Openai

The OpenAI Responses API replaces the Assistants API with a simpler, more flexible architecture for building AI agents. It eliminates threads by using previous_response_id to maintain conversation context, supports stateless instructions, and improves tool usage through built-in integrations like file search, web search, and code execution. Developers benefit from strong TypeScript support, easier state management, and new features like vector stores with batch uploads and metadata. Migration is straightforward and preserves existing functionality, while paving the way for future enhancements. With OpenAI planning full feature parity and eventual deprecation of the Assistants API, switching now ensures long-term compatibility.

The blog compares OpenAI’s Responses API and Assistants API for tool-using AI agents. Responses API offers fine-grained control with manual orchestration, ideal for flexible, low-level implementations. Assistants API provides a structured, high-level framework with built-in state management and easier tool chaining, simplifying development at the cost of reduced flexibility.

OpenAI, Anthropic, xAI, and Google offer similar API-level tools for their LLMs, focusing on structured tool usage like function calling, web search, file handling, and code execution. While OpenAI provides built-in tools (web search, file search, code interpreter), Anthropic emphasizes client/server tool use distinctions, including editing and execution tools. xAI’s Grok prioritizes real-time web data integration. Google’s Gemini supports extensive custom integrations via function calling within Vertex AI.

The AI SDK with Zod offers a higher-level, type-safe development experience ideal for most use cases where the set of tools is known and relatively small-to-medium. The native OpenAI API offers maximal flexibility and control with minimal overhead, which can be important in certain scenarios.