Browse GitHub Copilot Blogs (21)

Hidde de Smet audits a local SKILL.md “skills” library spread across Claude Code, a shared .agents catalog, and GitHub Copilot’s VS Code setup, showing how silent failures (missing files, duplicates, stale references) accumulate over time and how to stocktake them with a checklist and a couple of shell one-liners.

Rob Bos shares a curated set of GitHub governance references he regularly sends to teams, covering enterprise platform baselines, GitHub Actions supply-chain controls, GitHub Advanced Security rollout and triage practices, and GitHub Copilot governance topics like premium requests, extension governance, and MCP-related security notes.

Hidde de Smet breaks down why spec-driven development can either reduce risk or quietly add “delivery debt”, especially in regulated environments. He outlines six common process cost centers, a three-lane model (full/light/no-spec), and a small set of KPIs to tell when structure is paying off.

Randy Pagels shares three practical habits for getting more reliable results from GitHub Copilot: start with intent, ask for multiple options, and explicitly review assumptions before accepting generated code.

Hidde de Smet explains how MCP’s Enterprise-Managed Authorization changes MCP authentication from per-server OAuth consent to policy-driven sign-in via an identity provider, with VS Code 1.123 preview support for Entra ID, Okta, and Auth0 and governance controls that pair with GitHub Copilot’s MCP registry policies.

John Edward introduces the GitHub Copilot Desktop App and explains how it extends Copilot beyond the IDE into a standalone workspace for understanding repositories, planning work, and getting AI help across day-to-day development tasks.

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.

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 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.

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.