Articles

A practical, production-ready prompt collection and playbook for engineers, architects, and SREs using Kubernetes, Docker, gRPC, and Kafka. Each prompt is written to be used with AI coding assistants (Codex-style) to accelerate design, implementation, testing, and operations of resilient microservices. Architecture Design Implementation Testing Operations DevOps engineers implementing the infrastructure…

Use this masterclass to plug high-quality prompts directly into your ChatGPT-5.5 workflow. Each prompt is production-ready, specific, and includes customizable context variables in [brackets] so you can adapt them to your domain, data, and target journals. The prompts are designed to minimize ambiguity, reduce hallucination risk, and produce structured outputs…

By ChatGPT AI Hub • Technical Guide Note on terminology and status: As of the latest public information, “Agent2Agent (A2A)” is used in the industry as a general descriptor for agent-to-agent interoperability patterns rather than a single ratified public standard from Google. This guide uses “A2A” to refer to a…

How to Build Custom AI Agents with OpenAI’s Responses API A practical, end-to-end tutorial for developers: environment setup, a basic agent, tool integration, multi-step reasoning, error handling, and deploying to production with Python examples.

By ChatGPT AI Hub Newsroom • Analysis • Q2 2026 Agentic workflow lifecycle: intent capture → planning → tool invocation → execution → verification → reporting → memory. The shift is visible in telemetry: longer multi-turn sessions, higher share of tool calls per session, and more conversations culminating in file…