Articles

5 automation Prompts for GPT-5.4 — Copy-Paste Ready for Enterprise DeploymentsThe Complete Guide to ChatGPT’s New Custom GPTs Interface: How the Updated Plugin Menu, MCP Connectors, and Action Icons Transform Enterprise AI WorkflowsHow Enterprise Dev Orgs Used Gemini 3.1 Pro to Ship Features 10x Faster: A 2026 Case Study In…

Author: Markos Symeonides, ChatGPT AI Hub In 2026, enterprise AI governance is no longer a peripheral compliance exercise. It is an operational discipline that blends risk management, data protection, security engineering, product management, and organizational change. As generative AI systems graduate from isolated pilots to mission-critical platforms powering customer support,…

Production-grade APIs are more than HTTP endpoints. They are carefully modeled contracts with explicit behavior, backed by resilient storage, enforced by authentication and authorization, validated with automated tests, observable in real time, and shipped through repeatable pipelines. This playbook is a practical, technical walkthrough for building RESTful APIs that hold…

DevOps engineers can use conversational assistants to accelerate architecture decisions, codify operational standards, and automate repetitive toil. The 25 prompts below are designed to be immediately actionable in real-world environments. They cover end-to-end CI/CD pipelines, Infrastructure as Code, observability stacks and monitoring dashboards, and incident management. Each prompt provides a…

Modern search systems must deliver high relevance under strict latency and cost budgets, while handling ambiguous, multi-faceted natural language. GPT-5.5 Instant enables a new class of AI-powered search by combining fast intent understanding, robust constraint handling, and structured tool outputs with traditional information retrieval. This guide describes an end-to-end architecture…

Author: Markos Symeonides, ChatGPT AI Hub Overview: This long-form tutorial explains why many teams are moving from the Assistants API to the Responses API, what architectural differences to expect, and provides a step-by-step migration plan that includes complete Python and TypeScript code examples. We’ll cover stateful conversations, file search migration…

In June 2026, OpenAI announced its first in-house AI inference chip—code-named “Jalapeño”—built in partnership with Broadcom. The move marks a strategic shift from reliance on general-purpose accelerators toward custom silicon optimized for large language model (LLM) inference. If executed well, Jalapeño will change the economics of serving multimodal AI, reshape…