A workflow for rapidly building applications with GitHub Copilot CLI, emphasizing its role in generating *momentum* and quickly reaching a reviewable pull request. Leverage Copilot CLI for speed, your IDE for refinement, and GitHub for collaboration.
* **Define & Scaffold:** Start with a natural language description of your goal and use Copilot CLI to scaffold only the parts you're ready to actively work on.
* **Iterate & Refine:** Run tests and use Copilot CLI to help understand and fix failures; handle mechanical, repo-wide changes with the CLI.
* **Develop & Ship:** Transition to your IDE for complex logic/design, then commit your changes and create a pull request on GitHub for collaboration.
* The Copilot SDK offers possibilities for embedding agentic execution directly within applications.
* **Define & Scaffold:** Start with a natural language description of your goal and use Copilot CLI to scaffold only the parts you're ready to actively work on.
* **Iterate & Refine:** Run tests and use Copilot CLI to help understand and fix failures; handle mechanical, repo-wide changes with the CLI.
* **Develop & Ship:** Transition to your IDE for complex logic/design, then commit your changes and create a pull request on GitHub for collaboration.
* The Copilot SDK offers possibilities for embedding agentic execution directly within applications.
This guide offers five essential tips for writing effective GitHub Copilot custom instructions, covering project overview, tech stack, coding guidelines, structure, and resources, to help developers get better code suggestions.
This article details how to use Playwright MCP and GitHub Copilot to reproduce and debug web app issues. It covers setup, a sample scenario, and the benefits of this debugging approach.
This week's security roundup covers the Anubis web AI firewall, AI exploit generation, a vulnerability in CodeRabbit, the potential illegality of adblocking in Germany, a Microsoft Copilot audit log issue, and a disputed Elastic EDR vulnerability.
This article explores how AI agents are reshaping software development and the impact they have on a developer’s workflow. It introduces a practical approach to staying in control while working with these tools by adopting key best practices from the discipline of software architecture, including defining an implementation plan, splitting tasks, and so on.
Guidance on choosing the best AI model for GitHub Copilot projects, considering speed, depth, cost, and task complexity. Models discussed include GPT-4.1, GPT-4o, Claude 3.5 Sonnet, o4-mini, o3, Gemini 2.0 Flash, and GPT-4.5.
This article explores a framework for evaluating AI models for use with GitHub Copilot, considering factors like recentness, speed, accuracy, and how to test them within your workflow. It highlights the benefits of using different models for chat versus code completion, and reasoning models for complex tasks.
A repository containing extracted system prompts and tools for various AI models including FULL v0, Cursor, Manus, Same.dev, Lovable, Devin, Replit Agent, Windsurf Agent, and VSCode Agent. It offers insights into the structure and functionality of these models and includes a security notice for AI startups.
GitHub Copilot now features instant semantic code search indexing, dramatically reducing the time it takes for Copilot to understand and reference your codebase, making development workflows more efficient.
This blog post introduces the Semantic Telemetry project at Microsoft Research, which uses a data science approach to analyze how people interact with AI systems, specifically focusing on Copilot in Bing usage. It discusses the complexity of human-AI interactions and how they differ from traditional search.
- Topics: Copilot in Bing chats were analyzed for topic categorization. Technology (21%) was the most common topic, followed by Entertainment (12.8%), Health (11%), and others. Within technology, programming and scripting were prominent subtopics.
- Platform Differences: Mobile users tend to use Copilot for personal tasks, while desktop users engage in more professional activities.
- Topics: Copilot in Bing chats were analyzed for topic categorization. Technology (21%) was the most common topic, followed by Entertainment (12.8%), Health (11%), and others. Within technology, programming and scripting were prominent subtopics.
- Platform Differences: Mobile users tend to use Copilot for personal tasks, while desktop users engage in more professional activities.
