Dark GitHub Style 🌙
Your eyes will ♥️ you.
[ GitHub ] : kutt.it/git-dark
〰️〰️〰️〰️〰️〰️
#GitHub #Theme
@ProgrammingTip
Your eyes will ♥️ you.
[ GitHub ] : kutt.it/git-dark
〰️〰️〰️〰️〰️〰️
#GitHub #Theme
@ProgrammingTip
GitHub Copilot X: The AI-powered developer experience 🏳️
GitHub Copilot is evolving to bring chat and voice interfaces, support pull requests, answer questions on docs, and adopt OpenAI’s GPT-4 for a more personalized developer experience.🆒
[ Article ] : https://kutt.it/CopilotX
〰️〰️〰️〰️〰️〰️
#GitHub #AI #ChatGPT
@ProgrammingTip
GitHub Copilot is evolving to bring chat and voice interfaces, support pull requests, answer questions on docs, and adopt OpenAI’s GPT-4 for a more personalized developer experience.
[ Article ] : https://kutt.it/CopilotX
〰️〰️〰️〰️〰️〰️
#GitHub #AI #ChatGPT
@ProgrammingTip
Please open Telegram to view this post
VIEW IN TELEGRAM
YouTube
GitHub Copilot X
Introducing our vision for the future of AI-powered software development with GitHub Copilot. To learn more visit https://gh.io/copilotx
Stay up-to-date on all things GitHub by subscribing and following us at:
YouTube: http://bit.ly/subgithub
Blog: https://github.blog…
Stay up-to-date on all things GitHub by subscribing and following us at:
YouTube: http://bit.ly/subgithub
Blog: https://github.blog…
GitHub MCP Registry: The fastest way to discover MCP Servers 🔝
If you’ve tried connecting AI agents to your development tools, you know the pain: MCP servers scattered across numerous registries, random repos, buried in community threads — making discovery slow and full of friction without a central place to go. Meanwhile, MCP server creators are worn out from publishing to multiple places and answering the same setup questions again and again.
The GitHub MCP Registry launches as your new home base for discovering MCP servers. Whether you’re building with GitHub Copilot, agents, or any AI tool that speaks MCP, this is the place to find what you need. With GitHub already home to most MCP servers, the MCP Registry makes them dramatically easier to discover, explore, and use — helping developers find the right tools faster and contribute to a more open, interoperable ecosystem.✔️
[ GitHub MCP Registry ] : https://github.com/mcp
〰️〰️〰️〰️〰️〰️
#LLM #AI #MCP #GitHub
@ProgrammingTip
If you’ve tried connecting AI agents to your development tools, you know the pain: MCP servers scattered across numerous registries, random repos, buried in community threads — making discovery slow and full of friction without a central place to go. Meanwhile, MCP server creators are worn out from publishing to multiple places and answering the same setup questions again and again.
The GitHub MCP Registry launches as your new home base for discovering MCP servers. Whether you’re building with GitHub Copilot, agents, or any AI tool that speaks MCP, this is the place to find what you need. With GitHub already home to most MCP servers, the MCP Registry makes them dramatically easier to discover, explore, and use — helping developers find the right tools faster and contribute to a more open, interoperable ecosystem.
[ GitHub MCP Registry ] : https://github.com/mcp
〰️〰️〰️〰️〰️〰️
#LLM #AI #MCP #GitHub
@ProgrammingTip
Please open Telegram to view this post
VIEW IN TELEGRAM
GitHub moved the Copilot runtime to Rust 🚀
GitHub migrated the runtime behind Copilot to Rust, and used Copilot during the migration itself.
✅ Why this is worth reading:
• Runtime work is systems work: a language migration means tracing real production behavior, not just translating syntax.
• Copilot was part of the workflow: useful for exploring an unfamiliar codebase, drafting changes, and keeping momentum through repetitive conversion work.
• The output still needs engineering judgment: boundaries, performance, correctness, and rollout safety are not autocomplete problems.
This is a practical case study for teams asking where coding agents help on a large refactor. Use them to accelerate investigation and implementation. Keep humans on architecture, tests, and production checks.
[ Blog ] :
https://github.blog/ai-and-ml/generative-ai/migrating-the-github-copilot-runtime-to-rust-using-copilot
〰️〰️〰️〰️〰️〰️
#AI #GitHub #Rust #Copilot
@ProgrammingTip
GitHub migrated the runtime behind Copilot to Rust, and used Copilot during the migration itself.
• Runtime work is systems work: a language migration means tracing real production behavior, not just translating syntax.
• Copilot was part of the workflow: useful for exploring an unfamiliar codebase, drafting changes, and keeping momentum through repetitive conversion work.
• The output still needs engineering judgment: boundaries, performance, correctness, and rollout safety are not autocomplete problems.
This is a practical case study for teams asking where coding agents help on a large refactor. Use them to accelerate investigation and implementation. Keep humans on architecture, tests, and production checks.
[ Blog ] :
https://github.blog/ai-and-ml/generative-ai/migrating-the-github-copilot-runtime-to-rust-using-copilot
〰️〰️〰️〰️〰️〰️
#AI #GitHub #Rust #Copilot
@ProgrammingTip
Please open Telegram to view this post
VIEW IN TELEGRAM
The GitHub Blog
Migrating the GitHub Copilot runtime to Rust, using Copilot
A rewrite this size wasn't affordable before agents. Here's what porting the Copilot agent runtime to 800,000 lines of production Rust actually took.
GitHub improved the Copilot code review flow 🔥
GitHub shipped an improved Copilot code review experience. That matters most on the boring, high-volume PRs where reviewers need help finding a real issue, not another summary of changed files.
For C# teams, use Copilot review as an extra pass on every ASP.NET, EF Core, and library PR. Then keep the human review focused on contracts, failure behavior, and whether the change belongs in the codebase.
Practical rule:
• Let Copilot flag suspicious diffs.
• Do not merge because it found nothing.
• Keep analyzers and tests as the enforcement layer.
AI review is cheap coverage. It is not a replacement for someone who knows why that nullable property or cancellation token exists.
[ Read More ] :
https://github.blog/changelog/2026-09-18-copilot-code-review-an-improved-review-experience
〰〰〰〰〰〰
#dotnet #csharp #GitHub #Copilot
@ProgrammingTip
GitHub shipped an improved Copilot code review experience. That matters most on the boring, high-volume PRs where reviewers need help finding a real issue, not another summary of changed files.
For C# teams, use Copilot review as an extra pass on every ASP.NET, EF Core, and library PR. Then keep the human review focused on contracts, failure behavior, and whether the change belongs in the codebase.
Practical rule:
• Let Copilot flag suspicious diffs.
• Do not merge because it found nothing.
• Keep analyzers and tests as the enforcement layer.
AI review is cheap coverage. It is not a replacement for someone who knows why that nullable property or cancellation token exists.
[ Read More ] :
https://github.blog/changelog/2026-09-18-copilot-code-review-an-improved-review-experience
〰〰〰〰〰〰
#dotnet #csharp #GitHub #Copilot
@ProgrammingTip
The GitHub Blog
Copilot code review: An improved review experience - GitHub Changelog
Copilot code review now gives you a clearer view of how a review changes over time, more intelligently auto-resolves its own suggestions, and generates useful commit messages when you accept…
AI is changing the developer career ladder 🚀
GitHub's latest developer career advice is refreshingly practical: AI can write more of the first draft, but it cannot own the engineering outcome for you.
The skills to double down on:
• Systems thinking: understand the service, data flow, failure modes, and tradeoffs around the code.
• Judgment: spot the plausible-looking AI patch that breaks security, cost, or production behavior.
• Communication: turn a vague product request into constraints an agent, teammate, and reviewer can act on.
Using Copilot or an agent is becoming normal. Being the person who can frame the task, verify the output, and ship it safely is still the hard part.
[ Article ] :
https://github.blog/ai-and-ml/ai-is-rewriting-the-developer-career-ladder-heres-how-to-stand-out/
〰〰〰〰〰〰
#AI #GitHub #Copilot #Career
@ProgrammingTip
GitHub's latest developer career advice is refreshingly practical: AI can write more of the first draft, but it cannot own the engineering outcome for you.
The skills to double down on:
• Systems thinking: understand the service, data flow, failure modes, and tradeoffs around the code.
• Judgment: spot the plausible-looking AI patch that breaks security, cost, or production behavior.
• Communication: turn a vague product request into constraints an agent, teammate, and reviewer can act on.
Using Copilot or an agent is becoming normal. Being the person who can frame the task, verify the output, and ship it safely is still the hard part.
[ Article ] :
https://github.blog/ai-and-ml/ai-is-rewriting-the-developer-career-ladder-heres-how-to-stand-out/
〰〰〰〰〰〰
#AI #GitHub #Copilot #Career
@ProgrammingTip
The GitHub Blog
AI is changing developer work. Here are three skills to strengthen.
Learn three ways to get noticed and grow your career as AI reshapes how developers build software.
GitHub is rebuilding Git storage for agent-scale work ⚡️
GitHub explained the storage work behind Git at agent scale. More coding agents means more branches, refs, fetches, pushes, and short-lived repositories hitting the platform at once.
What changed:
• Repository storage moved to Azure as part of the platform migration.
• Per-reference write quorums help coordinate Git ref updates.
• Virtual replicas backed by object storage reduce the need to copy every repository everywhere.
This is infrastructure work, but .NET teams feel it directly. When CI, bots, Copilot-style agents, and developer machines all create refs concurrently, a normal Git workflow becomes a distributed-systems workload.
Worth reading if your build automation creates branches or tags and you still treat a failed push as "just retry it."
[ Blog ] :
https://github.blog/engineering/architecture-optimization/the-bridge-to-agent-scale-git-infrastructure/
〰〰〰〰〰〰
#dotnet #GitHub #Git #DevOps
@ProgrammingTip
GitHub explained the storage work behind Git at agent scale. More coding agents means more branches, refs, fetches, pushes, and short-lived repositories hitting the platform at once.
What changed:
• Repository storage moved to Azure as part of the platform migration.
• Per-reference write quorums help coordinate Git ref updates.
• Virtual replicas backed by object storage reduce the need to copy every repository everywhere.
This is infrastructure work, but .NET teams feel it directly. When CI, bots, Copilot-style agents, and developer machines all create refs concurrently, a normal Git workflow becomes a distributed-systems workload.
Worth reading if your build automation creates branches or tags and you still treat a failed push as "just retry it."
[ Blog ] :
https://github.blog/engineering/architecture-optimization/the-bridge-to-agent-scale-git-infrastructure/
〰〰〰〰〰〰
#dotnet #GitHub #Git #DevOps
@ProgrammingTip
The GitHub Blog
The bridge to agent-scale Git infrastructure
We moved a copy of 99.99999% of GitHub's repositories to Azure. Here's how per-reference quorums will bring over the rest.