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Authentication Explained: When to Use Basic, Bearer, OAuth2, JWT & SSO

Modern apps don’t just check passwords—they rely on **API tokens**, **OAuth**, and **Single Sign-On (SSO)** to know who’s knocking before they open the door... read more  

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Uncommon Uses of Common Python Standard Library Functions

A fresh guide gives old Python friends a second look—turns out, tools like **itertools.groupby**, **zip**, **bisect**, and **heapq** aren’t just standard; they’re slick solutions to real problems. Think run-length encoding, matrix transposes, or fast, sorted inserts without bringing in another depen.. read more  

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Building a Resilient Data Platform with Write-Ahead Log at Netflix

Netflix faced challenges like data loss, system entropy, updates across partitions, and reliable retries. To address these, they built a generic Write-Ahead Log (WAL) system serving a variety of use cases like delayed queues, generic cross-region replication, and multi-partition mutations. WAL abstr.. read more  

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Writing Load Balancer From Scratch In 250 Line of Code

A developer rolled out a fully working **Go load balancer** with a clean **Round Robin** setup—and hooks for dropping in smarter strategies like **Least Connection** or **IP Hash**. Backend servers live in a custom server pool. Swapping balancing logic? Just plug into the interface... read more  

Writing Load Balancer From Scratch In 250 Line of Code
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Inside NVIDIA GPUs: Anatomy of high performance matmul kernels

NVIDIA Hopper packs serious architectural tricks. At the core: **Tensor Memory Accelerator (TMA)**, **tensor cores**, and **swizzling**—the trio behind async, cache-friendly matmul kernels that flirt with peak throughput. But folks aren't stopping at cuBLAS. They're stacking new tactics: **warp-gro.. read more  

Inside NVIDIA GPUs: Anatomy of high performance matmul kernels
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Implementing Vector Search from Scratch: A Step-by-Step Tutorial

Search is a fundamental problem in computing, and vector search aims to match meanings rather than exact words. By converting queries and documents into numerical vectors and calculating similarity, vector search retrieves contextually relevant results. In this tutorial, a vector search system is bu.. read more  

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5 Free AI Courses from Hugging Face

Hugging Face just rolled out a sharp set of free AI courses. Real topics, real tools—think **AI agents, LLMs, diffusion models, deep RL**, and more. It’s hands-on from the jump, packed with frameworks like LangGraph, Diffusers, and Stable Baselines3. You don’t just read about models—you build ‘em i.. read more  

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The productivity paradox of AI coding assistants

A July 2025 METR trial dropped a twist: seasoned devs using Cursor with Claude 3.5/3.7 moved **19% slower** - while thinking they were **20% faster**. Chalk it up to AI-induced confidence inflation. Faros AI tracked over **10,000 developers**. More AI didn’t mean more done. It meant more juggling, .. read more  

The productivity paradox of AI coding assistants
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Becoming a Research Engineer at a Big LLM Lab - 18 Months of Strategic Career Development

To land a big career role like Mistral, mix efficient **tactical** moves (like LeetCode practice) with **strategic** ups, like building a powerful portfolio and a solid network. Balance is key; aim to impress and prepare well without overlooking the power of strategy in shaping a successful career... read more  

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Building a Natural Language Interface for Apache Pinot with LLM Agents

MiQ plugged **Google’s Agent Development Kit** into their stack to spin up **LLM agents** that turn plain English into clean, validated SQL. These agents speak directly to **Apache Pinot**, firing off real-time queries without the usual parsing pain. Behind the scenes, it’s a slick handoff: NL2SQL .. read more  

Building a Natural Language Interface for Apache Pinot with LLM Agents
FAUN.dev() is a developer-first platform built with a simple goal: help engineers stay sharp without wasting their time. It curates practical newsletters, thoughtful technical blogs, and useful developer tools that focus on signal over noise.

Created by engineers, for engineers, FAUN.dev() is where experienced developers turn to keep up with the fast-moving world of DevOps, Kubernetes, Cloud Native, AI, and modern programming. We handpick what matters and skip the fluff.

If it’s on FAUN.dev(), it’s worth your attention.

Beyond curation, we run a course marketplace (WIP) designed to keep developers current. These courses go deep into the subjects that shape real-world work—things like Kubernetes internals, modern DevOps workflows, cloud-native architecture, and using AI tools to build faster and smarter. It’s practical learning, taught by people who’ve done the work. Developers from companies like GitHub, Netflix, and Shopify already rely on FAUN.dev() to stay on top of their game. They trust us because we keep it real: no hype, no filler, just what you need to grow and do your best work. For sponsors and partners, FAUN.dev() offers access to a focused, engaged audience of technical professionals. This isn’t just another broad developer community—it’s a place where smart engineers go to get smarter. If you have something meaningful to offer them, you’ll be in good company. In short, FAUN.dev() is more than a content hub. It’s a place to grow, to learn, and to connect with what really matters in software today.