Happy New Year, everyone! Over the past few years, AI has consistently occupied the center stage of the tech world. But looking back from the start of 2026, I’ve noticed a significant shift: since late 2025, the obsession with “trillion-parameter models” and “leaderboard benchmarks” has gradually cooled. In its place is a sober, hands-on focus on the meticulous cultivation of AI Workflows.
If the past two years were characterized by most people experimenting with chatbots, today, AI has shattered the constraints of the chat box. Through CLI tools, MCP (Model Context Protocol), and various Slash commands, Skills, and SubAgents, AI is no longer just an external utility for experienced developers. Instead, it has become like a plugin, permeating every capillary of our terminals, editors, and even the operating system itself.
In this regard, macOS has demonstrated a serendipitous, natural advantage. Leveraging mature automation tools like AppleScript and Shortcuts, even non-developers can grant AI access to their private data without complex API development. This “old tech finding new life” has provided Apple with a new moat in the AI era. If this capability is fully unleashed on iOS through system-level Agents, we may see a profound reshaping of hardware device form factors.
Meanwhile, some manufacturers are taking a more “radical” approach. ByteDance’s Doubao phone attempts to “brute-force” control over everything at the system level by reading the screen and simulating interactions. Huawei, on the other hand, employs an A2A strategy, attempting to build a unified agent scheduling mechanism in the background. Regardless of the path, 2026 marks a singularity for the average consumer: AI is no longer a tool for conversation; it is explicitly or implicitly taking over our digital lives.
As the old saying goes: When a technology is no longer constantly talked about, it means it has truly integrated into our lives, becoming as indispensable as the blood in our veins.
However, the more seamless it becomes, the more vigilant we must be. As AI sinks deep into every detail of our workflows, privacy will become the ultimate luxury. In our pursuit of extreme automation and efficiency, the core challenges of 2026 will be how we choose our service providers, how we balance local versus cloud-based models, and how we preserve that last bit of symbolic “privacy.”
2026 is here. Have you started integrating AI into your workflow?
Recent Recommendations
The Indie Developer’s Trial: Zipic’s Productization Journey from 0 to 1
Zipic is an image compression tool I’ve been using frequently. I’ve personally witnessed how this app evolved from a small workplace necessity into an efficient, refined, and focused successful product through the continuous refinement by its author Shili. Indie developers often operate as a “one-person army,” constantly switching between strategy, design, development, distribution, and promotion. To uncover the story behind this journey, I invited Shili to review Zipic’s entire process from 0 to 1. The complete series consists of three chapters: product design (this article), distribution and sales without relying on the Mac App Store, and technical details review: SwiftUI pain points and performance bottlenecks.
Swift vs. Rust: 5 Surprising Facts Learned from the Ultimate Memory Management Showdown
In the developer community, discussions about Swift and Rust performance never cease. The conventional wisdom is: Swift is relatively slow due to Automatic Reference Counting (ARC), while Rust is renowned for its extreme speed and memory efficiency. However, Snow argues that these simple labels of “fast” and “slow” often obscure the fundamental differences in their design philosophies: Swift prioritizes developer experience and ecosystem compatibility, while Rust pursues ultimate performance and compile-time safety.
Through real-world examples, the article reveals five truths: Rust’s ownership rules are essentially zero-cost compile-time tools; Swift’s real performance burden comes from Objective-C compatibility rather than ARC itself; ARC’s core issue is performance unpredictability; for concurrency safety, Swift relies on runtime protection while Rust achieves compile-time guarantees; and why Swift cannot “become” Rust.
StoreKit Subscriptions: A Practical Guide
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Skip 2025 Retrospective and 2026 Roadmap
In 2025, with the official release of Swift SDK for Android on swift.org, Skip provided native compilation support through Skip Fuse, unlocking thousands of native Swift packages for use on Android. New dual-platform frameworks were added for NFC, Stripe, PostHog, Auth0, Socket.IO, and more. iOS 26’s introduction of the Liquid Glass interface style became a litmus test for cross-platform frameworks. Skip, by adopting a “fully native” strategy (using native SwiftUI on iOS and mapping to Jetpack Compose on Android), automatically supported the new interface on day one without requiring rewrites or workarounds. In 2026, Skip plans to continue expanding integrated frameworks, optimizing the Skip Fuse toolchain, and improving performance and developer experience.
How to use Claude Code
This is a practical guide compiled by Khoa Pham after months of intensive Claude Code usage. Core tips include detailed application scenarios for various modes, especially how to use Extended Thinking mode judiciously to avoid wasting tokens. It also covers essential keyboard shortcuts, context management techniques, MCP integration, VS Code and Chrome extensions, GitHub Actions integration, Git Worktrees parallel workflows, plugin ecosystem, and prompt best practices. The content is detailed, specific, and targeted—not just a simple feature introduction manual.
App Store Connect API Webhook｜Automate CI/CD Workflows Seamlessly
Apple announced the App Store Connect API Webhook at WWDC 2025, supporting real-time push notifications for build status, app version status, TestFlight feedback, and other events. Zhong Cheng addresses the pain point of traditional polling methods requiring approximately 20 minutes of waiting after build uploads (wasting $1.24 per GitHub Runner instance), providing detailed instructions on applying this capability in CI/CD to achieve zero waiting costs; GitFlow merge-back timing can precisely align with actual app release time; developers can receive timely rejection notifications even with limited permissions.
Setting up Embedded Linux with WendyOS
WendyOS is a Linux distribution designed for embedded devices, written in Swift, aiming to bring the convenience of iOS development to the embedded domain. Joannis Orlandos provides a complete getting-started tutorial in this article: from installing Homebrew and Wendy tools, flashing WendyOS to devices like Raspberry Pi/Jetson Orin Nano, connecting devices via USB, configuring WiFi, creating Swift projects (including wendy.json permission configuration), to using VSCode extensions for remote debugging (supporting breakpoints and state inspection). Suitable as an introductory tutorial for developers wanting to apply Swift to embedded devices or IoT scenarios.
Tools
Fucking Approachable Swift Concurrency
This is a learning resource created by Pedro Piñera, based on Matt Massicotte’s Swift concurrency concepts, explaining core concepts like async/await, Task, Actor, and Sendable in an approachable way. Pedro uses an “Office Building” scenario to build intuitive mental models: comparing MainActor to a reception desk, actors to department offices, and await to knocking and waiting. Additionally, it provides a Skill.md file suitable for AI tools, allowing developers to directly embed these concurrency practices into their development workflow’s rule engine.
Dimillian’s Skills - iOS/Swift Development AI Agent Skills Collection
A Skills repository for iOS/Swift development created by Thomas Ricouard, containing six AI Agent Skills focused on practical workflows. Covers App Store Changelog generation (automatically generating release notes from git history), iOS Debugger Agent (building/debugging iOS projects using XcodeBuildMCP), Swift Concurrency Expert (fixing Swift 6.2 concurrency issues), SwiftUI Liquid Glass (implementing iOS 26+ Liquid Glass API), SwiftUI View Refactor (refactoring view structure and dependency patterns), and SwiftUI Performance Audit (reviewing performance bottlenecks and providing optimization recommendations).
StoreKit Helper - SwiftUI In-App Purchase Wrapper Library
A lightweight StoreKit 2 wrapper library developed by jaywcjlove, designed specifically for SwiftUI, greatly simplifying in-app purchase implementation. Compared to using the StoreKit 2 API directly, StoreKitHelper reduces approximately 70% of boilerplate code, making it particularly suitable for SwiftUI developers who need to quickly integrate in-app purchases without dealing with underlying complexity.
Core features include: @ObservableObject-based state management, protocol-driven type-safe product definitions, real-time transaction monitoring and automatic state updates, and built-in StoreKitHelperView and StoreKitHelperSelectionView UI components. Interface display can be easily controlled through hasNotPurchased/hasPurchased properties, supporting fluent API configuration for various purchase popup callbacks.
Jobs
macOS Systems Engineer
Photon is building open-source SDKs that let developers bring AI agents to interfaces that 99% of the world already knows how to use - iMessage, WhatsApp, phone calls, Discord, Signal, and more. On top of that, we’re building open-source Agent SDKs focused on interaction - things like multi-part messages, threading, reactions (Tapbacks), etc - so developers and enterprises can ship agents that actually feel human.
We are hiring a macOS Engineer. The ideal profile includes:
- Deep understanding of macOS internals and how system components interact
- Experience with macOS system analysis and debugging
- Hands-on experience working with system-level APIs and low-level mechanisms
- Strong curiosity and passion for exploring the undocumented side of Apple services
- (Optional but a plus) Experience with iMessage, IMAgent, or related messaging infrastructure
We offer competitive compensation (US-based, remote-friendly). Photon is backed by top-tier investors.
Contact: ryan@photon.codes
This is a job posting from Photon, a friend’s startup team. They’re building infrastructure for AI Agents on platforms like iMessage/WhatsApp—it’s an early-stage project. If you’re interested in macOS low-level technologies and early startup opportunities, feel free to check it out.