OpenAI Users Build Agent Workflows

The hot take: OpenAI’s value is shifting from “answer machine” to workflow engine. The people getting meaningful ROI are wrapping models in state, tools, logging, and guardrails instead of treating prompts as the product.

• –The strongest use cases are narrow but high-frequency: email triage, screening, summaries, and repeatable ops tasks.
• –“Thinking partner” agents are useful for planning, but the more durable wins come from execution, not advice.
• –The comments reinforce a basic rule: start with one bounded workflow, add logging, and expect retries and failures.
• –Discord and small-business ops keep coming up because they already live in messy, tool-heavy environments where agent orchestration can save real time.
• –This is less about better prompt craft and more about building reliable systems around model calls, which is where OpenAI’s tooling matters most.