Learn how to leverage Google's Gemini Batch API to add powerful background AI processing to your Swift applications. Perfect for developers using Firebase or Supabase who need to process large datasets asynchronously over hours or days without blocking user interactions. We'll walk through the complete lifecycle of creating batch requests, monitoring their progress, and handling results - all using Swift! You'll receive a fully functional Swift monitoring app at the end of the workshop to track your batch requests in real-time and integrate batch AI processing into your existing applications.

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​Discover how to use the FoundationModels framework to create truly reactive applications where users can configure app settings using natural language commands. Watch as we build a demo app that dynamically transforms its UI based on typed user preferences - from changing themes and layouts to adjusting functionality, all through conversational interaction. All code will be provided at the end of the workshop, so you can run it at your own pace whenever you are ready to upgrade to macOS Tahoe.

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Building apps with LLMs can be challenging because we, as developers, can't predict exactly what each user will see and must guard against factually-incorrect hallucinations that erode trust. To tackle this, we can set up evaluations - quantitative and qualitative tests that measure “correctness” or other desired outcomes of model outputs. By running those evaluation pipelines across multiple LLMs, we can compare metrics like accuracy, latency, and instruction-following to pick the best model for our app. In this workshop, you'll learn concrete techniques in Swift for building reusable, automated evaluation pipelines so you can quickly test and swap out models as your needs evolve.

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OpenAI has recently introduced the Responses API, a powerful new re-design of the Chat Completions API, optimized for building AI agents capable of independently performing complex tasks. In this workshop, we'll explore the strengths and weaknesses of the Responses API, and understand how—and when—to use it effectively. Most importantly, we'll dive into the built-in tools, including web search, file search, and computer use. All in Swift!

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This workshop is designed for Swift developers who are ready to begin integrating AI into their application. We'll focus on OpenAI's Chat Completions API, a powerful interface that has become the industry standard for interacting with Large Language Models (LLMs). You'll learn how to utilize this API not only to build chat applications but also to enhance other user interactions subtly with AI-driven features. Additionally, the workshop will cover techniques for incorporating images, files, and tools into your API requests, enabling functionalities like image analysis and file-based interactions. By the end of this session, you'll have a solid foundation to start building your AI-powered Swift app.

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The newly-released OpenAI Agents SDK offers a clear, organized way to build AI agents. In this workshop, you'll explore the Swift SDK version to create AI systems that follow custom instructions, perform smooth handoffs between agents, and include built-in safety checks. These techniques help you turn complicated workflows into simple, automated tasks, giving you practical skills to enhance your app development and build smart, AI-powered solutions.

Please note that while this workshop shares similarities with our other AI Agents in Swift sessions below, it places a stronger emphasis on understanding the unique terminology and hands-on implementation of the OpenAI Agents SDK.

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Discover how to integrate Google's new cutting-edge Gemini 2.0 Flash (Image Generation) Experimental model into your Swift projects! In this workshop, you'll learn to edit user photos with simple natural language prompts. Add or remove people, adjust room elements, change outfits, generate a professional passport photo, and much more — all without Photoshop. Then, enhance the edited image and transform it into a fun mini-video.

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Learn how to build an AI agent in Swift that converts PDFs into engaging, podcast-style audio content. Through this example, you'll gain practical skills that can be applied broadly to build advanced agent-based systems in your iOS and macOS applications.

Note: This workshop builds upon the previous session, “Introduction to AI Agents: Navigating LLM Workflows in Swift”. To get the most out of this workshop, you can purchase access to that recorded session below.

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You might have heard that 2025 is being hailed as the year of AI Agents. But what exactly are they? At their core, AI agents are intelligent systems that leverage large language models to autonomously perform tasks.

In this workshop, we'll cut through the hype and dive into practical, real-world LLM workflow patterns that you can integrate into your Swift applications. By the end of the session, you'll have the skills to design, implement, and optimize AI agent workflows, empowering you to build new app interfaces that were impossible before.

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In this workshop, you'll learn how to bring voice to life in your Swift apps using AI. Explore key techniques including:

• Transcribing user audio into actionable text with AI-powered speech recognition.

• Generating natural, engaging audio responses using AI.

• Leveraging function calling to process user commands, extract user data, and trigger meaningful actions.

By the end of the session, you'll have the skills to build a fully interactive, voice-powered app using AI in Swift.

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This introductory workshop is designed for Swift developers eager to kickstart their journey into building apps powered by Large Language Models (LLMs). You'll gain a solid understanding of how LLMs work, explore their limitations, and learn practical techniques to overcome these challenges. We'll also examine various products and APIs that you can leverage to start building LLM-powered apps right away.

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