Power of Eloquence

Mastering the Art of Technical Craftsmanship

Maximizing GitHub Copilot CLI: A Senior Engineer's Guide to AI-Powered Development

| Comments

Generated AI image by Microsoft Bing Image Creator

Introduction

As software engineers, we’re constantly seeking ways to streamline our workflows and boost productivity. GitHub Copilot CLI has emerged as a powerful tool that brings AI assistance directly into your terminal, transforming how we interact with code across different stacks. This comprehensive guide will walk you through setting up an effective AI-powered development workflow with GitHub Copilot CLI, whether you’re building front-end applications, back-end services, data pipelines, or cloud infrastructure.

Note: GitHub Copilot CLI is currently in public preview and features are subject to change. Always refer to the official GitHub documentation for the most up-to-date information.

What Makes Copilot CLI Different?

Unlike traditional code assistants, Copilot CLI is terminal-native and agentic—it doesn’t just answer questions, it can act as your coding partner. You can delegate tasks, and Copilot will autonomously execute them while you maintain oversight through explicit approval mechanisms.

Latest Update (February 2026): GitHub Copilot CLI now supports advanced AI models including Claude Opus 4.6, released on February 5, 2026. Claude Opus 4.6 features enhanced agentic capabilities, agent teams (multiple agents working in parallel), a 1M token context window (in beta), and record-breaking performance on coding benchmarks including 65.4% on Terminal-Bench 2.0.

Part 1: Setting Up Your AI Development Environment

1.1 Installation and Prerequisites

Requirements:

  • Node.js 22 or later
  • A GitHub account with Copilot access (Pro, Pro+, Business, or Enterprise)
  • Your organization must enable CLI preview features (for Business/Enterprise users)

Installation:

npm install -g @github/copilot
copilot

On first launch, you’ll be prompted to authenticate:

/login

Follow the on-screen instructions to authenticate with your GitHub account.

1.2 Custom Instructions: The Foundation of Productivity

Custom instructions teach Copilot about your team’s conventions, build processes, and coding standards. According to the official documentation, all custom instruction files now combine instead of using priority-based fallbacks.

Instruction File Locations:

Location Scope Use Case
~/.copilot/copilot-instructions.md Global (all sessions) Personal preferences, common aliases
.github/copilot-instructions.md Repository-wide Team standards, build commands

Important: The exact hierarchy and all supported file locations may vary. Check the official documentation for the current list of supported custom instruction files.

Example: Full-Stack Application Instructions

Here’s a production-ready .github/copilot-instructions.md for a TypeScript full-stack project:

## Build & Development Commands
- `npm run dev` - Start development server (frontend + backend)
- `npm run build` - Production build
- `npm run test` - Run all tests with coverage
- `npm run test:watch` - Run tests in watch mode
- `npm run lint:fix` - Auto-fix linting issues
- `npm run type-check` - TypeScript type checking

## Code Style & Architecture
- Use TypeScript strict mode across all files
- Frontend: Prefer functional React components with hooks
- Backend: Use dependency injection pattern for services
- Always add JSDoc comments for public APIs
- Follow Repository Pattern for data access
- Use async/await over promises chains

## Testing Requirements
- Unit test coverage must exceed 80%
- Integration tests for all API endpoints
- Use Jest for unit tests, Playwright for E2E
- Mock external services in tests

## Git Workflow
- Branch naming: `feature/`, `bugfix/`, `hotfix/`
- Commit format: Conventional Commits (feat, fix, docs, etc.)
- Run `npm run lint:fix && npm test` before commits
- Create feature branches from `develop`

## Stack-Specific Guidelines

### Frontend (React + TypeScript)
- Use CSS Modules or styled-components
- Implement proper error boundaries
- Lazy load routes with React.lazy()
- Follow accessibility standards (WCAG 2.1)

### Backend (Node.js + Express)
- All routes must have proper error handling
- Use middleware for cross-cutting concerns
- Validate all inputs with Zod schemas
- Implement rate limiting on public endpoints

### Database (PostgreSQL)
- Use migrations for all schema changes
- Never use raw SQL in application code
- Implement proper indexing strategies
- Use transactions for multi-step operations

Stack-Specific Instruction Templates

Data Stack (Python + Spark + Airflow):

## Data Engineering Standards
- Python 3.11+ with type hints mandatory
- All DAGs must include data quality checks
- Use PySpark for distributed processing
- Schema evolution handled via Delta Lake

## Workflow
- `poetry run pytest` - Run data pipeline tests
- `poetry run black . && poetry run ruff check --fix` - Format & lint
- All transformations must be idempotent
- Implement proper data lineage tracking

Cloud Infrastructure (Terraform + AWS):

## Infrastructure as Code Standards
- Use Terraform 1.6+ with proper state locking
- All resources must have proper tags
- Implement least privilege IAM policies
- Use AWS CDK for complex constructs

## Commands
- `terraform fmt && terraform validate` - Format & validate
- `terraform plan -out=plan.tfplan` - Generate plan
- Always review plans before apply
- Use workspaces for environment separation

1.3 Tool Permissions: Security Meets Productivity

Copilot CLI requires explicit permission for potentially destructive operations. During a session, Copilot will request permission when it wants to use a tool.

Permission Options:

When Copilot wants to use a tool (like chmod, git, or npm), you’ll be prompted with:

  1. Allow - Allow this one time
  2. Yes, and approve TOOL for the rest of the session - Auto-approve this tool for the current session
  3. No, and tell Copilot what to do differently (Esc) - Reject and provide alternative guidance

Command-line Permission Flags:

# Allow all tools (use with caution)
copilot --allow-all-tools

# Allow all paths
copilot --allow-all-paths

Security Note: Using --allow-all-tools gives Copilot the same access as you have to files and commands. Only use in trusted environments.

1.4 Model Selection: Choosing the Right AI for the Job

GitHub Copilot CLI’s default model is Claude Sonnet 4.5. You can switch models using the /model command within an interactive session.

Available Models (as of February 2026):

Use /model within a CLI session to see the complete list of available models. According to GitHub’s official repository, available models include:

  • Claude Sonnet 4.5 (default)
  • Claude Sonnet 4
  • Claude Opus 4.6 (latest, added in CLI version 0.0.406 on Feb 7, 2026)
  • GPT-5

Note: The exact list of available models may vary based on your subscription and region. Use the /model command to see what’s available in your environment.

What’s New in Claude Opus 4.6:

Claude Opus 4.6, released by Anthropic on February 5, 2026, represents a significant advancement:

  • Agent Teams: Multiple AI agents can work in parallel on different components of complex tasks
  • 1M Token Context Window (in beta): Work with massive codebases—roughly 750,000 words or about 3,000 pages of code
  • Enhanced Agentic Capabilities: 65.4% on Terminal-Bench 2.0, highest score for agentic coding systems
  • Improved Code Review: Can detect and correct its own mistakes during implementation
  • 128K Output Tokens: Doubled from the previous 64K limit
  • Adaptive Thinking: Dynamically adjusts reasoning depth based on task complexity

Switching Models:

# Within CLI session
/model

# Follow the prompts to select your desired model

Strategic Considerations:

  • Use the default model (Sonnet 4.5) for most day-to-day coding tasks
  • Switch to Opus 4.6 for complex architectural decisions, difficult debugging, or agentic tasks
  • Different models may consume different amounts of your monthly premium request quota

Part 2: Mastering Plan-Driven Development

2.1 Why Planning Matters

Plan mode transforms vague requests into concrete, reviewable implementation roadmaps. It helps catch misunderstandings before any code is written.

Activation:

  • Press Shift + Tab to cycle between modes (interactive → plan → autopilot)
  • Or use /plan command in interactive mode

The Planning Workflow:

  1. You provide the goal
  2. Copilot asks clarifying questions (architecture decisions, edge cases, constraints)
  3. Copilot generates a structured plan with checkboxes and detailed steps
  4. You review and modify the plan
  5. Copilot implements the approved plan

2.2 Real-World Planning Examples

Example 1: Adding OAuth2 Authentication

Prompt:

/plan Add OAuth2 authentication with Google and GitHub providers

Copilot’s Clarifying Questions:

  • Should users be able to link multiple OAuth providers to one account?
  • Do you want to support traditional email/password alongside OAuth?
  • What’s your preference for session management - JWT or server-side sessions?
  • Any specific libraries you’re already using for auth?

Generated Plan:

# Implementation Plan: OAuth2 Authentication

## Overview
Implement social authentication using OAuth2 with Google and GitHub providers,
supporting multiple provider linking and JWT-based session management.

## Dependencies
- [ ] Install passport (^0.7.0)
- [ ] Install passport-google-oauth20 (^2.0.0)
- [ ] Install passport-github2 (^0.1.12)
- [ ] Install jsonwebtoken (^9.0.0)

## Infrastructure Changes
- [ ] Add OAuth credentials to environment variables
  - GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET
  - GITHUB_CLIENT_ID, GITHUB_CLIENT_SECRET
  - JWT_SECRET

## Database Migrations
- [ ] Create `oauth_providers` table
  - user_id (FK to users)
  - provider (enum: google, github)
  - provider_user_id
  - access_token (encrypted)
  - refresh_token (encrypted)
  - unique constraint on (user_id, provider)

## Backend Implementation
- [ ] Create `/api/auth` routes module
  - POST /auth/google (initiate Google OAuth)
  - GET /auth/google/callback
  - POST /auth/github (initiate GitHub OAuth)
  - GET /auth/github/callback
  - POST /auth/link/:provider (link additional provider)
  
- [ ] Implement Passport strategies
  - GoogleStrategy with profile data mapping
  - GitHubStrategy with profile data mapping
  - Error handling for provider failures
  
- [ ] Create authentication service
  - findOrCreateUserFromOAuth()
  - linkProviderToUser()
  - generateJWTToken()
  - Token refresh logic

## Frontend Implementation
- [ ] Create OAuth login buttons component
- [ ] Add provider linking UI in settings
- [ ] Implement OAuth redirect handling
- [ ] Add loading states during auth flow
- [ ] Error messaging for auth failures

## Security Considerations
- [ ] Implement CSRF protection for OAuth state parameter
- [ ] Encrypt stored OAuth tokens
- [ ] Add rate limiting to auth endpoints
- [ ] Implement token rotation policy

## Testing
- [ ] Unit tests for strategies and auth service
- [ ] Integration tests for OAuth flows
- [ ] E2E tests for complete login process
- [ ] Test account linking scenarios

## Documentation
- [ ] Update API documentation
- [ ] Add OAuth setup guide for developers
- [ ] Document environment variable requirements

Implementation:

Proceed with the plan. Start with database migrations.

Example 2: Refactoring for Microservices

Prompt:

/plan Refactor the monolithic user service into separate microservices for authentication, profile management, and notifications

This complex architectural change benefits from planning because Copilot will:

  • Identify all coupling points
  • Propose API contracts between services
  • Plan database separation strategy
  • Address data consistency concerns
  • Suggest deployment sequencing

2.3 When to Use Plan Mode

Scenario Use Plan Mode? Reasoning
Adding a major feature ✅ Yes Complex, multi-file, needs architecture decisions
Refactoring core business logic ✅ Yes High risk, requires careful sequencing
Fixing a typo ❌ No Simple, single-file change
Quick bug fix ❌ No Usually isolated, fast iteration better
Database schema migration ✅ Yes Needs careful planning of rollback strategy
Adding a new API endpoint ⚠️ Depends Simple CRUD? No. Complex with validation? Yes

This five-phase workflow maximizes success rates:

Phase 1: Explore

Read the authentication system but don't write code yet. 
Explain the current architecture and identify potential bottlenecks.

Phase 2: Plan

/plan Implement password reset flow with email verification and rate limiting

Phase 3: Review & Iterate
Review the generated plan. Ask for modifications:

Add a step to implement magic link authentication as an alternative to password reset

Phase 4: Implement

Proceed with the updated plan. Implement the password reset first.

Phase 5: Verify

Run all authentication tests and fix any failures. Then run the linter.

Part 3: Advanced Workflows for Different Stacks

3.1 Front-End Development (React/Vue/Angular)

Component Generation with Design Systems:

Create a reusable DataTable component following our design system
Requirements:
- Support sorting, filtering, and pagination
- Responsive design with mobile-first approach
- Accessibility compliant (WCAG 2.1 AA)
- Include loading and error states
- TypeScript with proper prop types

Visual Design Implementation:

Note: Check current documentation for image upload capabilities, as features are evolving.

State Management Integration:

Refactor the shopping cart to use Zustand for state management
Migrate from Redux while maintaining the same API for components
Add persistence to localStorage
Include tests for all state transitions

3.2 Back-End Development (Node.js/Python/Go)

API Development:

/plan Create a RESTful API for product management with the following endpoints:
- GET /api/products (list with pagination, filtering, sorting)
- GET /api/products/:id (single product)
- POST /api/products (create, admin only)
- PUT /api/products/:id (update, admin only)
- DELETE /api/products/:id (soft delete, admin only)

Requirements:
- OpenAPI/Swagger documentation
- Request validation with Zod
- Proper error handling with standard error codes
- Rate limiting (100 req/min for authenticated users)
- Include integration tests

Database Optimization:

Analyze query patterns in the products table and propose indexing strategies
Consider:
- Current query patterns in @/services/product-service.ts
- Write vs read ratio (70% reads, 30% writes)
- Don't over-index, as it impacts write performance

Microservices Communication:

Implement an event-driven communication pattern between the order service and inventory service
- Use RabbitMQ for message broker
- Implement retry logic with exponential backoff
- Add dead letter queue for failed messages
- Ensure idempotency for inventory updates
- Include monitoring and alerting

3.3 Data Engineering (Python/Spark/Airflow)

ETL Pipeline Development:

/plan Create an Airflow DAG for customer analytics ETL pipeline

Source: PostgreSQL customer database
Transformations:
- Clean and normalize customer data
- Calculate customer lifetime value
- Segment customers by behavior patterns
- Aggregate purchase history

Destination: Snowflake data warehouse

Requirements:
- Incremental loading (process only new/changed records)
- Data quality checks at each stage
- Proper error handling and alerting
- Idempotent operations
- Include unit tests for transformation logic

Data Quality Implementation:

Add comprehensive data quality checks to the customer pipeline

Checks needed:
- Schema validation (expected columns and types)
- Null value checks for required fields
- Range checks for numeric fields (age, purchase amounts)
- Format validation (email, phone numbers)
- Cross-field validation (end_date > start_date)
- Statistical anomaly detection

On failure: quarantine bad records, alert data team, continue processing good records

3.4 Cloud Infrastructure (Terraform/CloudFormation)

Infrastructure as Code:

/plan Create Terraform configuration for a production-grade EKS cluster on AWS

Requirements:
- Multi-AZ deployment for high availability
- Auto-scaling node groups (min 3, max 10 nodes)
- Separate node groups for system and application workloads
- VPC with public and private subnets
- Proper security groups and NACLs
- IAM roles following least privilege
- Enable cluster autoscaler
- Integration with AWS Load Balancer Controller
- Monitoring with CloudWatch Container Insights
- Secrets management with AWS Secrets Manager

Security Hardening:

Review our Terraform configurations for security issues:
- Overly permissive IAM policies
- Unencrypted resources
- Public exposure of sensitive services
- Missing backup configurations
- Inadequate logging and monitoring
- Missing resource tags

Generate a report with findings and proposed fixes

3.5 DevOps & CI/CD

GitHub Actions Workflow:

Create a comprehensive GitHub Actions workflow for our Node.js application

Pipeline stages:
1. Lint and format checking
2. Unit tests with coverage (fail if < 80%)
3. Integration tests against test database
4. Security scanning (npm audit, Snyk)
5. Build Docker image
6. Push to ECR
7. Deploy to staging (auto)
8. E2E tests on staging
9. Deploy to production (manual approval)

Include:
- Caching for dependencies and build artifacts
- Parallel job execution where possible
- Slack notifications for failures
- Deployment status updates to PR

Kubernetes Deployment:

Create production-ready Kubernetes manifests for our microservices

Services: api-gateway, auth-service, product-service, notification-service

Requirements:
- Use Deployments with rolling update strategy
- Configure resource requests and limits
- Health checks (liveness and readiness probes)
- Horizontal Pod Autoscaling based on CPU/memory
- ConfigMaps for configuration
- Secrets for sensitive data
- Network policies for inter-service communication
- Ingress with TLS termination
- Include monitoring with Prometheus metrics

Part 4: Session Management and Context

4.1 Understanding Session Context

Copilot CLI features automatic context compaction to enable long-running sessions. When your conversation approaches 95% of the token limit, Copilot automatically compresses your history in the background.

How it works:

  1. Older conversation history is summarized
  2. Critical information and decisions are preserved
  3. Recent context remains in full detail
  4. The process happens automatically without interrupting your workflow

4.2 Session Management Commands

View current session info:

/session

View context usage:

/context

This shows a breakdown of how your context window is being used.

Manual compaction (rarely needed):

/compact

Press Escape to cancel if you change your mind.

4.3 Best Practices for Sessions

Start fresh between unrelated tasks:

# After completing authentication feature
/new

# Start fresh for payment integration
> Implement Stripe payment integration

Clear context when switching focus:

Think of /new like ending a meeting and starting a new one - context is reset, but you can always reference previous work:

# In a new session
> Review the authentication implementation patterns we used previously and apply similar approaches for payment authorization

Part 5: Delegation Capabilities

5.1 The /delegate Command

Important: Verify the current capabilities of the /delegate command in the official documentation, as this feature may work differently than described below or may be available through different mechanisms.

Delegation allows you to offload work to Copilot coding agent. According to GitHub’s documentation, you can delegate tasks in scenarios including:

  • Codebase maintenance (security fixes, dependency upgrades, refactoring)
  • Documentation updates
  • Feature development
  • Improving test coverage
  • Prototyping new projects

Example usage:

/delegate Add comprehensive API documentation using OpenAPI 3.0 spec

5.2 When to Delegate vs. Work Locally

Delegate to Agent Work Locally
Documentation updates Core features on the critical path
Test coverage improvements Active debugging sessions
Dependency updates Interactive exploration of codebase
Non-blocking refactoring Performance optimization requiring testing

Part 6: Multi-Repository Workflows

6.1 Working Across Multiple Codebases

Copilot CLI can work with multiple repositories simultaneously.

Option 1: Start from Parent Directory

cd ~/projects/my-microservices
copilot

Copilot now has access to all child repositories:

~/projects/my-microservices/
├── api-gateway/
├── auth-service/
├── product-service/
├── notification-service/
└── shared-libraries/

Option 2: Add Directories Dynamically

Note: The exact command syntax for adding directories may vary. Refer to the official documentation for current commands.

6.2 Real-World Multi-Repo Scenarios

Scenario 1: Coordinated API Changes

I need to update our user authentication API. Changes span multiple repositories:
- api-gateway (update routing)
- auth-service (implement new logic)
- mobile-app (update client SDK)
- docs (update API documentation)

Start by showing me the current authentication flow across all repos.
Then create a plan for migrating to OAuth 2.1 with PKCE.

Scenario 2: Shared Library Refactoring

The logger module in our shared libraries is being used inconsistently.

Search all microservices for logger usage patterns.
Propose a standardized interface.
Update the logger implementation.
Then update all microservices to use the new interface.

Part 7: Productivity Patterns for Common Tasks

7.1 Codebase Onboarding

When joining a new project:

I'm new to this codebase. Help me understand:
1. Overall architecture and design patterns
2. How authentication/authorization works
3. Database schema and ORM patterns
4. Build and deployment process
5. Testing strategy and conventions

7.2 Test-Driven Development

I want to implement user registration with email verification.

First, write comprehensive failing tests covering:
- Happy path (successful registration)
- Duplicate email handling
- Invalid email format
- Weak password rejection
- Email verification flow
- Expired verification tokens

Use Jest and follow our testing patterns

After reviewing and approving the tests:

Now implement the minimum code to make all tests pass.

7.3 Code Review Assistance

Review the changes in my current branch.

Focus on:
- Potential bugs and edge cases
- Security vulnerabilities
- Performance concerns
- Code style consistency
- Missing tests
- Documentation gaps

Provide a detailed report with specific suggestions.

7.4 Bug Investigation

The /api/products endpoint returns 500 errors intermittently (about 5% of requests).

Investigation steps:
1. Search application logs for related errors
2. Check database query performance
3. Look for race conditions in concurrent requests
4. Review error handling in the products controller
5. Check for memory leaks or resource exhaustion

Analyze the evidence and identify the root cause.

7.5 Performance Optimization

Analyze the performance of our product search feature

Current metrics:
- Average response time: 850ms
- P95: 1.2s
- P99: 2.5s

Target: Average < 200ms, P95 < 400ms

Identify bottlenecks and propose optimizations:
- Database query optimization
- Caching strategies (Redis)
- Index improvements
- Pagination efficiency
- API response payload size

7.6 Security Auditing

Conduct a security audit of our authentication system:

Check for:
- SQL injection vulnerabilities
- XSS attack vectors
- CSRF protection
- Weak password policies
- Insecure session management
- Missing rate limiting
- Exposed sensitive data in logs
- Insufficient input validation

Generate a security report with severity ratings and remediation steps.

Part 8: Team Collaboration and Standards

8.1 Establishing Team Conventions

Create a team-wide .github/copilot-instructions.md:

# Team Development Standards

## When to Use Copilot CLI Features

### Plan Mode (`/plan` or Shift+Tab)
**ALWAYS use for:**
- New features touching > 3 files
- Database schema changes
- API contract modifications
- Refactoring affecting multiple modules
- Security-sensitive changes

**SKIP for:**
- Bug fixes in single file
- Documentation updates
- Code formatting
- Dependency updates

## Code Review Requirements
All code (human or AI-generated) must:
- Pass CI/CD pipeline (tests, linting, security scans)
- Be reviewed by at least one team member
- Include tests with >80% coverage
- Update relevant documentation
- Follow conventional commit format

## Model Selection Guidance
- **Default to Sonnet 4.5** for most work
- **Use Opus 4.6** for architectural decisions, complex bugs, agentic tasks
- Consider premium request quota when choosing models

8.2 Shared Repository Instructions

For a full-stack e-commerce application:

# E-Commerce Platform Development Guide

## Architecture Overview
- Frontend: Next.js 14 (App Router) + TypeScript
- Backend: NestJS + PostgreSQL + Redis
- Infrastructure: AWS ECS + RDS + ElastiCache
- CI/CD: GitHub Actions → ECR → ECS

## Key Patterns

### Frontend
- Server Components by default, Client Components only when needed
- Data fetching in Server Components, not API routes
- Use React Server Actions for mutations
- Global state: Zustand (client-side only)
- Forms: React Hook Form + Zod validation

### Backend
- CQRS pattern for complex domains (orders, inventory)
- Repository pattern for data access
- Event-driven architecture for cross-service communication
- Queue processing with Bull for async tasks

### Database
- Prisma ORM for type-safe queries
- Migrations in `prisma/migrations/`
- Never use raw SQL in application code
- Always use transactions for multi-table operations

## Testing Strategy
- Unit: Jest (>80% coverage required)
- Integration: Supertest for API tests
- E2E: Playwright for critical user journeys
- Load: k6 for performance testing

## Deployment
- Main branch → Auto-deploy to staging
- Release branches → Manual deploy to production
- Rollback procedure documented in RUNBOOK.md

Part 9: Troubleshooting and Getting Help

9.1 Common Issues and Solutions

Issue: Copilot doesn’t see recent file changes

Try the session refresh approach or restart the CLI session.

Issue: Responses seem inconsistent with project conventions

# Review your custom instructions
cat .github/copilot-instructions.md

# Ensure they're being loaded properly

Issue: Permission denied errors

Make sure you’ve granted appropriate tool permissions when prompted, or use permission flags when starting Copilot CLI.

9.2 Built-in Help System

View general help:

copilot -h

Within CLI session:

/help

This shows all available slash commands.

9.3 Getting Support

Official resources:

  1. Documentation: GitHub Copilot CLI Docs
  2. GitHub Community: Community Discussions
  3. Feedback: Use /feedback within CLI for bug reports or feature requests
  4. Support: GitHub Support for enterprise customers

Part 10: Best Practices and Recommendations

10.1 Stay Updated

GitHub Copilot CLI is in active development and evolving rapidly.

Regular checks:

# Check for CLI updates
npm update -g @github/copilot

# Check current version
copilot --version

Stay informed:

10.2 Evolving Your Custom Instructions

Your custom instructions should evolve with your team:

Quarterly review process:

  1. What patterns is Copilot frequently getting wrong? → Add explicit guidance
  2. What questions do we repeatedly ask? → Add to instructions
  3. Have our tools or practices changed? → Update commands and tech stack
  4. Are there new team members’ pain points? → Improve onboarding instructions
  5. What works well? → Document and reinforce

Version control your instructions:

# Treat .github/copilot-instructions.md like production code
git log .github/copilot-instructions.md

# Review changes in PRs
git diff main HEAD -- .github/copilot-instructions.md

10.3 Responsible AI Use

Remember:

  1. Always review AI-generated code - Copilot is a tool, not a replacement for human judgment
  2. Security first - Review generated code for security vulnerabilities
  3. Test thoroughly - All generated code should have appropriate test coverage
  4. Understand what you commit - Don’t commit code you don’t understand
  5. IP considerations - Follow your organization’s policies on AI-generated code

10.4 Building an AI-Assisted Culture

Team practices:

  1. Share wins and learnings - Regular demos of effective Copilot usage
  2. Contribute to shared instructions - Treat them like production code
  3. Measure impact - Track metrics before and after adoption
  4. Continuous learning - Allocate time for experimentation
  5. Celebrate improvements - Recognize productivity gains

Conclusion: Embracing AI-Assisted Development

GitHub Copilot CLI represents a significant evolution in developer tooling. With the recent release of advanced AI models like Claude Opus 4.6 (February 5, 2026), the capabilities continue to expand, offering features like agent teams and extended context windows.

Key takeaways:

  1. Invest in custom instructions - They’re the foundation of consistent results
  2. Use plan mode for complex tasks - Structured planning improves outcomes
  3. Choose appropriate models - Balance capability with quota management
  4. Establish team standards - Shared conventions maximize productivity
  5. Always review and validate - AI is a powerful assistant, but you remain responsible
  6. Stay current - The tool is evolving; keep up with new features
  7. Measure and iterate - Track what works and continuously improve

The developers who thrive will be those who effectively integrate these tools into their workflow while maintaining strong engineering practices.

Getting Started:

  1. Install GitHub Copilot CLI: npm install -g @github/copilot
  2. Authenticate: copilot then /login
  3. Create your first .github/copilot-instructions.md
  4. Try a simple /plan workflow
  5. Share your experience with your team
  6. Iterate and improve

Disclaimer: This guide is based on the state of GitHub Copilot CLI as of February 2026. Features, commands, and capabilities are subject to change as the tool is in public preview. Always consult the official GitHub documentation for the most current and accurate information. Finally, this guide is not only for senior engineers but can be adapted for developers at all levels to maximize their productivity with AI-assisted development.

Till next time, Happy coding! 🚀

Comments