Let’s be real for a second. Prompting Claude, Cursor, or ChatGPT feels amazing... until it doesn’t.

You know the cycle:

1. You type a vague prompt like "Make me a auth system."
2. The AI spits out 200 lines of beautiful-looking TypeScript.
3. You get that dopamine hit. "I am a 10x engineer!"
4. You run it.
5. ERROR: undefined is not a function.
6. You spend the next 4 hours debugging code you didn’t write and barely understand.

That’s not engineering. That’s a slot machine with syntax highlighting.

The Problem: AI (and most of us frequently) Has No "Chill"

Vibe coding is chaotic because LLMs are people-pleasers. They want to give you code now, regardless of whether it actually makes sense architecturally. They lack a Thinking Framework. They don’t check invariants.

They just... vibe.

What if you could force the AI to actually think before it types?

Enter Quint 🛠️

Quint is a tiny, no-nonsense toolkit for AI-assisted engineering.

It’s not a new IDE. It’s not a bloated SaaS wrapper. It’s a set of CLI commands (currently) that act as a "Thinking OS" for your AI tool collaboration – making both of you more rigorous.

Whether you use Claude Code, Cursor, Gemini CLI, or Codex, Quint sits in the middle and says: "Hey AI, before you write that function, prove to me it won’t break the build."

Why You Should Care (Right Now)

The current version is commands set only. No UI. No dependencies to break anything. Tiny, almost zero overhead in the context for your Claude Code or Cursor.

But We’ve been using it in real scenarious of tackling highly complex engineering and even marketing tasks, and you know what... the difference in the results quality is wild.

Instead of getting "plausible spaghetti," we get decision records that actually respect the goals and are linked with evidence.

It just make sense.

What’s Under The Hood? 🧠

The current latest version of Quint Code implements about 10% of the First Principles Framework (FPF) – an original, brilliant but formal, and very complex specification of the "thinking OS" created by Anatoly Levenchuk.

Now, I know what you’re thinking: "Only 10%? Why release it?"

Because that 10% is the Pareto Principle in action. It turns out you don’t need a PhD in Formal Logic to improve AI and AI + Human collaborative reasoning.

You just need to force the AI to acknowledge few Invariants and Reasoning Chains. And then act as External Transformer, like an Oracle or... Overseer.

Even this minimal implementation forces AI agents to plan the decisions and thus the follow-up work much better than any heuristic planners and to-dos.

🔮 The Near Future: v4.0.0 & The MCP Hype Train

We are close to dropping v4.0.0, and it’s going to be a banger.

We’re introducing a tiny MCP (Model Context Protocol) Server which will handle FPF kernel and Invariants better in local sqlite database + same MD files.

It will allow Quint to feed the AI persistent context about your project’s "Laws of Physics," as well as your rules and past decisions mostly automatically.

We’re aiming for ~75% FPF Invariants support with this MCP. Still small. Still focused. But dramatically smarter.

🧪 Try It. Break It. Roast It.

I don’t want "polite" feedback. I want feedback from devs who are actually in the trenches using Cursor/Claude Code daily. Who have zero ideas about this scientific stuff and all the systems engineering formalities and methods that I do love, but the devs, as I said - in the trenches. And I need the feedback from the trenches.

• Does it fit your flow?
• Is the README too confusing?
• Did it save you from a hallucination?
• Did it help you to plan complex tasks better?

🔗 Link to Quint Code Repo: https://github.com/m0n0x41d/quint-code

Go ahead. Try it out. If it sucks, tell me why. If it fixes your vibe coding hangover, tell your friends.

Quint is a small tool, but it has a damn big brain energy.

---

Thanks for reading, ivan zakutni