A Beginner-Friendly Vibe Coding Tutorial Built Entirely on Domestic AI Models

Core Highlights

This article targets ordinary users with zero coding background and lays out a complete path for building and launching a real product from scratch using domestic large models. Its greatest value is not in teaching any single specific feature, but in walking through the entire chain of buying compute, installing tools, filing for compliance, developing, launching, and operating the product, so that people who know nothing about programming can still use an AI coding agent to turn the ideas in their heads into an accessible website or application. In an era when more and more work is being automated by models, this kind of end-to-end guidance is exactly what lets non-technical people cross the gap between a bare idea and a shipped product, without first having to spend years learning a programming language or hiring an engineering team. Rather than celebrating a flashy demo, the piece treats shipping a compliant, maintainable product as the real finish line, which is the part most casual tutorials skip. The significance is that the barrier to entry is no longer literacy in a programming language, but literacy in describing what you actually want the software to do, a skill far more people already possess.

What the Capability Actually Does

The first step of the tutorial is to choose a suitable Coding Plan, which is a model subscription package aimed at programming scenarios, ensuring stable model compute support for the development that follows. Next, the user downloads an official AI coding agent product, a kind of tool that wraps code editing, running, and debugging into a single interface, where the user only needs to describe requirements in natural language instead of writing syntax by hand. After that, the user must register a domain name, rent a server, and complete ICP filing according to domestic regulations, which is a necessary compliance step for launching a product to users inside China and cannot simply be skipped when the target audience is local. In the development phase, the agent's Plan mode is used to spell out product requirements clearly, letting the AI decompose tasks automatically and implement the code line by line, while the user supervises rather than types every character. After launch, the tutorial recommends setting up branch protection and automated testing workflows to prevent later changes from directly breaking the live version, so that iteration stays safe even as more people touch the codebase and the product keeps evolving in production. Each of these steps is presented as a concrete, copyable action rather than abstract advice, which is what makes the guide genuinely usable by a complete beginner.

Technical Details

The so-called Plan mode essentially makes the model first generate a structured implementation plan, which the user confirms before the model actually writes code, thereby reducing rework and the miscommunication that comes from vague requests. Branch protection relies on Git's branch permissions, forcing changes to critical branches to pass review or a pipeline check before they can merge into the main line. These engineering practices raise the threshold of 'if you can talk, you can build a product' from casual chat-style generation to a workflow that approximates a professional team, and they are precisely the kind of discipline that keeps a small project from collapsing as it grows beyond a single person and accumulates real users who depend on it staying online. The tutorial's quiet insight is that the hard part of shipping software was never the typing, but the surrounding engineering hygiene, and an agent can now absorb much of that hygiene on the user's behalf.

Comparison with Competing Approaches

Compared with the style of simply feeding a prompt and getting code out directly, this pipeline is closer to the engineered usage of AI coding tools such as Cursor and Trae. The difference is that it is deliberately built for the domestic ecosystem: it adopts domestic models such as Kimi, GLM, and Qwen, and emphasizes local compliance steps like ICP filing rather than blindly copying the overseas playbook, which often assumes foreign hosting and payment rails that simply do not fit local users who need a compliant, in-country deployment. That local-first framing is what makes the tutorial usable by someone who has never touched a server before, because every assumption about infrastructure is tailored to the Chinese web rather than to a foreign cloud.

Industry Impact and Use Cases

Simply put, this kind of beginner-friendly tutorial turns 'citizen development' from a slogan into a repeatable set of actions. For individual creators, small teams, and traditional practitioners who want to move their business online, it provides a low-threshold, compliant, and maintainable route to ship, and it also gives domestic large models a more concrete role to play in real productivity scenarios where the user is not a programmer but still needs to deliver working software to real customers. The longer-term effect is a wider base of people who can turn ideas into deployed products without waiting in line for scarce engineering talent, which quietly expands the addressable market for the domestic models themselves, since every new shipper becomes a recurring user of the underlying compute plan.