MobilePro #213: Working with Claude Code, Swift IDE support, React Native 0.85, and more…

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Welcome to the 213th edition of MobilePro.

AI in development continues to be a growing beast. We’ve moved from asking models for snippets to relying on them across larger parts of the workflow. Unfortunately, that also brings with it new challenges. Sessions get cluttered, context drifts, and outputs become inconsistent. Sure, code gets written faster now, but controlling how AI behaves inside the development process is a concern.

That shift is reflected across this week’s updates. Swift is expanding into AI-friendly editors beyond Xcode. Meanwhile, React Native continues evolving its architecture and benchmarks like Android Bench are beginning to measure how well AI actually performs on real development tasks. At the same time, the idea of an AI coding stack is taking shape; orchestration, execution, and models all work together! That’s why this week’s tutorial focuses on using Claude Code as a structured development environment, and how managing context, memory, and workflows can turn AI from a helpful assistant into a reliable part of your stack.

Before we move to the tutorial, here are some of the key news highlights from this week:

• Swift expands IDE support beyond Xcode to modern editors and AI tools

• React Native 0.85 ships new animation backend and key improvements

• AI coding shifts toward composable multi-tool stacks

• GPT-5.4 and Gemini 3.1 Pro lead Android AI coding benchmarks

Let’s get started!

Getting Started with Claude Code: From Setup to Real-World Workflows

Modern AI-powered development tools are evolving quickly, but getting real value from them requires more than just installation. You need to understand how they behave in practice, how to control them, configure them, and integrate them into your daily workflow.

Claude Code is designed to be more than a coding assistant. It’s a configurable, extensible system that supports long-running development workflows through features like slash commands, memory, hooks, and skills. In this article, we’ll walk through how to move from basic setup to using Claude Code effectively in real-world scenarios.

Controlling Claude Code with Slash Commands

Once inside Claude Code, the primary way to interact with it is through slash commands. These commands give you direct control over sessions, context, and configuration. Some of the most important ones include:

• /clear: Resets the session completely

• /compact: Summarizes the conversation to reduce context size

• /config: Opens configuration settings

• /agents: Manages specialized sub-agents

• /models: Lists available models

As conversations grow, they can become inefficient or confusing, a phenomenon often called context rot. Commands like /clear and /compact help maintain performance and clarity over time. This is where context engineering becomes practical: you’re actively shaping what the model remembers and how it behaves.

Bringing Claude Code into Your IDE

While Claude Code can run in the terminal, most developers use it directly inside their IDE, especially tools like Cursor. Integrating Claude Code into your editor allows you to:

• View code changes in real time

• Work with diffs more effectively

• Keep your workflow centralized

This setup transforms Claude Code from a chat tool into a true development companion embedded in your environment.

Automating Workflows with Hooks

Hooks are one of the most powerful features in Claude Code. They allow you to run automated logic at specific points in the workflow. For example, you can trigger actions before or after a tool runs, when a user submits a prompt, and when Claude finishes generating output.

A simple use case is a notification hook that plays a sound when Claude completes a response. While basic, it demonstrates how hooks can automate repetitive tasks and enforce consistency.

More advanced use cases include running tests automatically, formatting code, blocking unsafe changes, and triggering sub-agents. Hooks are essential for building reliable, repeatable workflows.

Memory: Making Claude Code Persistent

Claude Code isn’t limited to a single session, it can retain structured context across projects using a memory system built around CLAUDE.md files. Here are the types of memory:

• User Memory: Personal preferences across all projects

• Project Memory: Shared rules and context for a specific project

• Organization Policy: Company-wide rules and constraints

These memory files are loaded hierarchically, meaning:

• Global preferences coexist with project-specific rules

• More specific instructions override broader ones

Why Memory Matters

Instead of repeating instructions, you can store them once and reuse them automatically. This improves consistency, efficiency, and output quality. You can even initialize memory automatically using the /init command, which analyzes your codebase and generates a structured context file.

Safe Experimentation with Rewind

AI-assisted coding encourages experimentation, but it also introduces risk. Claude Code addresses this with a built-in checkpointing system. Using /rewind, you can undo code changes, restore previous states, and explore alternative implementations safely. Each prompt that modifies files creates a checkpoint, allowing you to roll back changes without losing progress. This significantly reduces the cost of AI recovery, making development more forgiving and iterative.

Extending Claude Code with Skills

Skills (formerly custom slash commands) allow you to encapsulate repeatable workflows into reusable commands. For example, you can create a skill that reviews changed files, generates a commit message, and executes Git commands. Skills are defined using simple Markdown files with structured prompts. They can also accept dynamic input using placeholders like $ARGUMENTS.

Skills matter because they combine prompt engineering, tool execution, and context control. They enable you to build mini automation pipelines inside Claude Code, tailored to your workflow. For more advanced use cases, you can:

• Restrict allowed tools (principle of least privilege)

• Preload context using system commands

• Combine retrieval and generation

This turns Claude Code into a programmable agent system rather than just an assistant.

Best Practices for Working Effectively with Claude Code

While Claude Code is powerful out of the box, getting consistent and reliable results depends on how you use it. The following best practices will help you avoid common pitfalls and maximize productivity:

• Treat Context as a Limited Resource: Claude Code operates within a context window, so managing what it “remembers” is critical.

  • Use /compact regularly to reduce noise in long sessions

  • Use /clear when switching tasks or domains

  • Avoid dumping unnecessary information into the conversation

• Use Memory Strategically, Not Excessively: Memory is powerful, but overusing it can backfire.

  • Keep md files concise and specific

  • Store only high-value, reusable information (coding standards, workflows, preferences)

  • Avoid vague or redundant entries

• Separate Global and Project-Level Concerns: Take advantage of Claude Code’s layered memory system:

  • Use user memory for personal habits and preferences

  • Use project memory for team conventions and architecture

  • Use local memory for temporary overrides

• Keep Hooks Lightweight and Fast: Hooks run automatically and frequently, so performance matters.

  • Prefer simple shell commands over heavy scripts

  • Avoid long-running processes inside hooks

  • Test hooks independently before integrating

• Validate AI Output Before Trusting It: Even with strong context, Claude Code can make mistakes.

  • Review diffs carefully before approving changes

  • Test generated code, especially in critical paths

  • Don’t blindly accept commits or automation results

• Monitor Costs and Usage (When Using API Keys): If you’re using API-based billing:

  • Check /cost regularly

  • Set usage limits in the Anthropic console

  • Be cautious with multi-agent workflows

Claude Code is not just about generating code, it’s about shaping how AI participates in your development process. By combining slash commands for control, hooks for automation, memory for persistence, rewind for safety, and skills for extensibility you can build workflows that are not only powerful but also predictable and scalable. The real value comes from understanding how these pieces fit together, and using them intentionally.

Claude Code becomes significantly more powerful when you stop treating it like a chat assistant and start treating it like a programmable development environment. The difference lies in how you manage context, structure memory, and design your workflows. Master those, and Claude Code shifts from helpful to indispensable.

If you want to learn more about agent coding, check out Agentic Coding with Claude Code by Eden Marco.

Agentic Coding with Claude Code

🧑‍💻Learn Claude Code as a development partner to build custom automations and agentic workflows.

🛠️ Build and iterate on a Next.js application using Claude Code for AI-assisted development.

🔎 Scale AI-assisted development with Claude Code while maintaining code quality.

This week’s news corner

With that in mind, here are a few updates from the past week that show where mobile development is heading next.

• Swift expands IDE support across modern editors and AI tools: Swift now supports a wider range of IDEs, including Cursor, VSCodium, AWS Kiro, and Google Antigravity, through its official extension on the Open VSX Registry, bringing first-class language features like debugging, refactoring, and test tooling beyond Xcode.

• React Native 0.85 is out: React Native 0.85 has released. This latest version comes with New Animation Backend and moves Jest preset to a dedicated package. It includes several other fixes and improvements including multiple CDP connections, native tabs on macOS, and request payload previews.

• AI coding stacks emerge as next phase of developer tooling: The modern AI coding ecosystem is no longer centered around a single tool but is emerging as a composable stack made up of orchestration (e.g., Cursor), execution (e.g., Claude Code), and model layers (e.g., OpenAI Codex). It highlights a growing need to evaluate and integrate multiple AI tools as part of their core development setup.

• Google updates best AI models for coding Android apps, Gemini & GPT 5.4 at the top: Google has updated its Android Bench rankings, with OpenAI’s GPT-5.4 and Gemini 3.1 Pro now tied as the top AI models for Android app development. The benchmark evaluates models on real Android tasks, though results may vary based on developer workflows and use cases.

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Cheers,

Runcil Rebello,

Editor-in-Chief, MobilePro