AI PMs Should Start With the Workflow, Not the Model | AI Product Management Design Frameworks Part1

AI PMs should not start with the model.

They should start with the workflow.

In Part 1 of AI Product Management Design Frameworks, I explain why many AI product efforts begin with the wrong question: which model should we use, should we use RAG, should we build an agent, should we fine-tune, or can we automate this?

Those questions matter, but they are not the starting point.

The better starting point is:

What workflow are we trying to improve?

A model is not a product.
A prompt is not a product.
A chatbot is not automatically a product.

A product changes how work gets done.

In this video, I cover:

- Why AI PMs should start with workflow design
- Why model choice should follow product workflow
- How the same AI capability can support different products
- Why support ticket summarization depends on the decision being improved
- How enterprise AI workflows involve systems, records, queues, alerts, policies, audit requirements, and operational consequences
- A practical workflow-first test for AI PMs

The core idea:

Capability is not the same as product value.

Before discussing model choice, AI PMs should ask:

What workflow are we improving?
What decision or action should change?
What context does the system need?
What happens after the model responds?
How will we know the workflow improved?

This is Part 1 of my series: AI Product Management Design Frameworks.

Next video:
AI PMs Must Define the Automation Boundary

#aiproductmanagement #generativeai #productmanagement #enterpriseai #productionai #aigovernance #aiinfrastructure

Видео AI PMs Should Start With the Workflow, Not the Model | AI Product Management Design Frameworks Part1 канала Apurv Gaurav