Description
Welcome back to ProgrammingKnowledge2! In today’s highly requested, full-length artificial intelligence and software engineering tutorial, we are solving the most crucial prompt engineering challenge in the 2026 ecosystem: how to properly add custom instructions and system roles in Qwen AI.
If you are a final-year B.Tech CSE student generating thousands of lines of cybersecurity scripts, or a backend engineer debugging complex cloud infrastructure, you cannot afford to manually type "Please output only Python code without markdown" every single time you open a new chat. Your AI agent needs to intrinsically understand your coding style, your formatting preferences, and your enterprise rules before you even type your first prompt. In 2026, Alibaba Cloud completely unified how custom instructions are handled across the Qwen Studio Web UI, the Qwen Code CLI, and the raw DashScope API.
In this ultimate, complete step-by-step developer guide, we are going to break down how to set up Custom Roles in the browser, how to inject global instructions using local workspace files, and how to programmatically set the system prompt for custom subagents!
Step 1: Setting Up Custom Roles in Qwen Web Studio
If you rely on the browser-based Qwen Studio, you do not use a standard "Custom Instructions" text box like older AI models. Instead, Qwen utilizes a powerful "Custom Roles" feature. We will navigate to the sidebar menu and click on Create Role. Here, you can define a permanent system instruction that dictates exactly how Qwen 3.7 Max should act. We will write a tailored blueprint that forces the AI to behave as a senior cybersecurity auditor, ensuring that every response strictly follows your predefined guidelines and eliminates all conversational fluff.
Step 2: Injecting Instructions via the QWEN dot md File
For developers using the Qwen Code CLI in the terminal, managing instructions at the project level is an absolute game-changer. We will open our IDE and create a plain text file named 'QWEN.md' right in the root directory of our project. This file acts as the ultimate custom instruction manual for your local agent. We will show you exactly what to write inside this file, including your preferred package managers, strict linting rules, and architectural constraints. Every time you launch a new terminal session, Qwen automatically reads this file first and applies your custom rules to the entire context window.
Step 3: Modifying Global Settings in Qwen Code CLI
What if you want a custom instruction to apply to every single project on your machine, not just one? We will navigate to your hidden home directory and open the global 'settings.json' file for Qwen Code. We will show you how to configure the global prompt wrappers. By editing the JSON properties, you can inject a universal custom instruction—like "Always use arrow functions in JavaScript"—that will automatically bind to every single CLI session you ever open across your entire operating system.
Step 4: Building Custom Subagents with Specific Instructions
Why stop at one custom instruction? Qwen Code allows you to build multiple specialized subagents. We will use the terminal slash command to create dedicated agents, such as a code-reviewer and an api-designer. You will learn how to assign completely different system instructions to each subagent. This means you can have one AI agent instructed to be highly creative for UI design, and another agent instructed to be incredibly rigid for backend database schemas, allowing you to switch between them seamlessly.
Step 5: Programmatic System Prompts via the API
Finally, if you are building your own AI applications using the Qwen API, we will show you how to pass custom instructions programmatically. We will open our Python editor and use the official SDK to construct a messages array. You will see how placing your custom instructions inside the 'system' role block at the very beginning of the array ensures the Qwen inference engine prioritizes your rules above all other user inputs.
Mastering custom instructions ensures your Qwen AI agents are perfectly synchronized with your personal workflow and strict enterprise standards.
If you found this incredibly detailed, full-length prompt engineering tutorial helpful, please smash that LIKE button and SUBSCRIBE to ProgrammingKnowledge2 for more in-depth software engineering guides, local AI workflows, and productivity tutorials in 2026! What is the most important custom instruction you give to your AI? Let us know your thoughts and ideas in the comments section below!
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