Command Line Basics for Beginners

Scheduling actions in the GitHub Copilot CLI

GitHub Copilot CLI bổ sung hai lệnh thử nghiệm /every (lặp lại theo khoảng thời gian, tối thiểu 10 giây, tối đa 1 ngày) và /after (trì hoãn một lần) để lập lịch prompts. Các lệnh này chỉ hoạt động trong phiên terminal hiện tại và yêu cầu bật chế độ thử nghiệm. Để lập lịch lâu dài, người dùng cần dùng Task Scheduler, GitHub Actions hoặc Azure DevOps pipelines.

Lập trình viên nên đọc để khám phá cách tự động hóa các nhiệm vụ lập trình nhỏ nhặt bằng GitHub Copilot CLI, tiết kiệm thời gian và tránh mất tập trung trong quá trình làm việc hàng ngày.

Query Speed Insights from the Vercel CLI

Vercel now lets you query Speed Insights data directly from the CLI using the vercel metrics command. It surfaces Core Web Vitals (LCP, INP, CLS) and other performance metrics (FCP, TTFB) from real user traffic. You can filter by region, device type, and time range, and even give a coding agent CLI access to answer performance regression questions programmatically.

Every (Agents) Connection to Railway

Railway outlines three ways AI coding agents can connect to and interact with the Railway platform: Local MCP (via the Railway CLI, best for local development), Remote MCP (hosted at mcp.railway.com, OAuth-based, for hosted assistants and CI), and the Railway Agent (a Railway-aware operator accessible via CLI or MCP for multi-step tasks). The post covers installation via a one-liner, CLI improvements for agent-friendliness (--json, -y, -s/-e flags), and guidance on when to use each connection method. It also details the Railway Agent's capabilities including diagnosing failing deployments, managing services, and opening pull requests with fixes.

State of Rails: How Railway Is Building Infrastructure for AI Agents

Railway is building an agent-first deployment platform designed to let AI coding agents handle the full software development loop — from signup and first deploy to debugging, iteration, and operations. Key features include an agent-optimized CLI with JSON output and reduced interactivity requirements, local and remote MCP server support (with the older npx path deprecated), agent skills that teach agents when and how to use Railway tools, sandboxes for disposable execution environments, a Railway-native Agent that understands the platform's project model, and Guardrails policies (starting with deploy source control) that let teams safely expand what agents are allowed to do. MCP-driven agent usage has grown more than 5x in the past month.