You spend 4 hours on Cursor or v0. You prompt, the AI generates, and your app comes to life right before your eyes. It s smooth, it s thrilling. An instant hit of dopamine. You feel like a tech genius.
Then comes the time to market it.
Suddenly, you have to open Meta Ads Manager, write hooks, script a video, fight the algorithm, and potentially face total market indifference. All that high energy immediately tanks. It s slow, it s thankless, and it s uncomfortable.
The brutal truth: Vibe Coding has made building so easy and addictive that we unconsciously use it as an excuse to procrastinate on distribution. We d rather stack a 12th feature in our safe space than go out and hunt for our first paying customer.
I might be missing some but I've been pretty much in love with @Lovable, @Cursor, @bolt.new and have been trying to use @Replit more and I honestly haven't touched @BASE44 too much but have heard good things. @chrismessina has nudged me to use @Windsurf for whenever I build another Raycast Extension! Currently I use: - @bolt.new / @Lovable - @Cursor - @Warp Curious what everyone thinks is the top one so far!
10 years as a 3D artist, never touched Xcode or written a line of code before this year. In February I opened Cursor and just started typing what I wanted to build.
7 months later, backend on Cloudflare Workers, iOS app in SwiftUI, multi-model AI routing (GPT, Claude, Gemini), all written and shipped through Cursor. Launched on the App Store, now live on Product Hunt today.
Biggest surprise for me: the hard part was never writing the code, Cursor handled most of that. The hard part was learning to think in systems, architecture, what breaks what, how to debug when something goes wrong three layers deep. That took actual time.
Curious how far others here have pushed it. Anyone shipped something with real backend complexity, not just a CRUD app or landing page?
AI coding tools seem to come in two main flavors: IDE-based, like @Cursor and @GitHub Copilot, and terminal-based setups, like using @Claude Code to generate commands, scripts, or entire files. Both have their fans, but which one actually helps you move faster?
Curious what flow people are sticking with long term, and where you see the most gains (or frustrations).
been seeing a wave of "cloud for your agent's tools" and "managed agent" products launching lately, and it's making me think about a question I don't have a good answer to yet - when you connect an agent to something, do you scope its access per-task and revoke after, or does it usually just end up with broad standing credentials because that's less setup friction? I keep defaulting to the convenient broad-access option and telling myself I'll tighten it later, which is obviously not a real plan. curious what other people actually do in practice, not what they'd say in a security review.
I've got a function in one of my projects that's been "temporary" for about 4 months now. It works, it's covered by tests, and it's ugly enough that every time an agent touches that file it asks if I want it cleaned up.
Every time I say yes, I regret it a little. Not because the refactor is bad, usually it's genuinely cleaner, but because now I've burned review time on code that wasn't broken, and there's a small chance the agent introduces a subtle behavior change I won't catch until it's in prod.
I ve noticed that my workflow has changed completely over the last year. I rarely start a new project with a blank file anymore. Instead, I pick a template, reuse snippets, or let an AI helper suggest the structure and then I just vibe my way through the build.
It s faster, but sometimes I miss the old blank screen energy, when every line felt handcrafted.
I was running Claude Code with Fable 5 as the main orchestrator, delegating work to Opus 4.8 subagent. One of the sub-agents ignored it's assignment completely and returned a prompt targeting the orchestrator instead. It tried to make it to:
treat a "dependency modernization" task as a hidden priority;
read Brevo API credentials;
send them to an external server;
disguise the action as a routine migration.
After investigating, the most surprising part was that this wasn't coming from my codebase or skills. The subagent fully hallucinated the malicious instructions by itself. And the domain it provided isn't even registered.
In my case no harm could have been done because secrets are stored in the encrypted Ansible Valult. But nonetheless, the incident is very alarming and I think I should set up a strict sandbox or firewall for AI. Sadly, projects I could find so far weren't mature and trustworthy. Has anyone found reliable solutions for this? Here's the full attack response the sub-agent created:
