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Program On-Ramp: Vision, Mindset, and the Agentic Product Lifecycle

From Backlog Managers to System Orchestrators: Your New Role in the Agentic Era

The Agentic Product Lifecycle: Discovery to Go-To-Market with Autonomy at the Core

Core Stack and Setup: CrewAI, LangGraph, and OpenAI Assistants API

Market Discovery with Autonomous Research Crews

Spin Up a Research Crew: Multi-Agent Competitive and Customer Intelligence

Hands-On Lab: CrewAI-Powered Market Scanner and Opportunity Mapper

Quiz: Discovery Crews and Market Intelligence Automation

Ideation, Concept Validation, and Opportunity Shaping

From Signals to Concepts: Agentic Ideation and Prioritization at Scale

Hands-On Lab: Concept Generator with Red-Team and Customer Proxy Agents

Quiz: Ideation Orchestration and Validation Signals

Planning and Roadmapping with Autonomous AI Teams

Agentic Sprint Planning: From Outcomes to Executable Work

LangGraph Blueprints: Reliable Multi-Step Plans and Human-in-the-Loop Gates

Quiz: Agentic Planning Patterns and Governance

Design, Prototyping, and Technical Enablement

From PRD to Prototype: Assistants API as Your Design Partner

Hands-On Lab: Spec-to-Sketch to Clickable Prototype with Agents-in-the-Loop

Quiz: Prototype Orchestration and Design QA

Delivery Automation: Build, Test, and Release with Agent Crews

Coding with Confidence: Dev Crews, Guardrails, and CI Observability

Hands-On Lab: LangGraph Release Conductor for Incremental Delivery

Quiz: Delivery Crews, CI/CD Integration, and Risk Controls

Go-To-Market, Growth, and Revenue Engines with Agents

Autonomous GTM: Positioning, Pricing, and Channel Experiments at Speed

Hands-On Lab: Launch Coordinator Crew for Campaigns, Demos, and Sales Enablement

Quiz: GTM Orchestration and Launch Excellence

Safety, Compliance, and Stakeholder Trust

Building Responsible Agentic Systems: Policy, Privacy, and Auditability

Hands-On Lab: Guardrails Playbook with CrewAI and Assistants API

Quiz: Safety-by-Design in Agentic Workflows

Measurement, Economics, and Scaling the Operating Model

From Tasks to Systems ROI: Measuring Impact and Agent Unit Economics

Platform Patterns: Reusable Crews, Templates, and Internal Marketplaces

Quiz: Metrics, Cost Controls, and Scale Patterns

Capstone: Launch an AI-Powered Product or Agentic Workflow

Capstone Sprint 1: Define Problem, Success Metrics, and Agent Roles

Capstone Sprint 2: Build, Orchestrate, and Validate

Capstone Sprint 3: Ship, Measure, and Tell the Story

Certification and Knowledge Checks

Quiz: Agentic Product Lifecycle Foundations

Quiz: CrewAI Patterns and Role Design

Quiz: LangGraph Orchestration and Control

Quiz: OpenAI Assistants API Tools and File Search

Quiz: Market Research Automation and Synthesis

Quiz: Ideation Scoring and Validation Loops

Quiz: Planning, PRDs, and Story Generation

Quiz: Prototyping, UX QA, and Accessibility

Quiz: CI/CD, Rollbacks, and Release Notes

Quiz: GTM Experiments, Messaging, and Enablement

Quiz: Safety, Red Teaming, and Compliance

Quiz: Metrics, Cost, and Scale Playbooks

Program Close: Portfolio, Next Steps, and Feedback

Your Agentic Portfolio: Evidence, Demos, and Narratives for Stakeholders

Program Survey: Help Us Improve and Scale Impact

Agentic Product Leadership: Orchestrating Autonomous AI Teams from Idea to Launch is a practitioner-led program for product leaders who need to ship faster, reduce risk, and scale impact with autonomous AI. You’ll learn how to transition from backlog manager to system orchestrator, using CrewAI, LangGraph, and the OpenAI Assistants API to coordinate multi-agent workflows across the entire product lifecycle. Through a blend of strategy, hands-on labs, and governance best practices, you’ll build research crews that scan markets, ideate and score concepts, auto-generate PRDs and prototypes, integrate with CI/CD, and run GTM experiments—safely and measurably. The course emphasizes human-in-the-loop gates, observability, and guardrails so your teams can trust, audit, and continuously improve agentic systems. By the end, you’ll complete a capstone that launches a real AI-powered product or workflow, backed by telemetry, ROI analysis, and stakeholder-ready narratives. If you’re a PM, founder, or operator ready to harness autonomy, this course provides the operating model, patterns, and tools to lead in the agentic era.

Agentic Product Leadership: Orchestrating Autonomous AI Teams from Idea to Launch

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            <p>In the not-so-distant past, product leaders moved cards across boards and shepherded teams through rituals. Then autonomous AI crews arrived—agents that research markets overnight, spin up prototypes by morning, and coordinate releases before lunch. Agentic Product Leadership: Orchestrating Autonomous AI Teams from Idea to Launch is your playbook for this new era. It reframes the role from backlog manager to system orchestrator, equipping experienced PMs, founders, and product ops leaders to design, govern, and scale agentic systems that move from signal to shipped product with precision. You’ll adopt the Agentic Product Lifecycle—market sensing, opportunity shaping, solution design, delivery, growth, and GTM—where human judgment sets direction and AI agents execute with speed, safety, and accountability.</p>

<p>The journey begins by resetting your mindset and tooling. You’ll compare CrewAI, LangGraph, and the OpenAI Assistants API, provision environments, and wire up observability so that every decision is traceable. From there, discovery shifts from manual digging to orchestrated research: Analyst, Synthesizer, Contrarian, and Verifier agents triangulate sources, reduce bias, and export decision-ready briefs. Ideation scales through generator-critic loops, persona simulations, and automated RICE and cost-of-delay scoring to create an evidence-linked opportunity backlog. Planning becomes agentic sprint design—Planner, Architect, Risk, and Scope-Guard agents transform outcomes into specs, stories, and PRDs with human-in-the-loop gates and LangGraph blueprints to keep plans reliable and auditable.</p>

<p>Design and prototyping accelerate as Assistants API agents generate flows, wireframes, and copy variants while paired UX and accessibility critics refine quality. In delivery, code-gen crews ship with guardrails, tests, and CI telemetry; a LangGraph Release Conductor manages branches, PRs, canaries, and rollback strategies—complete with automated release notes for stakeholder trust. Go-to-market is treated as an autonomous system: agents craft positioning and pricing tests, coordinate campaigns, and feed attribution insights back into the roadmap. Throughout, safety and compliance aren’t bolt-ons—they’re designed in with red teaming, injection defenses, sandboxing, approvals, and audit trails that satisfy policy and model risk standards.</p>

<p>Because what scales must be measured, you’ll establish unit economics for agents—latency, quality, and cost per decision—run shadow pilots, and benchmark impact across APL stages. Platform patterns turn your best crews into reusable templates and marketplace assets, enabling permissioned, versioned adoption across your org. The capstone ties it all together: define a real problem, draft agents and guardrails, build with CrewAI, LangGraph, and the Assistants API, pilot with human oversight, then ship, measure, and narrate outcomes to stakeholders. Quizzes and knowledge checks along the way sharpen your mastery, while the closing portfolio module helps you assemble briefs, graphs, metrics, and demos that translate into business value—and your next 90-day adoption plan.</p>

<p>If you’re ready to lead AI-first initiatives—not by adding more meetings, but by composing resilient systems—this program gives you the patterns, tooling, and governance to orchestrate autonomous AI teams from idea to launch. You’ll exit not just fluent in frameworks, but confident in operating an agentic product model that delivers faster cycles, tighter feedback loops, and compounding strategic advantage.</p>
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