This article explores how a team built an AI-powered emoji list generator during a Rubber Duck Thursday live stream. The tool runs in the terminal, takes a list of bullet points, and uses AI to intelligently replace them with relevant emojis before copying the result to the clipboard.
Key highlights include:
- Use of GitHub Copilot CLI for rapid development via plan and autopilot modes.
- Integration of @opentui/core for the terminal user interface.
- Leveraging the GitHub Copilot SDK to provide intelligent emoji selection.
- Implementation of a multi-model workflow using different LLMs for planning and execution.
Key highlights include:
- Use of GitHub Copilot CLI for rapid development via plan and autopilot modes.
- Integration of @opentui/core for the terminal user interface.
- Leveraging the GitHub Copilot SDK to provide intelligent emoji selection.
- Implementation of a multi-model workflow using different LLMs for planning and execution.
This article details the updates to agent-shell version 0.47.1, a native Emacs mode for interacting with LLM agents powered by ACP. Key improvements include renaming 'claude-code-acp' to 'claude-agent-acp', support for new agents like Auggie, Cline, and GitHub Copilot, and experimental bootstrapped and resumable sessions. Enhancements have also been made to clipboard image handling, status display, image rendering, and table rendering. The update also introduces usage tracking, improved diffs, event subscriptions, and customizable context sources. The author encourages sponsorship to ensure the project's sustainability.
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 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.
