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@kala shared a link, 3 months, 1 week ago
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Reading across books with Claude Code

A custom LLM agent, built withClaude Codeand some hard-working CLI tools, chewed through 100+ nonfiction books by slicing them into 500-word semantic chunks - and then threading excerpt trails by topic. Under the hood: Chunk-topic indexes lived inSQLite. Topic embeddings flowed throughUMAPfor clust.. read more  

Reading across books with Claude Code
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@kala shared a link, 3 months, 1 week ago
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The Complete Guide to CLAUDE.md

Claude Code just got smarter withCLAUDE.md- a project-level file that loads every time a session starts. Drop in your team's coding quirks, custom commands, naming rules, or traps to avoid. Claude reads it, remembers it, and quietly tailors responses to fit. Think of it likeAGENTS.md, seen in Cursor.. read more  

The Complete Guide to CLAUDE.md
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@devopslinks shared a link, 3 months, 1 week ago
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What I Really Mean When I Say “Good Communication” in Incident Response

In the world of incidents,communication is key. Tailor messages for different audiences: be clear for business stakeholders, factual for IT management, and detailed for fellow responders. Don't let vagueness derail incident response - keep stakeholders informed with precise updates and clear expecta.. read more  

What I Really Mean When I Say “Good Communication” in Incident Response
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@devopslinks shared a link, 3 months, 1 week ago
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Monitoring & Observability: Using Logs, Metrics, Traces, and Alerts to Understand System Failures

Railway just leveled up its observability game. Now logs, metrics, and alerts all live in one tidy dashboard - clean and connected. Structured logs flow straight from stdout/stderr. Metrics pulse in real time. Alerts plug into monitors or deployment webhooks so teams catch firesbeforethey rage... read more  

Monitoring & Observability: Using Logs, Metrics, Traces, and Alerts to Understand System Failures
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@devopslinks shared a link, 3 months, 1 week ago
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Year in Review: Lessons From 12 Projects Patreon Shipped in 2025

Patreon engineers made massive bets in 2025, shipping code across all areas of the system and enabling impactful features like Autopilot's growth tools suite. Expanding Autopilot's scope, reach, and effectiveness was a challenge, especially guaranteeing recipient redemption after email delivery in a.. read more  

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@devopslinks shared a link, 3 months, 1 week ago
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Making a micro Linux distro

A dev dives into building a barebones Linux distro for RISC-V using QEMU. Starts at the metal: compiles the kernel, wires up a no-frills init process, packs it all into an initramfs. Then levels up, drops inu-rootto swap out raw shell scripts for Go-powered userland tools. Adds network. Now it’s a f.. read more  

Making a micro Linux distro
News FAUN.dev() Team
@devopslinks shared an update, 3 months, 1 week ago
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Canonical Introduces Minimal Ubuntu Pro: Smaller Images and Secure Cloud Workloads at Scale

Ubuntu GNU/Linux

Canonical has launched Minimal Ubuntu Pro, enhancing cloud security with lightweight images and robust features. Available on AWS, Azure, and Google Cloud, it offers minimized attack surfaces and long-term support.

Canonical Introduces Minimal Ubuntu Pro: Smaller Images and Secure Cloud Workloads at Scale
News FAUN.dev() Team
@varbear shared an update, 3 months, 1 week ago
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AI's Dependence on Python Deepens as Anthropic Funds Core Ecosystem Work

Python

Anthropic invests $1.5 million in the Python Software Foundation to boost Python ecosystem security. The funding targets improvements in CPython and PyPI, including new tools for package review and malware datasets. It also supports the PSF's core activities and community initiatives.

AI's Dependence on Python Deepens as Anthropic Funds Core Ecosystem Work
News FAUN.dev() Team
@kala shared an update, 3 months, 1 week 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
News FAUN.dev() Team
@varbear shared an update, 3 months, 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.

GPT-5.3-Codex is OpenAI’s advanced agentic coding model, designed to go beyond writing code and operate as a general-purpose collaborator on a computer. It builds on GPT-5.2-Codex by combining stronger coding performance with improved reasoning and professional knowledge, while running about 25% faster. The model is optimized for long-running tasks that involve research, tool use, and complex execution, and it performs at the top of industry benchmarks such as SWE-Bench Pro and Terminal-Bench.

Unlike earlier Codex models that focused primarily on code generation and review, GPT-5.3-Codex can reason, plan, and act across the full software lifecycle. It supports activities such as debugging, deploying, monitoring, writing product requirement documents, creating tests, and analyzing metrics. It can also autonomously build and iterate on complex applications and better interpret underspecified prompts, producing more complete and production-ready results by default.

A defining feature of GPT-5.3-Codex is its interactive, agentic workflow. Users can steer the model while it is working, receive progress updates, and adjust direction without losing context, making it feel more like a teammate than a batch automation tool. The model was even used internally to help debug its own training and deployment processes. GPT-5.3-Codex is available through paid ChatGPT plans in the Codex app, CLI, IDE extension, and web, with API access planned for the future.