PM role has changed with AI. Most product managers have not.

AI for product management is changing what one strong PM can do alone.
But only if you turn the tools into repeatable systems built on your own product.

traditional pm

Traditional PM

Writes docs manually

Depends on specialists for every workflow

Waits for dashboards, research, prototypes, and reporting

Uses AI occasionally for isolated tasks

Works inside one narrow part of the lifecycle

agentic pm

Agentic PM

Builds repeatable systems with AI

Works across discovery, analysis, delivery, and ops

Ships dashboards, prototypes, and workflows faster

Puts agents and structured product context to work daily

Keeps strategy and judgment human while automating execution

HOW IT WORKS

Work on your real product cases

Every session is practical and built on your own product. We keep a tight focus on setting up agentic product management for your context. Your data, your users, your goals. No generic demos. You leave with working systems, not notes.

Setup AI workflows

Build a clear foundation in agentic product management from AI workflows

Leave with an action plan

Turn ideas, tools, and templates into reusable assets and workflows you can keep using

Practice on real cases

Apply each module to practical assignments and product scenarios

agentic PM sprint

4 modules that set up agentic product management for your product

You own the data layer, discover faster, build live dashboards, and ship prototypes with AI. Each module wires up one part of that stack for your product.

Sprint overview

The Agentic PM Sprint runs a simple path from foundations to execution.

AI PM & Content Engineering

Strategy & Discovery

Analytics & Data

Product Delivery

Module 1

AI PM & Content Engineering

You shift from operator to orchestrator. Build a product context and data layer every agent can read, so work compounds instead of starting over each time.

Set up your agentic workspace with Git, MCP servers, and Claude Code, Cursor, or Codex

Structure your product knowledge for LLMs with context repository and prompt library

Build light data pipelines that connect your CRM, analytics, and feedback sources

Key agentic systems:

Product context knowledge base

Data AI agents

Personal prompt and skill library

Module 2

Product Strategy and Discovery

Use AI to find opportunities and pressure test your direction. Judgment stays with you. Your context turns into grounded strategy artefacts in hours, not weeks.

Run competitive landscape scans and PMF survey analysis with AI

Build your ICP and personas from CRM and interview data

Draft OKRs and a Now/Next/Later roadmap from your vision doc

Key agentic systems:

Competitive intelligence agent

ICP and persona synthesis agent

OST and roadmap agent

Module 3

Product Analytics and Data

Design metrics, run experiments, and build live dashboards yourself with vibecoding. Go from question to answer without waiting on a data team.

Define your North Star, HEART, and AARRR metrics and event tracking

Vibecode dashboards with Cursor, v0.dev, and Bolt.new, then automate your weekly KPI report

Build cohort, funnel, and LTV/CAC unit economics analyses

Key agentic systems:

Vibecoded analytics dashboard

Weekly KPI report agent

Unit economics model

Module 4

Product Delivery

Run delivery with AI as your build partner. Prototype, prioritise, and ship launch assets without a designer or engineer in the loop.

Generate PRDs, user stories, and RICE or MoSCoW prioritisation with AI

Vibe design a prototype straight from your PRD with Figma AI, Lovable or v0.dev

Run sprint planning, retrospectives, and changelogs from your team's transcripts

Draft stakeholder updates and 1:1 prep straight from your product log

Set up a product ops playbook and RACI so the team moves without you in every thread

Key agentic systems:

PRD and backlog agent

Prototype agent for vibe design

Stakeholder update agent

AI tools stack

Bring your product context and set up your own agentic PM operating model

You'll leave with a practical AI tools stack set up on your own product. Work with Git, build agents across different tools, and create skills with Claude Code, Codex, Gemini, and Cursor.

Set up your project context and version control on Git

Configure MCP servers and plugins and connect your tools

Configure an agentic development environment in Cursor

Create skills for Claude Code, Codex, or Gemini

Create automation workflows and scheduled tasks

Use agents for full stack engineering and vibe coding

Apply now

Claim your seat to lead products with AI

Two weeks of hands on work gives you a product context base, live dashboards, and shipping prototypes. We run each sprint with a small group only, so seats are limited.