GitHub Copilot for Seniors: Codify Architectural Standards

Name: GitHub Copilot for Seniors: Codify Architectural Standards
Rating: 4.8 (2 reviews)

Learn basics, define custom instructions, and build complex standalone prompts to make AI work like your second self

Created byVitalii Andriiovskyi

Last updated 4/2026

English

What you'll learn

Master the Copilot Ecosystem: Leverage Inline Chat, Chat View, and advanced suggestions with professional efficiency.
Codify Your Standards: Configure Custom Instructions to force the AI to adhere to your specific coding rules.
Build a Scaffolding Engine: Create reusable commands (e.g., /add-feature, /add-api-endpoint) to automate boilerplate while maintaining architectural integrity
Engineer Your Context: Use meaningful naming and type declarations to ensure Copilot provides accurate, relevant results.
Control AI Inputs: Supply the right files, documentation, and logic examples to build comprehensive, high-quality prompts.
Achieve Architectural Alignment: Train the AI to mirror your style, making it a reliable "second self" for your projects.

Course content

5 sections • 14 lectures • 2h 40m total length

Introduction4:09
Setup12:42
This is the setup lesson. You will configure the necessary software and tools needed to complete this course. You will also set up pawsitive-play, the project I use to showcase AI in action: writing and executing prompts, using standalone prompts like /add-form, /add-feature, /add-feature-back-end .

Code Completions8:45
Copilot attempts to predict your intent to complete your code, and you can influence its behavior. By the end of this lesson, you will be able to enable or disable Code Completions, and use various techniques to help Copilot understand your intent, resulting in more relevant suggestions.
Inline Chat12:33
You will learn how to initiate and use Inline Chat. While the basic operation is straightforward, the true value lies in configuring prompts. You will practice instructing Copilot to use logic from any workspace file as a code example, or to integrate it into a new implementation. Furthermore, you will be able to reference guidelines from external web pages in your prompts for new code, or simply run quick commands in Inline Chat, such as /add-types.
Chat View14:12
The Chat View is your dedicated IDE panel for requesting Copilot's assistance. Here, you can ask for advice, run prompts to edit multiple files, or engage the agent to plan and implement entire features based on specific requirements. You will master these capabilities easily by the end of the lesson.

P. S. The branch with the code prepared for the lesson is lesson-copilot-chat-view

Custom Instructions19:02
When writing many prompts in Inline Chat or Chat View, you'll quickly notice that you constantly reuse certain requirements or guidelines. Copying and pasting this information is annoying. You can solve this problem using custom instructions.
By the end of the lesson, you will be able to create custom instructions and configure them to apply only in specific scenarios, such as for JavaScript or CSS files.

P. S. The branch with the code prepared for the lesson is lesson-custom-instructions
Developer's Coding Style18:44
You likely have your own coding style and wish the AI to generate code that reflects it. This lesson shows how to make Copilot follow your coding style, rules, and approach when writing logic.

P. S. The branch with the code prepared for this lesson is lesson-coding-style

Standalone Prompts10:28
Repetitive tasks often require you to use the same prompts many times. Writing them out or copying and pasting them is a time-consuming process. Fortunately, Copilot offers a feature called standalone prompts.
At the end of this lesson, you will be creating and configuring standalone prompts with ease, and running them in Inline Chat or Chat View as a custom command like /add-types.

P. S. The branch with the code prepared for this lesson is lesson-standalone-prompts
/add-form15:33
This lesson focuses on the standalone prompt, /add-form, which you execute using the command of the same name. This prompt is configured to create forms that follow the same implementation approach but collect different data.
You will simply call the /add-form command and provide the data structure. Furthermore, you will be able to use this prompt as a template to create your own customized standalone prompt for building forms that adhere to your specific coding style.

P. S. The branch with the code prepared for this lesson is lesson-add-form
/add-feature-back-end10:41
The standalone prompt /add-feature-back-end instructs Copilot to scaffold a feature split across multiple files. Each time the prompt is called, it creates the feature using the same approach but adjusts the logic to the data structure and details provided within the prompt call.
By the end of the lesson, you will understand the concept of a backend feature, and you will be able to use this prompt—or create a new one—to quickly build backend features.

P. S. The branch with the code prepared for this lesson is lesson-add-feature-back-end
/add-api-endpoint14:35
The branch with the code prepared for this lesson is lesson-add-api-endpoint
/add-feature16:01
The standalone prompt /add-feature instructs Copilot to create a feature for the frontend. Specifically, it will create multiple files for a feature, insert basic logic into them, and adjust the logic to the data structure and details provided within the prompt call.
You will be able to use this prompt in your projects or use it as a template to create your own customized standalone prompt.

P. S. The branch with the code prepared for this lesson is lesson-add-feature
Custom Prompts for Full-Stack Nx Monorepo (Angular 21 · NestJS 11 · PostgreSQL)1:34

Requirements

Complete beginners for GitHub Copilot
You should know JavaScript, TypeScript, next.js and React
Developers with experience and their own style of code writing.
Junior developers might face difficulties here. While the theory and use cases may be easy to understand, the resulting code itself could be complex to grasp. Although the code shown in the course could be a good starting point for learning project architecture, be aware that the feature-based architecture used here is quite complicated.

Description

Welcome to "GitHub Copilot for Seniors: Codify Architectural Standards"! This course is a practical guide to evolving GitHub Copilot from a basic coding assistant into a high-level engineering partner—a true "second self" for your development workflow.

Course Methodology: From Basics to Architectural Scaffolding

The curriculum is structured to guide the transition from basic AI interaction to full-stack automated engineering:

Phase 1: Foundations of AI-Assisted Engineering

The course starts with the essentials, but it skips the fluff. It focuses on context injection—the technique of curating the specific data, files, and documentation that Copilot requires to generate accurate, production-ready code. Lessons cover how to treat Copilot as a functional extension of the IDE rather than a basic chatbot.

Phase 2: Defining Coding Standards

True mastery is achieved when the AI generates code according to rigid project requirements. The course teaches the use of Custom Instructions to codify architectural preferences—from Clean Architecture patterns to specific CSS methodologies—ensuring every generated snippet adheres to professional standards.

Phase 3: The Scaffolding Engine (Standalone Prompts)

This represents the core of the curriculum. It moves beyond simple chat queries to implement a reusable library of high-level commands. Through the use of custom standalone prompts—such as /add-form, /add-feature, /add-feature-backend, and /add-api-endpoint—the following capabilities are mastered:

Feature Scaffolding: Generate entire features across front-end and back-end environments simultaneously.
Type-Safe Logic: Create code perfectly adapted to specific, complex data models.
Boilerplate Automation: Eliminate repetitive tasks while maintaining strict architectural integrity.

Phase 4: Scaling the Workflow

By the conclusion of the course, the transition from simple "prompting" to managing a standardized AI workflow is complete. The material provides a production-ready toolkit that transforms architectural blueprints into functional features, allowing the focus to remain on system design rather than routine implementation.

Why Enroll?

This course is designed to inspire a shift in perspective. You will move from manually typing out boilerplate to engineering the systems that generate it. By the end of this journey, you will be equipped to identify the repetitive bottlenecks in your own practice and write custom, standalone prompts to automate them indefinitely.

Join the course today and transform your development workflow into an automated, architecture-driven engine.

Who this course is for:

This course is for developers seeking all possible ways to use AI as effectively as possible, particularly to automate many routine tasks. My goal was to make AI work like my second self. That is, the AI creates a backend feature, implements an API endpoint, generates a frontend feature, and builds a form precisely in the way I like. To achieve this, I identified the most common tasks and wrote dedicated standalone prompts for them.

GitHub Copilot for Seniors: Codify Architectural Standards

What you'll learn

Explore related topics

Course content

Introduction2 lectures • 17min

GitHub Copilot Basics3 lectures • 36min

Code Generation with a Personal Coding Style2 lectures • 38min

Standalone Prompts6 lectures • 1hr 9min

Thanks Note1 lecture • 1min

Requirements

Description

Who this course is for: