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@kala shared an update, 6 days, 23 hours ago
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Anthropic’s New "Economic Primitives" Reveal Who Uses Claude, for What, and How Well It Works

Anthropic's new Economic Index report introduces five "economic primitives" to measure *how* Claude is used: task complexity, user and AI skill level, use case (work, coursework, personal), autonomy, and task success - built from privacy-preserving classification of anonymized Claude.ai and first-party API transcripts from **November 2025**.

Anthropic’s New "Economic Primitives" Reveal Who Uses Claude, for What, and How Well It Works
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@varbear shared an update, 1 week ago
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Tailwind CSS Lays Off 75% of Its Engineering Team as AI Cuts Documentation Traffic by 40%

tailwindcss Vercel

Tailwind CSS laid off roughly **75% of its engineering team** after a **~40% drop in documentation traffic** and an estimated **~80% decline in revenue**, even as usage of the framework continues to grow. According to its creator, AI-driven access to documentation has broken the link between adoption and sustainability.

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@devopslinks shared an update, 1 week ago
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Pulumi Expands IaC Platform to Support Terraform, OpenTofu, and Native HCL

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Pulumi added support for managing Terraform and OpenTofu state in Pulumi Cloud and introduced native HCL support in its infrastructure as code engine. These changes allow teams to use Terraform, OpenTofu, Pulumi languages, and HCL side by side, with shared state visibility, governance features, and AI-assisted operations available across tools.

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DeepSeekMath-V2 is a state-of-the-art mathematical reasoning model built on the DeepSeek-V3.2-Exp-Base architecture with 685 billion parameters. Unlike conventional math-focused language models that optimize only for correct final answers, DeepSeekMath-V2 introduces a self-verification framework where the model generates, inspects, and validates its own mathematical proofs.

This approach enables rigorous, step-by-step reasoning suitable for theorem proving, scientific research, and domains requiring high-integrity logic. The model is trained through a generation-verification loop involving a dedicated LLM-based verifier and reinforcement learning optimized for proof correctness rather than answer matching.

DeepSeekMath-V2 achieves gold-level scores on IMO 2025 and CMO 2024, along with a groundbreaking 118/120 on the Putnam 2024 contest. Released under the Apache 2.0 license and hosted on Hugging Face, it is fully open source for research and commercial use.