This workflow describes an A2A agent pattern where your orchestrator agent receives user input, fetches metadata from remote agents (which may be your agents or 3rd-party agents, via A2A Agent Cards), and dispatches tasks to those remote agents using A2A protocol methods.
Each task supports streaming updates and may result in dynamic content (e.g., text or images) rendered back in your orchstrator agent's user interface or notification service.
The workflow ends after gathering final responses from remote agents and rendering them to the user.
You care about improving the entire lifecycle of buyer and customer journeys. And you want inspiration for areas where Ai may help.
You want inspiration for real-world ways to help people as you're building your Ai product.
You're focused on the stage in your daily job and want to find ways for Ai to help you do more with less.
Does this AI agent workflow rely too much on AI and not enough on human know-how? Or the reverse? Is it missing steps or tools?
Note that this Ai workflow is presented as inspiration for what's possible. Adjust the amount, type and quality of the data inputs. Adjust how much or how little your human team mates (or you), AI and fully autonomous agents contribute.
And test it! Learn what works and what doesn't.
Don't forget! In the end, it's not just about efficiency. It's about delivering great experiences for your customers and customers-to-be.
Craft an Ai automation or agent plan, just for your b2b. Simple. The first step in automating across your buyer and customer journeys: inspiration for what to build. Talk with an Ai agent via your phone to quickly create your custom Ai agent plan.