OpenAI Agents SDK

The Agents SDK's real value is the boring middle layer. Most teams building a multi-agent product spend the first month wiring up handoffs, retry logic, session history, and some way to see what the model actually did. This framework ships those: Agents as LLMs configured with instructions, tools, guardrails, and handoffs; a single Runner to execute them; Sessions for automatic conversation history across runs; and built-in tracing you can inspect in the OpenAI dashboard. That is a genuine head start, not a wrapper around a chat endpoint. The four run modes are the part buyers underrate. Text agents cover ordinary request/response flows. Sandbox agents put the agent in a container so it can inspect files, run commands, apply patches, and keep workspace state across long-horizon tasks — that is the code-review and repo-exploration use case handled natively. Realtime agents run over WebSocket on gpt-realtime-2.1 with the full agent feature set for low-latency voice. Voice pipelines chain speech-to-text, an agent workflow, and streaming text-to-speech when you want more control over each stage. The trade-off between the last two is control versus latency, and having both in one SDK saves you a second dependency. Where it is thin: it is designed around OpenAI. It works with other providers through LiteLLM, but you should expect tracing quality and the Realtime integration to be OpenAI-first. There is no durable-runtime story either — agents are stateless between runs unless you wire persistence yourself, which makes the optional Redis sessions or your own store your problem. Memory, evals, and deployment tooling are all yours to bring. The API is still evolving, so pin your version and read the changelog before a minor upgrade; and remember the framework is $0 but your model provider bills tokens separately, which for agent-heavy iteration with retries and multi-step handoffs can dwarf any framework you might have paid for. Fit it to greenfield Python agent products where OpenAI is already the model of choice and you want handoffs, guardrails, sandboxed execution, and tracing without adopting a graph DSL. A 2026-08 cross-vendor agreement on a common standard for AI agents may widen interoperability with third-party agent tooling later, but do not plan on it today.