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Users Only Care About 20% of Your Application

Modern apps burst with features most people never touch. Users stick to their favorite 20%. The rest? Frustration, bloat, ignored edge cases. Tools like **VS Code**, **Slack**, and **Notion** nail it by staying lean at the core and letting users stack what they need. Extensions, plug-ins, integrati.. read more  

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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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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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@faun shared a link, 2 months ago
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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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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
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Jupyter Agents: training LLMs to reason with notebooks

Hugging Face dropped an open pipeline and dataset for training small models—think **Qwen3-4B**—into sharp **Jupyter-native data science agents**. They pulled curated Kaggle notebooks, whipped up synthetic QA pairs, added lightweight **scaffolding**, and went full fine-tune. Net result? A **36% jump .. read more  

Jupyter Agents: training LLMs to reason with notebooks
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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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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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@faun shared a link, 2 months ago
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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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