Proactive iOS Digital Assistant
Inspired by upcoming AI features in iOS 27, this challenge involves building a prototype of a proactive digital assistant that leverages GPT-5 for advanced reasoning and LangGraph for complex, stateful workflows. The assistant will utilize the A2A Protocol for seamless agent-to-agent communication, enabling specialized agents to collaborate and provide personalized, context-aware assistance across simulated iOS applications and services. Participants will design a graph-based multi-agent system where different 'service agents' (e.g., Calendar Agent, Messaging Agent, Smart Home Agent) interact using A2A Protocol, orchestrated by a central 'Proactive Assistant Agent'. This system should anticipate user needs, suggest actions, and execute tasks across simulated device functionalities, demonstrating a cutting-edge approach to on-device AI integration and user experience.
What you are building
The core problem, expected build, and operating context for this challenge.
Inspired by upcoming AI features in iOS 27, this challenge involves building a prototype of a proactive digital assistant that leverages GPT-5 for advanced reasoning and LangGraph for complex, stateful workflows. The assistant will utilize the A2A Protocol for seamless agent-to-agent communication, enabling specialized agents to collaborate and provide personalized, context-aware assistance across simulated iOS applications and services. Participants will design a graph-based multi-agent system where different 'service agents' (e.g., Calendar Agent, Messaging Agent, Smart Home Agent) interact using A2A Protocol, orchestrated by a central 'Proactive Assistant Agent'. This system should anticipate user needs, suggest actions, and execute tasks across simulated device functionalities, demonstrating a cutting-edge approach to on-device AI integration and user experience.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
What you should walk away with
Master LangGraph for building stateful, cyclic DAG agent workflows, allowing complex decision-making, re-planning, and dynamic agent activation.
Implement A2A Protocol for robust, secure, and asynchronous agent-to-agent communication, enabling specialized 'service agents' to collaborate within the assistant system.
Utilize GPT-5 for the central 'Proactive Assistant Agent' to interpret complex user requests, infer intent, and predict future needs based on context, employing adaptive thinking budgets.
Design and integrate simulated iOS APIs (e.g., calendar, reminders, messaging, location services) as tools that agents can autonomously invoke.
Build specialized agents (e.g., 'Calendar Agent', 'Messaging Agent', 'Location Agent') that communicate via A2A Protocol and manage specific simulated iOS services.
Orchestrate dynamic agent teams using OpenAI Swarm principles for complex tasks, where the 'Proactive Assistant Agent' can dynamically assemble and coordinate specialized agents to fulfill user requests or proactively offer assistance.
[ok] Wrote CHALLENGE.md
[ok] Wrote .versalist.json
[ok] Wrote eval/examples.json
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