Manage AI Task Execution for the Agentic Era
Shift from simple prompting to managing autonomous AI agent workflows.
Adopt an 'agentic' mindset by structuring prompts that allow the AI to plan and execute multi-step processes with minimal manual intervention.
The Scenario
You are managing a long-term research or data processing task that involves multiple distinct steps and decision points.
Before & after
Managing multi-step AI workflows manually requires constant prompting and checking of each individual output, often taking 60–90 minutes for complex workflows.
Using an AI agent framework, you can set the goal and let the model navigate sub-tasks, reducing your oversight time to 10–15 minutes of review.
The Prompt
I want to treat this interaction as an agentic workflow. My goal is to [DESCRIBE END GOAL]. Please break this down into 5 autonomous steps, execute the first step of research, and then ask for my approval before proceeding to the synthesis step.
As the industry moves into the 'agentic era,' managing how and where you deploy AI requires a focus on autonomous task completion rather than just chat.
Source
OpenAI News | OpenAI"How to manage AI investments in the agentic era."