AI workflows help OpenEdge developers turn single AI prompts into reliable multi-step processes using structured inputs, validation, tools, and control logic to safely integrate generative AI into real-world applications.
This blog argues that OpenEdge can serve as the trusted operational backbone for production AI by securely integrating an AI “coffee‑buying” agent with live ERP data (via PAS for OpenEdge) and captured human expertise to deliver fast, controlled, actionable decisions without replacing core systems.
This blog post explains modern GenAI concepts for OpenEdge developers—how models work (and differ by purpose), why prompting and token limits matter, how RAG grounds answers in your real documentation, and how assistants differ from agents that use tools to iterate toward a goal.
This post introduces GenAI concepts for OpenEdge developers and proposes a safety-first approach where AI helps with language-heavy tasks (explain/summarize/draft/extract) while OpenEdge remains the system of record for validation, business rules, and transactions.
Progress Agentic RAG, paired with the OpenEdge MCP Server, helps OpenEdge-based ISVs unlock and reason over decades of structured and unstructured application knowledge through secure, governed AI actions—delivering fast, grounded insights without rewriting trusted code.