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Build Your First GitHub Copilot Custom Agent: A Practical LoadRunner Example

This article provides a step-by-step guide to creating custom agents in GitHub Copilot, turning a conversation into a repeatable engineering capability with a defined job and domain knowledge.

Why it matters: It empowers developers to extend Copilot's capabilities by creating specialized agents tailored to specific tasks.

InfoQ AI

Graphify: Unifying Codebase Context to Streamline Agentic Software Engineering

Graphify is an open-source tool that converts codebases into queryable knowledge graphs, enhancing multi-file reasoning for AI coding assistants.

Why it matters: It improves AI's ability to understand and navigate complex codebases, making agentic coding more efficient.

GitHub Blog

Rendering huge pull requests in the GitHub Copilot app

This article discusses the improvements made to the GitHub Copilot app to handle massive pull requests, enhancing the user experience for developers.

Why it matters: Handling large pull requests efficiently is crucial for maintaining productivity in AI-assisted coding environments.

Wired AI

Meta’s Muse AI Assistant Rolled Out With a Serious Security Flaw

Meta's Muse AI assistant had a zero-day vulnerability that allowed attackers to exploit the system, highlighting the risks associated with AI agents.

Why it matters: Security vulnerabilities in AI agents can lead to severe breaches, emphasizing the need for robust security measures.

MarkTechPost

A Coding Guide to TypeSafe AI Jev: Typed Decisions, Calibrated Confidence, and Speculative Fan-Out with a System One Model

This guide covers the implementation of TypeSafe AI's Jev model, focusing on typed decisions and calibrated confidence for structured judgments.

Why it matters: It provides developers with practical insights into implementing decision models with AI, enhancing decision-making processes.

InfoQ AI

Presentation: APIs for Agents: Rethinking API Programs in the MCP Era

This presentation explores how Morgan Stanley uses Architecture as Code with CALM to modernize its API program, integrating AI agents effectively.

Why it matters: It offers insights into modern API design for integrating AI agents, crucial for developing scalable AI-driven applications.

GitHub Blog

Developers want more efficient software. Here’s what over 1000 GitHub users told us they need.

Research from GitHub reveals a strong demand for tools and guidance to help developers reduce wasted compute and improve software efficiency.

Why it matters: Understanding developer needs can guide the development of more efficient AI coding tools and workflows.

Interconnects

Why I still haven’t bought into true RSI

This article provides a moderate view on the trajectory of frontier AI models, discussing the skepticism around true RSI (Recursive Self-Improvement).

Why it matters: It offers a balanced perspective on the potential and limitations of AI models, relevant for developers working with advanced AI systems.

Toward Data Science

How to Make Your First World Model from Scratch

A beginner-friendly guide to building a world model in Python, allowing it to simulate environments and test AI capabilities.

Why it matters: World models are essential for testing and improving AI algorithms, providing a sandbox for experimentation.

Simon Willison

Claude Opus 5.5, GPT-6 Sol, GPT-6 Luna, and a new price war

This article discusses the release of new AI models and the competitive pricing strategies emerging in the AI market.

Why it matters: Staying informed about new models and pricing can help developers choose the best tools for their projects.

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