Claude

ChatGPT

LangChain

CrewAI

Microsoft

Sol Farahmand

AI Engineer | 2X Entrepreneur | AI Hackathon Winner

Intro to Multi-Agent Fundamentals Using CrewAI

MindStudio

Lovable

AI Hackathon Winner | 2X Entrepreneur | AI Workflow Builder

Learn to define a CrewAI agent using role, goal, backstory, LLM, and tools so it knows what job it owns.

Understand agents, the brains behind the operation

Learn to build a task with description, agent, expected_output, and context so the result is predictable.

Write tasks that tell agents what to deliver

Learn to use the crew as the container that brings your agents and tasks together and actually runs them.

Assemble a crew that runs agents and tasks

Learn to pick the right processing mode and see how design patterns map to how your crew executes work.

Run crews sequentially, concurrently, or hierarchically

Learn to connect multiple agents, tasks, and a crew into one run where agents hand off work to each other.

Build a working multi-agent crew end to end

Build AI Agent Skills that Actually Work - 3 Hours Hands-on Workshop

Product Leader and Super IC at Google

Google

Disney+ Hotstar

Zynga

Anshumani Ruddra

Product Super IC at Google with 22+ years crafting experiences and blockbuster products

Cohort 07

Cohort 08

Most product builders use AI agents the same way they used search - typing queries and hoping for the best. That's leaving most of the value on the table.The teams pulling ahead aren't using better prompts. They're teaching their agents. Agent Skills are reusable, testable instruction sets that tell AI agents exactly how to handle specific workflows: your deployment process, your code review standards, your team's edge cases. Write one skill well, and every agent on your team benefits from it, every time, automatically.The problem: nobody is teaching product builders how to create them. Most documentation is written for a narrow technical audience, and the tooling is fragmented across Claude Code, Codex, and Gemini.In this hands-on workshop, you'll go from zero to a working skill installed in your own agent: one that reflects your real workflows, not generic templates. You'll also learn how to evaluate and improve skills systematically, so they get better over time instead of drifting.If you build or are hoping to build products with AI agents: this is the highest-leverage skill you can develop right now.

🤖 Learn to build procedural Agent Skills, transforming your professional mindset from solo prompter to manager of elite AI agents

Shift to an AI Management Mindset

Build Custom, Reusable Agent Skills

Leverage the Open-Source Ecosystem

Evaluate and Iterate for 10x Output

Product Managers: who use Claude Code or Codex daily but rely on ad-hoc prompts - and want repeatable, team-shareable AI workflows.

Entrepreneurs &amp; Founders: building AI-native products who need their agents to encode business logic, not just generate code on demand.

Tech Executives &amp; Product Leaders: who want their teams to stop reinventing prompts and start shipping a shared skills library.

The Conductor's Playbook: the six moves you'll own by the end. The tools change every few months; these are what you keep.

18 AI Products · 50,000+ Students

Apple

Nathan Wang

Founder of AI-Nate, a one-person company run by 30+ AI agents | 18 products in 18 weeks | PhD, Apple & Meta

AI Superpower Cohort 3

AI Superpower Cohort 4

Is this you?• You have watched 50 AI demos and built nothing you can point to.• You are stuck in endless ChatGPT threads instead of putting agents to work while you sleep.• Your team still does by hand what agents should be doing, and you are expected to have the answer.• You want something of your own, but "raise money, hire a team" feels like the wrong decade.The problem is not AI, and it is not you. Nobody taught you to conduct it.One person directing an agent crew can now do what used to take a team. True inside a company, for a consulting practice, or for a product of your own. The bottleneck was never ambition. It was headcount, and agents just removed it.In 4 weeks you build one real AI agent product, genuinely yours, on your own domain. Not a demo. Take it to work, show clients, or seed your own company.The skill outlasts the tool. ClawBot, Claude Code, whatever ships next, all just instruments. What you keep is the Conductor’s Playbook: how to brief, staff, and run a crew of agents toward an outcome, across Product, System, and Business.Cohort 4 is capped at 10. 6 seats are open. Doors close Sep 20.🚨 <a target="_blank" rel="noopener noreferrer nofollow" href="https://maven.com/ai-nate/ai-superpower/4/join?promoCode=EARLYBIRD">Self-funding? Code EARLYBIRD takes 20% off through Sun Sep 6.</a>

Your AI agent crew builds. You conduct. At work, or on your own product.

Conduct, Don't Do: Build a Product People Actually Want

One Job Per Agent: Master AgentOS From First Principles

Brief Before Build: Run It as a One-Person Company (OPC)

Ship Ugly, Ship Daily: A Real Product on Your Own Domain

The Handoff Is You: Orchestrate a Crew That Hands Off Work

Give It a Heartbeat: Agents That Run on Their Own Loop

Professionals Who Lead AI at WorkPMs, engineers, and team leads: ship a real agent product and bring the playbook back to your team.

Domain Experts &amp; EducatorsCoaches, professors, consultants: turn what you know into an AI product built by a crew, no engineers required.

Founders &amp; Side-BuildersLaunch your own product and run it as a one-person company: agents do the work, you own the outcome.

Lead a team that uses Agentic AI fast — with the standards, accountability, and readiness to keep quality high.

AI Advisor · Executive Trainer · Author

Andreas Welsch

AI Advisor | Executive Trainer | 2x Best-selling Author

Join this inaugural cohort and start leading AI-ready teams!

Inaugural Cohort

Most teams are producing more with AI and trusting it less. Drafts pile up, ownership blurs, and "good" becomes whatever ships. The hard part is leading how people use AI tools and agents. In this cohort course, Andreas Welsch gives business and technology leaders a practical system for building AI-ready teams that move fast without sacrificing quality or accountability. Across three working sessions, you will set clear standards for when and how to use AI, decide what to delegate to agents and what stays with people, build accountability into everyday work, and run the change so adoption sticks. You will leave with a team operating model you can put to work the next morning..Join the inaugural cohort! .Note: To test the possibilities and limitations of AI, Andreas produced this course with the help of AI tools (scripting, video generation, voice cloning, and post-production). Each video follows the same didactic best practices that you will find in Andreas' LinkedIn Learning courses. Each script has been thoroughly reviewed and adjusted to convey the lesson's key information. Each office hours session provides an opportunity to connect and get practical insights in real-life.

Your team produces more with AI and trusts it less. This course fixes that.

Set clear standards for when and how your team uses AI

Decide what to delegate to AI agents and what stays with people

Build a complete, accountable AI agent using the six-dimension Operating Model

Business and technology leaders accountable for what their teams produce with AI.

Leaders under pressure to show AI productivity gains without sacrificing quality, accountability, or trust.

Team leads who want to set clear standards and empower their people to use Agentic AI well.

See your venture clearly, find what is holding it back, and choose the next move—so AI creates leverage instead of more work.

Systems Architect · Founder, Sysdom AI

THE WORLD BANK GROUP

Carnegie Mellon University

Han Kay

Systems Architect · Carnegie Mellon (MISM) · Triple Master's (MBA, MS) · 30+ yrs

Cohort 1

AI gives founders two possible futures. It can multiply company capacity—or multiply the coordination work returning to the founder. If you're building an AI-native or agentic company, adding agents is the easy part. The harder problem is turning their output into leverage without becoming the integration layer for every handoff, decision, and next move. The missing layer is the system the agents operate inside. That is Systems Intelligence.This four-week working lab turns Systems Intelligence into founder practice. Across four focused 90-minute sessions, you will map your venture, identify the active constraint beneath the surrounding noise, commit one bounded next move, and complete a founder-directed operating cycle.Sysdom.ai is the included, supported working environment. It organizes venture context across the Product/Service, Customer, Cash, and Skills Engines, preserves evidence, and records the chosen move. You remain responsible for direction, consequential decisions, and approval boundaries.Leave with a clearer venture state, explicit decision boundaries, one completed cycle, and a repeatable way to increase agent capacity without increasing founder coordination.

AI amplifies everything. Including what’s broken.

See your venture as one system

Build an evidence-backed venture map

Find the constraint behind the noise

Choose one bounded next move

Set founder and agent decision boundaries

Start a guided operating cycle

Bring research, a prototype, operating signals, prior decisions, or a serious plan. No website, revenue, or technical setup required.

Bring one real venture—and some evidence

Founders building a venture who feel complexity outpacing their mental model. You have pieces but no unified operating system.

Founders who hit their first real bottleneck and realized working harder isn't solving the structural problem underneath.

Founders whose AI tools and agents produce more output while every important decision and handoff still routes back through them.

Agentic AI

Coding with AI

AI Workflows

Claude Code

OpenClaw

Vibe Coding

AI Evals

AI Transformation

RAG & Search

AI for PMs

AI for Engineers

AI for Designers

AI for Marketers

AI for Founders

Product Sense

Product Discovery

User Research

Prototyping

Growth

Analytics

Tech Foundations

Strategy

Influence

Leadership

Career Growth

Machine Learning

LLM Ops

Context Eng

Security

System Design

Figma

Design Systems

Visual Design

Design Strategy

Automation

Content Marketing

Demand Gen

Go-to-Market

Product Marketing

Positioning

Social Media

Brand

B2B Marketing

SEO & AEO

AI for Leaders

AI Governance

Communication

Management

People Operations

Exec Presence

Storytelling

Goal-setting

Personal Brand

Fundraising

Everyone

Operators

Data Scientists

Business Analysts

User Researchers

Customer Success

Project Managers

HR Professionals

Sales People

Lawyers

Finance

Investors

Real Estate

Educators

Creators

Casual Conversation: Weekend and Salsa Dancing in Toronto

Introduction to Multi-Agent Frameworks and CrewAI

Why Build with CrewAI: Role-Based Collaboration and Orchestration

How CrewAI Works: Orchestrator vs. Direct LLM Decision Making

Comparing AI Frameworks: OpenAI SDK, LangChain, LangGraph, and CrewAI

Understanding Crews and Flows in CrewAI

CrewAI Studio vs. Open Source Framework for Developers

Foundations of CrewAI: Agents, Tasks, Crews, and Processes

Use Case: Multi-Agent Financial Analysis Workflow and Project Structure

Defining Agents and Tasks in CrewAI Code

Running the CrewAI Application and Analyzing the Output

Setting Up a New CrewAI Project from Scratch using UV

Q&A, Upcoming Labs, and Final Review of the Financial Analysis Output

Engineers and engineering leaders who build, deploy, and scale software systems.

Data scientists who apply statistical and ML techniques to extract insights from data.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Building autonomous AI agent systems that take actions, use tools, and orchestrate multi-step workflows.

Automating professional workflows with AI tools — productivity, operations, and task automation.

Intro to Multi-Agent Fundamentals Using CrewAI

What you'll learn

Why this topic matters

You'll learn from

Sol Farahmand