Coord’s Post

Why the "Rubber Duck" is the most important update to Copilot in 2026. GitHub just dropped an experimental feature that solves a massive headache for dev managers: AI hallucinations in multi-file refactors. It’s called Rubber Duck mode, and it’s a brilliant move in agentic design. Instead of one model checking its own homework (which rarely works bias in, bias out), Copilot now pairs your primary model with a "reviewer" from a completely different AI family. How it works: If you're using Claude as your primary coder, GitHub spins up GPT-5.4 as the "Rubber Duck" to critique the plan before a single line of code is written. The result? Early benchmarks show it closes nearly 75% of the performance gap on complex, 70+ step tasks. It’s catching the silent logic errors that usually don't surface until a production bug report hits your desk. In my view, 2026 isn't about which LLM is "smarter." It’s about which multi-agent architecture provides the highest guardrails for our teams. #GitHubCopilot #AI #SoftwareEngineering #AgenticAI #GenAI

GitHub Launches Rubber Duck Experimental Feature for Copilot CLI 📌 GitHub’s Rubber Duck experiment brings a second AI mind to Copilot CLI, cross-checking code plans with a different model family to catch “confident mistakes” before they escalate. It boosts accuracy on complex tasks - closing 74.7% of performance gaps and catching critical bugs like silent overwrites or dependency conflicts. Now in experimental mode, it’s a bold leap toward smarter, more reliable AI coding assistants. 🔗 Read more: https://lnkd.in/dfnCgvZS #Githubcopilotcli #Rubberduck #Multimodelreview #Experimentalfeature #Aiassistant

GitHub Adds “Rubber Duck” Review Agent to Copilot CLI GitHub has launched an experimental “Rubber Duck” mode in Copilot CLI, bringing a second AI model into the loop to review, challenge, and validate the primary agent’s work before execution. What’s interesting isn’t just the feature - it’s the pattern. 🔹 Second Opinion by Design: A separate model from a different AI family evaluates plans before they run. 🔹 Focused Review Layer: It flags missed assumptions, edge cases, and hidden risks. 🔹 Better Outcomes on Complex Tasks: Especially effective on multi-file, high-step problems where errors compound. 🔹 Agent + Reviewer Pattern: Introduces a structured “builder + critic” dynamic inside AI workflows. As agents become more autonomous, the risk isn’t that they can’t execute - it’s that they execute flawed plans too confidently. Rubber Duck introduces friction in the right place: before things break. At ScaleGlide, we see GitHub’s Rubber Duck as a clear signal that agentic development is moving from raw execution to structured validation. But as multiple agents enter the loop, the real bottleneck shifts downstream — into how feedback is prioritized, conflicts are resolved, and decisions are ultimately made. Read more: https://lnkd.in/dUwd5dms #AI #GitHubCopilot #AICoding #AgenticAI #DevTools #SoftwareEngineering #FutureOfWork #GlenFlow

Your terminal just got a co-pilot. And it changes more than you think. GitHub Copilot CLI is now generally available. Natural language in your terminal. No more Googling obscure flags or copy-pasting Stack Overflow commands. But here's the part most people are skipping past: → It's not just autocomplete for commands → It explains what a command does before you run it → It's now moving into 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 - meaning it can chain actions together → The terminal is becoming a conversation, not just an execution layer Pair this with tools like ai-agents-metrics (tracking token cost, retry pressure, outcome quality) and you start to see the bigger picture. We're not just writing code faster. We're building systems that think in steps. 𝗧𝗵𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝘄𝗵𝗼 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝘀 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 today will look like a wizard to teams still using AI as a fancy search bar. If you haven't tried Copilot CLI yet, this week is a good time to start. What's your take - is AI in the terminal a productivity leap or just another layer of abstraction we'll eventually fight with? #GitHubCopilot #AITools #DeveloperProductivity #AgenticAI #Tech

OpenAI's coding tool just became something much bigger. The latest Codex desktop update adds computer use, an in-app browser called Atlas, image generation, and scheduled automations — transforming it from an AI coding assistant into a full AI super app. Claude Code, Cursor, and GitHub Copilot are all in the crosshairs. The race to own the developer desktop is intensifying fast. And the winner won't just be a coding tool — it'll be the AI that controls your entire workflow. 🔗 Full article in the comments. #AINews #ArtificialIntelligence #AITools #AIWire #Developer

GPT-5.5 Is Live in Copilot. This One’s Actually Different. GPT-5.5 just dropped inside GitHub Copilot. Here’s why developers should care. 🧵 Forget chatbots. This model is built for real coding work — multi-step agentic tasks, debugging complex codebases, and running long workflows across tools without falling apart. Early testers describe it as the first model that actually understands how a codebase fits together. Not just autocomplete. Actual reasoning about your code. What’s new: → Best-in-class on complex agentic coding benchmarks → Fewer tokens, same speed, better results → Available across VS Code, JetBrains, Xcode, GitHub Mobile, and more Who gets it: Copilot Pro+, Business, and Enterprise users. The catch? A 7.5× premium request multiplier at launch. It’s not cheap to run — but if it saves you hours of debugging, the math still works. The rollout is gradual. If it’s not in your model picker yet, it will be soon. The bar for AI coding tools just moved. Again. #OpenAI #GitHubCopilot #GPT55 #AIEngineering #DevTools

🦆 GitHub just shipped a "Rubber Duck" agent for Copilot CLI — and the data backs it up. The idea is simple but powerful: after the primary model writes code, a second model from a different AI family automatically reviews it. Why it works → Models from the same family share the same blind spots. Cross-architecture review catches a completely different class of errors than self-review. The results? 74.7% gap closure in code quality issues. This is basically institutionalizing what top engineers already do — getting a code review from someone with a different perspective. Currently available in Copilot CLI only. VS Code coming soon. 🔗 Credit: @burkeholland #GitHubCopilot #AI #CopilotCLI #CodeReview #SoftwareEngineering #DeveloperTools

⚠️ Addictive tech warning for developers. Once you add a 🦆rubber duck to your AI agent pipeline, you’ll start feeling uncomfortable without it. This is exactly what happened to me. I no longer want to rely on a single model’s opinion for important technical decisions, and I definitely don’t want extra manual steps just to get a second perspective. That’s where “Rubber Duck”, an experimental feature in the GitHub Copilot CLI, really worked for me: - enable it with: "copilot --experimental" (Rubber Duck is the 1000th reason for you to switch to terminal-first development) - watch one LLM actively criticise another’s decisions right at the moments where it matters most, pushing towards a better solution - everything happens automatically, no extra friction, no context switching It is a targeted reviewer that steps in at high-value moments such as after drafting a plan, after a complex implementation, and after writing tests before execution. That feels like a very practical way to reduce compounding errors early, especially in long-running or multi-file tasks. So having AI challenge AI has quietly become part of how I build now. Would you trust critical technical decisions to a single model, or is multi-model critique the new baseline for serious AI-assisted development? Ready to try Rubber Duck? I warned you :) More details: https://msft.it/6044Q4Zs2 Morten Stange Bye, Haakon Hasli, Christian Tryti, Else Tefre, Francesco Manni, Jaime De Mora, Martin Woodward, Lee Stott, Christoffer Noring, Daniel Meppiel, Joel Norman, Ömür Sert, Adil I., Sebastien Le Calvez, 🥑 Aaron Powell, Nick McKenna, Burke Holland, Cornelia Bjørke-Hill #GitHubCopilot #GitHubCopilotCLI #CopilotCLI #DeveloperTools #AIAgents #CopilotRubberDuck #msftadvocate

Hot take on AI coding tools 👇 After testing multiple tools: • Codex → best for accurate, structured code & full tasks • RooCode / Continue → best for command-based workflows & control • Copilot → great for daily coding… ⚠️ but mixing models sometimes creates messy or inconsistent output 👉 So the real answer is: There is no “best tool” — it depends on how you work. 👨💻 If you want: • precision → Codex • control → RooCode / Continue • speed → Copilot 💬 What’s your experience? Which one actually saves you time in real projects? #AI #Coding #Developers #SoftwareEngineering #GitHub #OpenAI #RooCode

The Death of the Unlimited Vibe: Why GitHub Copilot is Gating the Future The era of "all-you-can-prompt" is coming to an end. 🛑 GitHub’s latest changes to Copilot Individual plans are more than just a pricing update—they are the first major reality check for the "Vibe Coding" movement. When every prompt could counts against a weekly limit! Read the full breakdown below! Everything Mr. Osama Elzero said about why programmers should learn the fundamentals of programming rather than fully relying on AI and "Vibe Coding" turned out to be true! ------------------------------------------------------------------------------------- #SoftwareEngineering #AI #GitHubCopilot #VibeCoding #GenerativeAI #Productivity #TechTrends #WebDev #FutureOfWork