Keeping up with mobile development requires a steady flow of high quality information. RSS feeds are still one of the best ways to follow platform updates, deep technical articles, and long form insights without relying on social media algorithms.

What are RSS feeds

RSS stands for Really Simple Syndication.
An RSS feed is a constantly updated stream of content published by a website. Instead of visiting dozens of sites every day, you subscribe to their feeds and read all new articles in one place.

When a site publishes a new post, it automatically appears in your RSS reader. No algorithms, no distractions, no missing important updates.

RSS is especially useful for developers because it lets you follow official blogs, deep technical articles, and long form content in a clean chronological order.

How to read RSS feeds

To read RSS feeds you need an RSS reader. An RSS reader is an app or web service where you add feed links and read new posts as they appear.

You copy the feed URL and add it to the reader. From that moment on, new articles show up automatically.

Popular free RSS readers

Feedly
https://feedly.com/
One of the most popular RSS readers. Available on web, iOS, and Android. Easy to use and great for organizing feeds into folders. The free plan is more than enough for most developers.

Inoreader
https://www.inoreader.com
A powerful RSS reader with excellent filtering and organization features. Works on web and mobile. Very popular among power users and developers who follow many feeds.

NetNewsWire
https://netnewswire.com/
A free and open source RSS reader for Apple platforms. Very fast, clean, and privacy focused. Ideal if you want a native macOS and iOS experience without cloud services.

A curated list of essential RSS feeds for mobile developers

Android Developers Blog
https://android-developers.googleblog.com/atom.xml
The official Android Developers Blog published by Google. It covers platform changes, new APIs, tooling updates, Jetpack libraries, performance improvements, and long term Android roadmap insights.

Google Android Medium Publication
https://medium.com/feed/androiddevelopers
Articles written by Android engineers at Google and the community. Often complements the official Android Developers Blog with practical examples and deep dives.

Android Weekly
https://androidweekly.net/rss.xml
A weekly curated newsletter with links to the best Android articles, libraries, tools, and open source projects. Very useful for discovering high quality content you might otherwise miss.

AppCoda
https://www.appcoda.com/rss/
A popular blog focused mainly on iOS development. It provides practical tutorials on Swift, SwiftUI, UIKit, and Apple platform APIs with clear explanations and code examples.

Apple Developer News
http://developer.apple.com/news/rss/news.rss
The official Apple developer feed. It includes announcements about SDK changes, App Store policies, WWDC updates, platform releases, and new Apple frameworks.

iOS Dev Weekly
https://iosdevweekly.com/issues.rss
A long running weekly newsletter curated by Dave Verwer. It aggregates the best iOS development articles, tools, libraries, and discussions from across the community.

Kotlin Blog by JetBrains
https://blog.jetbrains.com/kotlin/feed/
The official Kotlin blog by JetBrains. It covers Kotlin language evolution, Kotlin Multiplatform updates, compiler changes, and best practices relevant to Android and cross platform development.

ProMobile.Dev
https://promobile.dev/feed
A focused feed covering mobile development news, articles and tutorials across Android, iOS, and Kotlin Multiplatform.

Swift.org Blog
https://www.swift.org/atom.xml
The official Swift language blog. It publishes proposals, language evolution updates, compiler changes, and announcements relevant to Swift developers on all platforms.

Use Your Loaf
https://useyourloaf.com/blog/rss.xml
An iOS focused blog with deep dives into Apple frameworks, APIs, and platform behavior. Known for clear explanations and attention to technical detail.

Paul Hudson - Hacking with Swift
https://www.hackingwithswift.com/articles/rss
High quality Swift and iOS development content ranging from beginner to advanced topics, written clearly and consistently updated.

Learn how to build agentic AI workflows.

We just posted a course on the freeCodeCamp.org YouTube channel that provides a comprehensive overview of agentic AI, defining agents as software entities that use LLMs to perceive environments, make decisions, and execute actions to achieve specific goals. It explores the critical distinction between static workflows and dynamic agentic systems, emphasizing how LLMs serve as a reasoning "brain" to decompose tasks at runtime. Rola Dali, PhD created this course.

Through practical Python demonstrations, the course covers essential components like system prompts, tools, and memory, while also comparing architectural patterns such as Supervisor and Swarm. Finally, the session addresses the future of technology by discussing emerging interoperability protocols like MCP and the shifting paradigms of software development in an AI-driven world.

Here are the sections covered in this course:

• Introduction and Speaker Background

• A Brief History of Artificial Intelligence (1940s–Present)

• Traditional Machine Learning vs. Generative AI

• The Three Pillars of AI: Algorithms, Data, and Compute

• Specific Tasks vs. General Task Execution

• Defining Agency and the Spectrum of Autonomy

• Agentic Milestone Timeline (2017–2026)

• What is a Generative AI Agent?

• Agents vs. Workflows: Dynamic Flow vs. Static Paths

• Pros and Cons of Agentic Systems

• Patterns and Anti-patterns: When to Use Agents

• The Core Components of an Agent

• Choosing the Right LLM for Your Agent

• Crafting Identity with System Prompts

• Understanding Memory: Intrinsic, Short-term, and Long-term

• Enhancing Capabilities with Tools and Actions

• Hands-on Implementation: From Single LLM Call to Python Agent

• Adding Memory and History to Your Custom Agent

• Building Agents with Frameworks (LangChain)

• The Evolving Landscape of Models and Frameworks

• Agentic Architectural Patterns: Supervisor vs. Swarm

• Case Study: Single Agent vs. Supervisor Architecture

• Deep Dive: Swarm Architecture Performance

• When to Choose Multi-agent Systems

• Interface Protocols: MCP, A2A, and AGUI

• How to Evaluate Agentic Systems (LLM vs. System vs. App)

• Evaluation Methods: Code-based, LLM-as-a-Judge, and Human

• Current Challenges: Hallucinations, Cost, and Debugging

• Real-world Incidents and the AI Incident Database

• Career Impact: Which Jobs are Most at Risk?

• Software 3.0: The Evolution of Development Paradigms

• Weathering the Storm: Strategies for the Future

• Beyond LLMs: World Models and the Future of AMI

• Recommended Resources and Closing Thoughts

Watch the full course on the freeCodeCamp.org YouTube channel (2-hour watch).

OAuth 2.0 is an industry-standard authorization framework allowing third-party apps to access user data on another service (like Google or Facebook) without sharing passwords, instead using temporary, limited-scope access tokens for delegated access, enhancing security and privacy by restricting permissions.

We just posted a course on the freeCodeCamp.org YouTube channel that will provide you an introduction to OAuth 2.0.

Here are the sections in this course:

• Introduction to OAuth 2.0

• OAuth 2.0 in Simple Terms: The Valet Key System

• The Four OAuth Roles (Resource Owner, Client, Auth Server, Resource Server)

• Why PKCE (Proof Key for Code Exchange) Matters

• Project Setup & Folder Structure

• Building the Authorization Server

• Authorization Server: Code Imports & Initial Setup

• Building the Resource Server (API)

• Building the Client App (Authorization Code + PKCE)

• Running the Full System (Auth, Resource, Client Servers)

• Debugging and Fixing the JWKS Error

• Debugging and Fixing the Axios 400 Error

• Summary of Key Roles and Best Practices

• Setting up the GitHub Repository

Watch the full course on the freeCodeCamp.org YouTube channel (2-hour watch).

[1.0.0b260106] - 2026-01-06

Added

• repo: Add issue template and additional labeling (#3006) by @eavanvalkenburg

Changed

• None

Fixed

• agent-framework-core: Fix max tokens translation and add extra integer test (#3037) by @eavanvalkenburg
• agent-framework-azure-ai: Fix failure when conversation history contains assistant messages (#3076) by @moonbox3
• agent-framework-core: Use HTTP exporter for http/protobuf protocol (#3070) by @takanori-terai
• agent-framework-core: Fix ExecutorInvokedEvent and ExecutorCompletedEvent observability data (#3090) by @moonbox3
• agent-framework-core: Honor tool_choice parameter passed to agent.run() and chat client methods (#3095) by @moonbox3
• samples: AzureAI SharePoint sample fix (#3108) by @giles17

New Contributors

• @takanori-terai made their first contribution in #3070

Full Changelog: python-1.0.0b251223...python-1.0.0b260106

A field guide to sandboxes for AI

He starts by differentiating between containers (which share the host kernel), microVMs (their own guest kernel behind hardwae virtualization), gVisor userspace kernels and WebAssembly/isolates that constrain everything within a runtime.

The piece then dives deep into terminology, approaches and the landscape of existing tools.

I think using the right sandboxes to safely run untrusted code is one of the most important problems to solve in 2026. This guide is an invaluable starting point.

Via lobste.rs

Tags: sandboxing, ai, generative-ai, llms