Show HN: Multi-Agent AI with OpenAI Agents SDK (Analysts → Statisticians) (www.cognitora.dev)

Developers have released a production-ready integration that pairs OpenAI’s new Agents SDK (the intelligence layer) with Cognitora’s secure sandboxed execution platform, enabling autonomous agents that can both generate and safely run code. Instead of risky local execution or purely hypothetical code snippets, agents use a simple execute_code tool to validate and call Cognitora’s API, which spins up isolated sandboxes with sub‑second cold starts, military‑grade isolation, configurable networking, multi‑language support (Python/JS/Bash), file I/O, and resource limits. The Agents SDK contributes Python‑first agent primitives, multi‑agent handoffs, built‑in tracing, and provider‑agnostic LLM support, letting orchestrators delegate to specialists like statisticians or report writers. This matters because it closes the loop between reasoning and action: agents can iterate—generate code, run it in a safe environment, inspect errors, self‑fix, and produce verified outputs—unlocking real-world apps from autonomous data analysis and financial modeling to multi‑agent research workflows and interactive coding tutors. Key technical takeaways: a minimal async execute_code interface (code, language, enable_networking) returns output or stderr; Cognitora promises <500ms cold starts and typical code runs <2s; full agent loops take ~5–15s; cost per autonomous task is roughly $0.01–$0.05. The repo includes six production examples (stock analyst, live crypto tracker, visualization pipelines, etc.) showing how secure execution enables agentic systems at scale.