🍔🧠 How Node.js Works Behind the Scenes (Deep Dive)

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📚 Software Engineering Articles

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• Master session management with cookies and tokens for better security

• How Google handles tech debt efficiently in its engineering teams

• Learn about 5 core distributed concepts every developer must understand

• Revolutionary web performance tips to speed up your site

• Discover how Cursor indexes codebases lightning fast

🗞️ Tech and AI Trends

• Apple partners with Anthropic to build a revolutionary coding platform

• Uber expands robotaxi service to 15 new cities

• Stripe launches stablecoin accounts in over 100 countries

👨🏻‍💻 Coding Tip

• Use Go's select with a timer for graceful timeouts in concurrent operations

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How Node.js Works Behind the Scenes ⚡

Node.js powers millions of backend applications by executing JavaScript code through an event loop with multiple specialized phases. Understanding how it works internally is crucial for writing performant server-side applications that handle concurrent operations efficiently.

The challenge: 
A runtime that can process async operations like file I/O and network requests without blocking while maintaining predictable execution order across different types of operations.

Implementation highlights:

• Event loop phases: Multiple specialized phases (timers, poll, check etc.) to handle different types of operations efficiently

• libuv integration: C library that provides cross-platform async I/O operations and event loop implementation

• Poll phase optimization: Blocks efficiently waiting for I/O events rather than spinning the loop

• process.nextTick: Special queue that runs after each phase for fine-grained control

• Promise microtasks: Lower priority than nextTick but higher than macrotasks for predictable async execution

Results and learnings:

• Efficient I/O: Non-blocking handling of file and network operations

• Predictable order: Well-defined phase sequence ensures consistent execution patterns

• Developer-friendly: Familiar JavaScript APIs while handling complex async operations under the hood

Node.js shows that with careful system design, we can build powerful server-side applications using JavaScript. Understanding the event loop phases helps write better code by working with the runtime rather than against it.

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🤖 Apple and Anthropic Team Up to Build AI-Powered Coding Platform (2 min)

Brief: Apple partners with Anthropic to develop an AI coding tool using Claude Sonnet for writing, editing, and testing code, potentially integrating it into Xcode for internal use first.

🚗 Uber Pumps $100M into WeRide to Scale Robotaxis to 15 New Cities (2 min)

Brief: Uber doubles down on autonomous vehicles with a $100M investment in WeRide to expand their robotaxi partnership to 15 more cities, focusing on Europe and beyond.

🚀 Google's Gemini 2.5 Pro Update Enhances AI Coding Capabilities (2 min)

Brief: Google's latest Gemini 2.5 Pro update significantly improves the AI model's coding performance, making it more efficient and accurate for developers.

💰 Stripe Expands Stablecoin Payments to 100+ Countries, Leveraging USDC and USDB (2 min)

Brief: Stripe now enables merchants in 100+ countries to hold and transfer funds via stablecoins (USDC and USDB), accelerating cross-border payments and deepening its fintech ecosystem.

🤖 Amazon’s "Vulcan" Robot Can Now Feel—But Won’t Replace Workers (3 min)

Brief: Amazon unveils Vulcan, a touch-sensitive warehouse robot that handles 75% of inventory items, operates 20 hours/day, and aims to reduce worker injuries—but insists it’s not replacing humans.

🎨 Figma Launches AI-Powered 'Vibe-Coding' for Automated Web & App Design (3 min)

Brief: Figma introduces AI-driven "vibe-coding", allowing users to generate functional app and website code from text prompts or existing designs, with premium access starting at $16/month and integration of Anthropic’s Claude AI model.

This week’s coding challenge:

This week’s tip:

In Go, use select with a default case and a timer to implement graceful timeouts for concurrent operations while still processing results that arrive within the time window. This pattern provides more control than context-based timeouts and allows partial results to be handled.

Wen?

• Distributed systems: Collecting partial results from multiple services when complete responses aren't critical.

• Resource cleanup: Gracefully shutting down goroutines while still processing in-flight requests.

• Batch processing: Implementing "process as much as possible within time window" scenarios.

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