Stop Being a Product Documenter and Start Being a "Proto-Manager"

The role of the product manager has long been defined by documentation.

We write PRDs, user stories, and GTM plans. We meticulously detail features before they're built.

What if the future of product management isn't about documentation at all?

What if it's about being a "proto-manager"—an agile, AI-powered architect of a living, breathing product?

The truth is, AI is not here to replace us; it's here to free us.

It's time to stop thinking of AI as a tool for a one-off task and start using it as an integrated system that handles the grunt work, so we can focus on the strategic, high-impact activities that truly drive growth.

If you've already started using AI to draft a PRD or generate a user flow, you've taken the first step. But the real value comes from scaling that initial win into an AI-native operation. Here is a simple, three-phase framework for how to get there.

Phase 1: Measure & Monetise Your Prototype

Your first successful AI workflow is your proof of concept.

Don’t just celebrate it—measure its impact.

* Go Beyond Time Saved:

Did the AI-generated workflow reduce customer support tickets?

Did it speed up your team's design time?

Track tangible metrics like cost reduction, revenue impact, or error rate reduction.

* Get Your Internal Case Study:

Use this first win to build momentum. Gather feedback from the people who used the workflow. Document how it saved time and delivered business value. This becomes a powerful case study you can use to get buy-in from other teams.

By monetising this prototype, you prove that AI isn't just an expense; it’s a strategic asset with a measurable ROI.

Phase 2: Build the AI-Native Pipeline

Once you have a success story, the goal is to make AI adoption repeatable and systematic. This means building a continuous pipeline of opportunities.

* Create a "Friction Log":

Empower everyone on your team to identify and log their most repetitive, friction-filled tasks. This is your backlog. The most valuable AI projects are not the ones you dream up; they're the ones that solve real, daily pain points.

* Use an AI Prioritisation Matrix:

Not every friction point is an AI opportunity. I suggest using a simple 2x2 matrix to evaluate potential projects based on Business Impact and AI Feasibility. Focus on the high-impact, highly feasible opportunities first.

* Democratize Prototyping:

The future of product management isn't a single PM writing a document; it's a team of "proto-managers" all building and testing with no-code AI tools. This accelerates your learning and frees you to experiment at a pace never before possible.

Phase 3: Cultivate an AI-Native Culture

The final phase is about transforming your company's mindset. It’s no longer about using disconnected AI tools; it's about building an integrated system of human and artificial intelligence.

* Shift from Tools to Systems:

The greatest mistake is treating AI as a series of one-off tools. A truly AI-native company builds a cohesive, integrated architecture where AI agents and human teams work seamlessly together.

* Establish a Community of Practice:

Create a space for people to share their AI wins and challenges. This accelerates institutional learning and turns tribal knowledge into a shared asset.

* Maintain Your Strategic Role:

AI can draft a plan, but it can’t build a vision. Your unique value as a product manager lies in understanding the "why"—the deep user empathy, market context, and business strategy that AI cannot replicate.

Embrace this framework, and you'll find that AI isn't a threat to your job; it’s the catalyst that allows you to move from being a product documenter to a true proto-manager, building the future of your company, one intelligent system at a time.