From model to agent: Equipping the Responses API with a computer environment
OpenAI Blog / 3/11/2026
💬 OpinionDeveloper Stack & InfrastructureTools & Practical Usage
Key Points
- OpenAI documents building an agent runtime that combines the Responses API, the shell tool, and hosted containers to let agents run with files, tools, and persistent state.
- The approach emphasizes secure sandboxing and scalable deployment to support many concurrent agents without data or state leakage.
- The design enables agents to access external tools and resources, enabling more complex tasks beyond prompt-only interactions.
- The articleframes this as a practical step from language models to a full agent platform, outlining architectural tradeoffs in security, tooling, and performance.
How OpenAI built an agent runtime using the Responses API, shell tool, and hosted containers to run secure, scalable agents with files, tools, and state.
Related Articles
Astral to Join OpenAI
Dev.to

I Built a MITM Proxy to See What Claude Code Actually Sends to Anthropic
Dev.to

Your AI coding agent is installing vulnerable packages. I built the fix.
Dev.to
ChatGPT Prompt Engineering for Freelancers: Unlocking Efficient Client Communication
Dev.to

PearlOS. We gave swarm intelligence a local desktop environment and code control to self-evolve. Has been pretty incredible to see so far. Open source and free if you want your own.
Reddit r/LocalLLaMA