From Code Writer to AI Conductor: How Vibe Coding Lets a Manager Build a Full Product with Just Words

Da Liu , a manager with a technical background, describes how he recently launched a complete product—covering content creation, AI customer service, ordering, shop and product management, and even real‑time token‑usage monitoring—almost entirely by speaking to an AI system, without writing code himself.

This illustrates a fundamental change: previously building a system required deep knowledge of code, modules, and performance; now the only KPI is whether the output satisfies the product requirements and runs the business logic, regardless of the underlying stack.

Da Liu was an early adopter of the AI wave. He first mastered prompt engineering for AI image generation, then progressed through tools such as Stitch, AI Studio, and Qoder, using them to handle both front‑end and back‑end tasks. He freely swapped models—using Minimax while it was free, switching to paid versions, and trying Qoder’s expert‑team service—deleting and restarting when results were unsatisfactory.

When WorkBuddy appeared, he immediately switched, attracted by its point system. Later he experimented with QClaw, a WeChat‑focused fork of OpenClaw, which he found more adept at handling low‑level tasks like computer control and environment setup, allowing rapid deployment of GitHub applications and configuration of a “digital employee” platform on a Mini device.

He even tasked an AI to scrape the most valuable logic from open‑source code to train his own digital employees, treating the AI as a powerful assistant—or even a technical co‑founder—that can materialize ideas when given clear directions.

Da Liu stresses that business logic must be defined first, because AI does not understand how a product makes money; it merely executes the path you set, and without clear goals it can only follow along aimlessly.

Based on this reasoning, he built an “AI Factory”: a conceptual factory that organizes AI modules into a production line. It includes a “content workshop” for mass‑producing copy, a “tool workshop” that stores various skill versions, and monitoring dashboards, all coordinated to deliver cohesive functionality.

He further split a single main account into a matrix of specialized accounts (e.g., Account A for travel content, Accounts B and C for store and product showcases) that act as digital employees, each focusing on a specific vertical and feeding into a central account that handles conversion.

The overall picture is that he continuously harvests the latest free AI tools, injects them into real business flows, and automates step‑by‑step tasks that previously required a full team, eventually letting his AI agents work night shifts for him.

He concludes with a wry remark, “So many low‑quality supplies,” noting that while the AI‑generated output may seem frivolous, it now actually runs his night‑shift operations.