I noticed that most AI tools are too polite. They tell you your code looks great even if the actual idea or logic is going to fail at scale. I built Failpoint because I wanted a "pessimistic" check. It doesn't just look for typos; it looks for flaws in the concept and the architecture. It's meant to be a brutal reality check before you spend weeks building something that won't work. Privacy: It runs in memory and doesn't store any data or code, no login is required.

The Inspiration (The "Why") Honestly? I got tired of AI sugar-coating every single time. I was working on a project late at night, and I knew deep down that my state management was a mess and my core logic had a huge hole in it. I pasted it into ChatGPT, and it just said, "Looking good! Here are a few small clean-up tips." It didn't tell me the truth: that my project was going to crash the moment I added a second user. I realized we don't need more "helpful" AI; we need an AI that acts like that one senior dev who isn't afraid to tell you your architecture is trash. I wanted a tool that would find the "Failpoints" before I wasted weeks building a house of cards. The Problem I’m Solving The biggest problem isn't syntax, it's logic gaps and bad ideas. • The "Close to the Code" Bias: When you are building, you get tunnel vision. You can't see the structural flaws because you are too focused on making the buttons click. • Sugarcoated AI: Most LLMs are tuned to be polite and encouraging. They are great for writing code, but they are terrible at auditing it for failure. • Privacy Anxiety: People want a quick check without feeling like their entire codebase is being sucked into a training database forever. **How the Approach Evolved** At first, I just wanted a simple code linter. But as I worked on it, I realized that good code can't save a bad idea. The approach shifted from "Let’s find bugs" to "Let’s find failure paths." I started focusing on the context. I realized the AI needed to understand the intent behind the project. • Version 1 was just checking for clean code. • Version 2 (Current) actually looks at your logic and your project goals to see if they match up. I also doubled down on the brutal tone. I found that when the AI is blunt and "pessimistic," it actually forces you to think harder about your architecture. It’s a reality check that helps you build something that actually lasts.

This genuinely felt useful to me, I hope for future updates like maybe adding login and captcha would be a great choice to avoid misuse of your ai I mean this can prevent people using bots to exhaust your resources. Thanks once again developer team

@alex_ferrico Thank you so much! That’s a really thoughtful suggestion. Security and resource management are definitely on my mind as we grow, adding a layer like captcha or a simple login to prevent bot abuse is a smart move to keep the AI available for everyone.

Failpoint

An AI that finds why your project or idea may fail

An AI that finds why your project or idea may fail