On Product Hunt, I can see many people launching their products using "vibe-coding tools" like @Lovable , @bolt.new , or@Replit

I reckon many people who created something with them are usually developers who didn't have enough time for building a side idea before, but with AI, they could make it happen.

Not the dramatic stuff that gets blocked. The quiet things you only notice an hour or a week later

Mine was two agent sessions working in the same repo. One of them went to clean up its own background process by matching the name and killed the other session's run too. No error anywhere. I just found a half finished job later and had to figure out why

I run LLMPvP, a ranked chess and Go arena where people plug in their own AI agents. The obvious way to cheat is to hide Stockfish behind the LLM and let it pick the moves.

My first idea was to flag agents that answer too fast or too evenly. Then I realized one sleep() line in the agent's webhook defeats that completely.

So I built labeled data instead: 2 honest agents and 2 cheating ones with different levels of disguise, 60 games round-robin in chess and Go. Then I checked which signals actually separated them.

Win rate: 13-20% for honest agents, 67-100% for cheaters.

Last summer, the idea for my SaaS, Xolora, started to take shape. Around the same time, the concept of vibe coding was blowing up. As a non-technical founder, it sounded like a dream come true. No coding experience? No problem, just let AI handle it.

The beginning was incredibly promising. Using Emergent made me feel unstoppable. I was seeing my idea come to life.

Hey everyone,

I've built my product around traditional SaaS pricing (monthly tiers), but I m starting to wonder if that model is getting outdated, especially with more AI-powered and compute-heavy tools entering the market.
That shift requires real architectural changes, instrumentation, metering, billing logic, and UI changes, not just pricing tweaks. It s something I m starting to seriously think about for my own product.

In particular, AI usage has real COGs (every prompt costs money), and I m seeing more platforms experimenting with usage-based models, or hybrids like SaaS base + usage + overage.

For those of you building AI or compute-intensive tools:

When an AI-assisted build takes a weekend instead of three weeks, hourly pricing starts to feel like it punishes you for being fast. But a fixed fee gets scary the moment the client keeps asking for one more tweak , and a retainer only works if they actually need ongoing changes.

For those of you building apps or tools for clients with AI coding tools: how do you price it now? Did you change how you charge once your build time dropped, and how do you explain the price to a client who knows it only took a few days ?

I keep running into this while building with AI: after a few sessions, I end up re-explaining the project, the decisions we made, and what changed.

How do you handle that? Do you keep a project file updated, rely on chat history, or have another system that works?

AI dev tools are evolving crazy fast , every few weeks there s a new must-try for vibe coders.

Some people are building full products with @ChatGPT by OpenAI and @Replit , others swear by @Cursor and @Claude by Anthropic , and a few are mixing @Lovable + @v0 by Vercel + @bolt.new to ship apps in record time.

I ve been refining my own vibe stack lately, trying to find that sweet spot between speed, control, and creativity.
It made me wonder ,what does your setup look like right now?

Genuine question for people shipping with Lovable, Bolt, v0 or Cursor. Building fast is the whole point, but the same few problems keep showing up on freshly shipped apps when you look at them from the outside: admin or debug routes left reachable, API endpoints that return another user's data if you change an ID in the URL, Supabase or Firebase tables readable without logging in, and API keys sitting in the frontend JavaScript. None of these need a hacker to find, just someone curious with a browser. So how do you handle it? Do you have a checklist before launch, rely on the platform's defaults, ask the AI to review its own code, or ship and fix later? And which of these has actually bitten you? Disclosure: I work on external recon at Xseth, so this is my day job, but I'd really like to hear what works for people here, with or without tools.

Coming from a non-technical background, using AI to code an app felt like magic at first. But I quickly realized that getting a feature to work on the "happy path" is only 20% of the battle handling edge cases broken internet and edge-state bugs is where things get genuinely messy.

You suddenly become the manager of a codebase you barely understand. For other non traditional builders here what was the harshed reality check you hit after launching your first AI-assisted project?