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@cinnamon_msft: GitHub Copilot CLI now has a statusline feature! Here's how to set it up with Oh My Posh

X AI KOLs Following · 19h ago Cached

GitHub Copilot CLI introduces a statusline feature, with setup instructions for Oh My Posh.

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#github-copilot

AgentKanban for VS Code - A task board with AI agent harness integration. Create and plan tasks with real-time collaboration, then hand off to GitHub Copilot

Reddit r/artificial · yesterday Cached

AgentKanban is a VS Code extension that integrates with GitHub Copilot to manage AI agent tasks, persist context via MCP, and enable resumable workflows through a collaborative Kanban board.

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#github-copilot

AI bills can be as big as a postdoc salary. Is the cost worth it?

Reddit r/ArtificialInteligence · yesterday Cached

Research laboratories are grappling with rising AI subscription costs and usage limits from providers like OpenAI and GitHub, raising questions about the cost-benefit ratio for scientific research.

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#github-copilot

@thsottiaux: For Codex, we’ve been thinking about keeping a stable release cadence and have a larger release each week on Thursday. …

X AI KOLs Following · yesterday

A developer discusses plans for GitHub Copilot Codebase to adopt a stable weekly release schedule with larger updates on Thursdays.

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#github-copilot

The April every AI plan broke (18 minute read)

TLDR AI · 2026-05-07 Cached

The article analyzes a series of chaotic pricing and plan adjustments by Anthropic, OpenAI, and GitHub in April, attributing them to the struggle of aligning legacy subscription models with new, high-cost agent usage patterns.

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#github-copilot

Changes to GitHub Copilot individual plans

Hacker News Top · 2026-04-20 Cached

GitHub pauses new Copilot Individual sign-ups and tightens usage limits while removing Opus models from Pro tier to curb soaring compute demand from agentic workflows.

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#github-copilot

Evaluating large language models trained on code

OpenAI Blog · 2021-07-07 Cached

OpenAI introduces Codex, a GPT model fine-tuned on GitHub code, achieving 28.8% functional correctness on HumanEval (a new benchmark for code synthesis from docstrings), significantly outperforming GPT-3 (0%) and GPT-J (11.4%). The paper demonstrates that repeated sampling improves performance to 70.2% with 100 samples, and discusses limitations and broader impacts of code generation systems.

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