools.

16 is too few to say they make more, and the ranges overlap. But there’s no sign they make less. The ones who get as far as revenue look much like everyone else. Which fits: customers don’t care how the code was written, only whether the thing works.

And when they launch on Hacker News

One place it does show is Hacker News, though that’s about AI as the product rather than the tool. Launches with AI in the title went from 5% of Show HN posts in 2022 to 35.1% in 2026, and reached 100 points about half as often as everything else (1.02% against 1.95% this year). Readers there have seen a lot of them. More in Does launching on Show HN still work?

So, is vibe coding the problem?

Not for selling. Across all builders, the share stuck on getting customers rose from 16.7% to 26.3% between 2022 and 2026, and that rise comes from everyone. Founders who built with AI are, if anything, less likely to be stuck there, because they’re stuck on the step before.

What vibe coding does is bring far more people to the starting line with something half built. Most of the pain is in the half that isn’t: security, data, deploys, and code nobody understands. The ones who push through hit the same wall as everyone else, finding people who’ll pay. I wrote about that wall in Building got easy. Getting anyone to care didn’t.

Before you launch something you vibe coded

This is what I’d check, drawn from what the stuck founders say went wrong:

1. Find your keys. Search the code that runs in the browser for API keys and secrets. Anything there, anyone can take. Move them to the server.

2. Try to skip your own paywall. Log out, open the paid pages directly, call the API without paying. If you can get in, so can everyone.

3. Lock the database. If you use Supabase or Firebase, check that one user can’t read another user’s data. Make a second account and try.

4. Write down how it works. One short file: what the app does, where the data lives, how money moves. Give it to the AI at the start of every session, and read it yourself.

5. Test the money path after every change. Sign up, pay, use the paid feature, cancel. The posts are full of fixes that broke something else.

6. Know where it’s hosted and how to move it. If it lives inside an app builder, find out how you’d get it out before you need to.

7. Get one human to look. Before real users and real payments, pay a developer for an hour to review security. It’s the cheapest insurance in this list.

8. Then spend as long on customers as you did on the build. That’s the part that decides whether any of the above mattered.

Where they post

r/SideProject and r/buildinpublic have the most, which fits: they’re where people show what they made and post progress. There’s more on each in Which startup subreddit is for what?

What I can’t tell you

“Built with AI” is what the post says, found by a text match. When I read 40 matches at random, 33 were right (about 83%); the misses were mostly AI products or demo videos. Most people who build with AI never say so, so the “everyone else” group has plenty of them in it, which if anything shrinks the gaps above. What each post is stuck on is a model’s label. The topic counts are word matches, so “security” in “job security” counts the same as a leaked key. And this is what people post about, not whether their products work.

How I did it

The posts are the seven builder subreddits from the builder dataset: 64,722 posts from people building something in 2025 and 2026, of which 1,164 say they built it with AI tools. A product that is itself about AI doesn’t count. The tool counts are any mention, with Bolt, v0 and Copilot narrowed after reading samples (“bolt-on”, “v0.1”, “an AI copilot for”). The revenue split uses the hand-checked claims from the revenue post, and I read each of the 16 AI-built ones to confirm. The 95% ranges come from the counts and, for medians, from resampling.

Cite as: GTM for One (gtmforone.com), “Is vibe coding the problem? What founders who built with AI actually get stuck on”, https://www.gtmforone.com/blog/is-vibe-coding-the-problem.

Once the build stands up, the next wall is finding the few people who’d actually pay for it. That’s the part I built GTM for One to help with.