Browse GitHub Copilot Blogs (29)

Hidde de Smet compares the GitHub Copilot App and the VS Code Agents Window, focusing on how each surface supports agent-first workflows: isolated sessions, worktrees, review/CI loops, and customization via MCP and instruction files. It includes a practical “which one should you use?” decision guide for day-to-day development vs delegated work.

Jesse Houwing shows how to automate GitHub Copilot AI Credits budgeting by assigning per-user budgets based on Microsoft Entra ID group membership, using a GitHub Actions workflow and a PowerShell script that calls the GitHub enterprise billing API via the GitHub CLI.

Hidde de Smet lays out a practical KPI scorecard for teams adopting AI coding agents under usage-based billing, using GitHub Copilot’s AI Credits model as the concrete example. It focuses on measuring speed, quality, reliability, and spend together, with a rollout plan and data sources you can wire into a weekly dashboard.

Randy Pagels explains how to reduce repeated prompting by capturing team conventions in a copilot-instructions.md file so GitHub Copilot can generate code that matches your repo’s standards, architecture expectations, and preferred testing and design patterns.

Harald Binkle demonstrates a practical BMAD workflow using GitHub Copilot to turn fuzzy requirements into reviewable artifacts: a PRD, project context, epics/stories, architecture decisions, risk-based test design, and traceability. The example focuses on enterprise authentication concerns like MFA, tenant isolation, RBAC, and auditability.

Rob Bos argues that as GitHub Copilot shifts to usage-based billing, teams should stop fixating on token costs in isolation and instead measure what they get back: foundation work, reduced tech debt, and faster MVP delivery. He shares real usage patterns, cost concentration among heavy users, and practical steps to manage spend without throttling engineers.

Hidde de Smet breaks down what AI coding agents actually cost once GitHub Copilot switches to usage-based billing, including how credits map to tokens, why model choice changes your bill, and how to budget for agent-heavy teams without surprising finance.

Rob Bos introduces the GitHub Copilot App technical preview and shares a practical first look at using it for repository maintenance, including parallel agent sessions, session modes (Interactive/Plan/Autopilot), and the Agent Merge workflow for handling CI failures, merge conflicts, and security-related alerts.

John Edward explains how GitHub Copilot changes team workflows around pull requests, code review expectations, and knowledge sharing. The article focuses on the trade-offs of faster AI-assisted coding, why review discipline matters more, and how teams can add guardrails like testing and security scanning without losing collaboration.

Jesse Houwing breaks down why GitHub Copilot is moving from Premium Request Units to token-based, usage-based billing, and what that means for model selection, cost predictability, and newer features like Agent Mode, Cloud Coding Agent, and Copilot Code Review—especially for organizations managing budgets and policies.

Rob Bos shares a real-world GitHub Copilot CLI mishap where an unintended Copilot CLI extension caused repeated prompts to close GitHub deployment-status notifications, and explains how he tracked down the source and removed it.

Rob Bos shares an overview of his open source projects spanning GitHub and CI/CD tooling, Azure-backed services, security reporting, and local-first AI utilities, with links to each repo and a clear description of what each tool does.

Hidde de Smet shows how to combine five GitHub Copilot customization file types in a single .NET Aspire repo, so the right instructions, skills, prompts, and agent roles load at the right time without bloating every chat request.

John Edward discusses how GitHub Copilot changes programming education, where it can speed up learning, and where it can undermine fundamentals if students rely on it too heavily. The post outlines practical habits for students and classroom approaches for educators to use Copilot without losing academic rigor.

Rob Bos breaks down five GitHub Copilot and agent extensibility surfaces that create supply-chain and governance gaps in large enterprises, and explains what controls exist today (and where they don’t) across Copilot CLI plugins, APM, gh skill, MCP servers, and VS Code extension registries.

Hidde de Smet's Blog breaks down the difference between AGENTS.md (repo-wide, always-on instructions for coding agents) and .agent.md (custom agent profiles for GitHub Copilot), including where to place each file, what fields matter, and how to use roles, tool restrictions, and handoffs safely.

Hidde de Smet's Blog explains how GitHub Copilot “skills” work via SKILL.md folders, why the YAML description is the key to discovery, and how this approach keeps context lightweight compared to a giant copilot-instructions.md. It includes a practical Azure Monitor/Application Insights KQL skill you can copy into a repo.

DevClass.com reports on Visual Studio 18.5 (Visual Studio 2026), covering new Copilot-driven “agentic” debugging, changes to how IntelliSense/Copilot suggestions are prioritized, and ongoing developer complaints about theme contrast and forced auto-updates.

Hidde de Smet compares three AI coding setups—single-agent, agent-with-tools, and multi-agent—using a realistic .NET Aspire + ASP.NET Core rate-limiting task to show trade-offs in fit, cost, latency, and common failure modes.

Jesse Houwing summarizes GitHub’s update that GitHub Copilot can now keep inference processing and associated data within US or EU data residency regions, and shows the enterprise/org policy you must enable to restrict Copilot to data-resident models.

Rob Bos walks through running GitHub Copilot CLI against local OpenAI-compatible inference servers (Ollama, LM Studio, Foundry Local, vLLM/TGI), focusing on the practical constraints (32k context, tool calling, VRAM/KV-cache) and sharing concrete Windows/PowerShell setup and throughput numbers.

Emanuele Bartolesi shows how to point GitHub Copilot CLI at an Azure AI Foundry (Azure OpenAI) deployment using a BYOK-style setup, including how to deploy a model, build the correct endpoint URL, set the required environment variables, and validate the connection.

Emanuele Bartolesi explains how to run GitHub Copilot CLI against a local LLM via LM Studio’s OpenAI-compatible API, including the exact PowerShell environment variables needed to avoid cloud fallback and when this offline setup is (and isn’t) worth using.

Hidde de Smet explains how Spec-Kit’s extension system works, highlights useful community extensions, and walks through the Ralph Loop extension, which runs a GitHub Copilot agent in iterations to implement tasks from `tasks.md`, commit changes, and track context in `progress.md`.

Harald Binkle explains the latest Visuals MCP update, adding a chart tool that lets AI agents render single charts and full dashboards directly inside GitHub Copilot Chat in VS Code, with Storybook examples and export options for turning analysis into shareable visuals.

Randy Pagels explains a simple GitHub Copilot workflow: before asking for an implementation, prompt Copilot to ask clarifying questions so you uncover assumptions, edge cases, and missing requirements early—leading to better prompts and better code changes.

Jesse Houwing clarifies GitHub Copilot’s April 24 interaction-data policy change, explaining which subscription tiers may have interactions used for training, what is and isn’t included (like private repos), and practical ways enterprises can enforce license tiers and lock down developer environments.

Emanuele Bartolesi explains how to make GitHub Copilot less “agreeable” and more useful by adding a repo-level voice instructions file that pushes Copilot to be direct, critical, and focused on correctness and maintainability.

Jesse Houwing explains why he rebuilt the Azure DevOps Marketplace publishing tasks from v5 to v6, focusing on faster builds, stronger testing, GitHub Actions support, and more secure authentication (OIDC/workload identity) while using GitHub Copilot’s Coding Agent to accelerate the rewrite.