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varbear
@varbear shared an update, 2 weeks, 2 days ago
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Tailwind CSS Lays Off 75% of Its Engineering Team as AI Cuts Documentation Traffic by 40%

#Tailwin...  #AI impa...  #enginee...  #GenAI  #Vercel 
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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News FAUN.dev() Team Trending
devopslinks
@devopslinks shared an update, 2 weeks, 2 days ago
FAUN.dev()

Pulumi Expands IaC Platform to Support Terraform, OpenTofu, and Native HCL

#infrast...  #Terrafo...  #Pulumi  #HCL  #OpenTof... 
Pulumi Terraform

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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Magika is an open-source file type identification engine developed by Google that uses machine learning instead of traditional signature-based heuristics. Unlike classic tools such as file, which rely on magic bytes and handcrafted rules, Magika analyzes file content holistically using a trained model to infer the true file type.

It is designed to be both highly accurate and extremely fast, capable of classifying files in milliseconds. Magika excels at detecting edge cases where file extensions are incorrect, intentionally spoofed, or absent altogether. This makes it particularly valuable for security scanning, malware analysis, digital forensics, and large-scale content ingestion pipelines.

Magika supports hundreds of file formats, including programming languages, configuration files, documents, archives, executables, media formats, and data files. It is available as a Python library, a CLI, and integrates cleanly into automated workflows. The project is maintained by Google and released under an open-source license, making it suitable for both enterprise and research use.

Magika is commonly used in scenarios such as:

- Secure file uploads and content validation
- Malware detection and sandboxing pipelines
- Code repository scanning
- Data lake ingestion and classification
- Digital forensics and incident response