Stephen W Thomas’ Post

Get GitHub Copilot directly in your terminal. It takes just seconds to get Copilot CLI running on your machine: 📦 Install via npm, Homebrew, or WinGet 🔐 Authenticate your GitHub account 🚀 Start coding No IDE required. No plugins. Just your terminal and Copilot — ready to code, debug, and explore your codebase from the command line. Credit: @GitHub #GitHub #Copilot #CopilotCLI #AI #DeveloperTools #Terminal #Productivity

I've been trying out GitHub Copilot CLI today, and no matter how many hints I dropped, including providing it an example of working code from another project, it kept saying that its code was correct and that any issue was external to the project. So I looked at the code and wow, what a mess. I identified the problem (and some other things that needed tidying) and wrote the following to Copilot: > i can still see usage of the ENV vars as well as a hard-coded redirect uri in the code when we should be now using rails credentials -- secondly, you're calling the get_token_set_from_callback wrong because you should be passing it the whole params object not just the code param It then fixed the issue that it was adamant didn't exist! Unfortunately I encountered another issue immediately after where it was trying to call a non-existent method, even though it previously researched the library. This is just one example of a repeated scenario I've encountered after getting Copilot to "one shot" an app for me. The bug-fixing is shots ad nauseam. Re models used: I created the app with Claude Opus 4.6, ran out of credits fixing bugs and switched to the free GPT-4.1, and hit the brick wall above. I have to say, the AI model companies definitely created a money-spinner!

GitHub Copilot CLI Now Generally Available for Developers 📌 GitHub Copilot CLI is now generally available, bringing AI-powered code assistance directly to your terminal-no IDE needed. Devs can run complex tasks, explore codebases, and automate workflows with just a few commands. Say goodbye to context-switching and hello to smarter, faster shell operations. 🔗 Read more: https://lnkd.in/dr4rTZQ7 #Githubcopilotcli #Terminalai #Devopstools #Generativeai

How to use GitHub Copilot better than 99% of people Most developers accept the first suggestion and move on. Meanwhile, the top 1% are using Agent Mode, assigning issues to Copilot, and connecting external tools via MCP. I built a 12-tip visual carousel to close that gap. ━━━━━━━━━━━━━━━━━━━━━━ 𝗪𝗵𝗮𝘁'𝘀 𝗶𝗻𝘀𝗶𝗱𝗲: 𝟭. Switch to Agent Mode 𝟮. Assign GitHub Issues directly to Copilot 𝟯. Add custom instructions to your repo 𝟰. Pick the right model for the task 𝟱. Create reusable prompt files 𝟲. Connect tools via MCP 𝟳. Use Copilot CLI in your terminal 𝟴. Master @workspace, @terminal, and slash commands 𝟵. Automate PR reviews with Copilot 𝟭𝟬. Build agent skills and extensions 𝟭𝟭. Configure org-level governance 𝟭𝟮. Treat your repo as Copilot's brain ━━━━━━━━━━━━━━━━━━━━━━ Every tip has real examples, terminal mockups, code snippets, and links to official GitHub Docs. No fluff. No "just use better prompts" advice. This is the reference I wish I had when I started. 📥 Save this for your next sprint. ♻️ Repost if your team needs this. #GitHubCopilot #AI #DeveloperProductivity #CopilotTips #GitHub #SoftwareEngineering #DevTools

New to the GitHub Copilot CLI? I put together a getting-started blog post to outline how to get started! The GitHub Copilot CLI changes everything. You no longer need to memorize complex syntax—just ask the terminal for what you want in plain English. In my latest blog post, we get you set up from absolute scratch: 🔹 Painless PowerShell installation & VS Code integration 🔹 Managing AI context & models 🔹 Building a custom AI Agent to automate a .NET 2 to .NET 10 upgrade! Stop typing commands by hand. Take a look at the blog post today: https://lnkd.in/gxGecQ9X #GitHubCopilot #GitHubCopilotCLI #GitHubCopilotBeginner

I put together a GitHub Copilot cheatsheet covering everything that actually matters for day-to-day use. 8 pages. Covers: → VS Code + CLI setup in 5 minutes → When to use Instructions vs Skills vs Agents vs Hooks → SKILL.md structure and description writing → Agent orchestration patterns → Hooks lifecycle reference → Complete summary table for all primitives The part most people skip: writing good Skill descriptions. Agents discover skills by matching your description to user intent. a vague description means the skill never gets used. #GitHubCopilot #AITools #DeveloperProductivity #Copilot #Upskilling

Want tips on using GitHub Copilot CLI ? I built a "Tip of the Day" for GitHub Copilot CLI — powered by /chronicle, it learns from how I actually use it 🚀 I use Copilot CLI daily for team investigations, GitHub searches, and workplace lookups. But I kept forgetting about features that would save me time. So I automated it. Now every morning, a personalized tip appears in my terminal — generated by Copilot's /chronicle command, based on my real session history. Here's how it works: - 🔍 /chronicle analyzes my past Copilot sessions — what tools I used, what I asked, what patterns I follow - 🎯 It generates a tip tailored to my workflow — features I haven't tried, better ways to do things I already do - 🔄 A zsh precmd hook displays the tip the first time I interact with any terminal each day — even ones left open overnight - ⏰ A macOS LaunchAgent pre-generates the tip at 7am so it's instant The whole setup is just two files: 1. daily-tip.sh — the zsh hook that calls /chronicle and caches the result 2. A LaunchAgent plist for pre-generation (optional) Add one line to your ~/.zshrc: [[ -f "$HOME/.copilot/daily-tip.sh" ]] && source "$HOME/.copilot/daily-tip.sh" That's it. No Python scripts, no static tip lists, no maintenance. /chronicle does the heavy lifting — it knows your history and gets smarter as your usage evolves. Grab the code: https://lnkd.in/e7CM4Wjz I built all of this using Copilot CLI itself. 😎 #GitHubCopilot #CopilotCLI #DeveloperProductivity #AI #DevTools

I finally integrated GitHub Copilot CLI into my workflow, and the "context switching" tax is officially gone. Instead of jumping to a browser to remember how to undo a commit or filter logs by date, I just type: gh copilot suggest "undo my last 3 commits but keep the changes" Why it’s a win: Natural Language to Bash: It translates what I want to do into executable commands. Explanation Mode: It doesn't just give code; it explains why the flags are used. Shell Integration: Works right inside my existing terminal setup. It’s like having a Senior Dev sitting right next to my prompt. Have you moved your AI workflow into the CLI yet, or are you still a "Tab to Browser" person? GitHub #GitHub #GitHubCopilot #CLI #SoftwareEngineering #DeveloperTools #CodingLife

I've been using GitHub Copilot CLI extensively for the past few weeks. It's been good. I found something recently as part of the exploration that surprised me. I ran into a command called /chronicle improve. Copilot CLI went through my entire session history, every prompt I had typed, every correction I made when the agent got something wrong, every time I had to redirect it because it diverged from my original intent, and turned all of that into updated instructions in my repo's .github/copilot-instructions.md file. Automatically. Think about that for a second. The tool watched where it struggled, identified the patterns in my corrections, and wrote better instructions for itself. There's another variation - /chronicle tips. This one looks at how you're working and suggests where you could be prompting better, using features you haven't discovered, or breaking habits that are costing you time. /chronicle improve makes Copilot smarter about your repo. /chronicle tips makes you smarter about Copilot. Run both periodically. Curious if others have stumbled on this. What else are you finding in Copilot that most people haven't noticed yet.

GitHub Copilot CLI… without a GitHub Copilot subscription? With recent restrictions around GitHub Copilot's new personal subscriptions sign-up, I wanted to see if I could still use the CLI experience with open models. Turns out—you can. I set up Copilot CLI using Open LLMs (BYOK approach), and it opens up a lot of possibilities: • Run models locally (depending on your hardware) • Use hosted models via OpenRouter • Control cost and performance • Customize how AI interacts with your workflows I also went deeper into: Context window management in CLI Model selection (weights, quantization, parameters) LM Studio configuration for running open source models And for a practical demo 👇 I built a skill that converts a wireframe into HTML/React code using the CLI. This setup is surprisingly powerful if you want flexibility beyond standard GH Copilot usage. 🎥 Watch here: https://lnkd.in/eHGM3b97 Let me know in the comments if you would like a copy of the wireframe to HTML code skill. #AI #Copilot #LLM #OpenSource #DeveloperTools #SoftwareEngineering