Introduction
This week, I decided to vibe code with Cursor AI in Agent Mode — letting the machine take the wheel while I sip my coffee and occasionally raise an eyebrow.
The experience is equal parts exciting, promising, and slightly chaotic: sometimes smooth like a friend who “gets it”, occasionally forgetful like that same friend after too much coffee.
What is Cursor AI and Vibe Coding?
Cursor AI is an AI-powered code editor that behaves more like a coding partner than a static IDE. It plugs large language models into your workflow so you can generate, refactor, and debug code conversationally — without hopping between apps. You can read my post about Cursor AI.
“Vibe coding” is the name I give to this flow. You describe intent, negotiate with the AI, and let it draft, test, and revise code while you steer.
In my own test, I asked Cursor to build a Dockerised Flask web app with PostgreSQL. In ~five minutes, I had a working prototype: registration, login, and a multi-user, scalable setup. Not flawless — some debugging required — but wonderfully fast for a first draft.
Sure, spinning up a basic CRUD app — Create, Read, Update, Delete — is quick when Cursor or Grok are in the mix. But the deeper architectural design, the way services talk to each other, and whether your app is a house of cards or a sturdy building — that’s still down to you. In other words, the AI can whip up the scaffolding, but the quality of the house depends on your skills with the blueprint.
Technical Details & My Experience with Cursor AI in Agent Mode
- Auto Mode — Handy on short tasks, but in longer chats, it stalled and lost context.
- GPT-5 (in Cursor) — Friendly and generally strong for coding; occasionally stalls and gets a bit over-optimistic (code “looks right” but needs checks).
- grok-code-fast — Direct, focused, and delivers quickly; needs more debugging at the start.
You can see the model comparison (with Specs that chatGPT-5 helped me to find):
| Model | Parameters / Context Window | Strengths | Weaknesses | Personality in Use |
|---|---|---|---|---|
| Auto Mode | Orchestration mode. Inherits the selected model’s limits; reliability drops in very long chats. | Quick for small tasks; minimal setup | Can stall; loses context as threads grow | The helper who loses track |
| GPT-5 (in Cursor) | Params: Not publicly disclosed. Context: up to 400k tokens (≈272k input + 128k output) per OpenAI API docs. | Friendly, capable; good for structured coding tasks | Can be over-optimistic; occasional stalls in complex flows | The cheerful coding buddy |
| grok-code-fast-1 | Params: MoE ~314B (estimated). Context: 256k tokens (provider docs). | Precise, fast; handles large repos & agentic workflows | Needs more early debugging; sometimes mislabels identity | The no-nonsense fixer |
Notes: “Auto Mode” is Cursor’s agent mode, not a standalone model. OpenAI does not disclose GPT-5 parameter count; context limits are documented at API level. grok-code-fast-1 context window is from provider docs; parameter count is reported as an MoE estimate in secondary sources.
Conclusion
Vibe coding with Cursor feels less like traditional programming and more like pair programming with an unpredictable friend. Sometimes you laugh, sometimes you sigh, but you do get things done. The key lesson? These tools aren’t here to replace your brain — they’re here to keep it company.
And one more thing: to really benefit from Cursor or any AI coding assistant, you still need to know a bit about coding, understand the technology stack that fits your task, and have a sense of how to design systems. The AI can accelerate the ride, but you are still steering.
