Certificate Program

Applied AI Agents for Product Managers

Design and ship AI agents that reason, use tools, and automate complex workflows.

Taught by Ata Tahiroglu · Sr. Director PM @ Salesforce · Ex-Group PM @ Apple

Live Hands-on Modules

Core Sections

Working Agent Shipped

Certificate of Completion

1-1 Coaching Sessions

★★★★★4.8See reviews

30-min call with Ata

Complete Curriculum

Agent Foundations

How agents actually work — architecture, tools, and hands-on building.

Module 1: How AI Agents Work

Go beyond the buzzword. Understand what separates an agent from a chatbot: planning, reasoning loops, tool use, and memory. Trace how a real agent breaks a goal into steps, decides which tools to call, and recovers from failure — and learn the vocabulary that lets you hold your own in any architecture discussion.

Module 2: Agent Architectures & Patterns

Map the design space: single agents, orchestrator patterns, and multi-agent collaboration. Learn when a simple workflow beats an autonomous agent, how leading frameworks approach the problem, and the cost, latency, and reliability trade-offs each architecture carries — the decisions PMs are accountable for.

Module 3: Tools, MCP & Context Design

An agent is only as good as the tools and context it can reach. Master Model Context Protocol (MCP) as the integration standard: how agents connect to databases, internal APIs, and third-party systems, how context windows are managed, and the security questions you must answer before an agent touches company data.

Module 4: Build Your First Agent Hands-On

Build a working agent in class using n8n and Claude — a real workflow with triggers, reasoning, tool calls, and outputs you can show your team the next morning. No code required: the goal is that you understand every component because you assembled every component.

Productizing AI Agents

Evals, economics, and strategy — the PM layer that makes agents ship.

Module 5: Agent Evals & Reliability

Non-deterministic products need a new quality bar. Learn to define eval suites for agent behavior — task success rates, hallucination checks, regression tests for prompts and tools — and to set the reliability thresholds that decide when an agent is ready for real users. This is the skill that separates agent demos from agent products.

Module 6: Multi-Agent Systems

Design systems where specialized agents collaborate: researcher, analyst, reviewer, executor. Understand orchestration, hand-off protocols, and shared context — and the failure modes that multiply when agents talk to agents. Build a multi-agent workflow in class and stress-test it against a real product scenario.

Module 7: Agent Product Strategy & Economics

Decide where agents belong in your product. Identify high-value use cases, run the build vs. buy analysis, and model the unit economics — token costs, latency budgets, and pricing models for agentic features. Leave with a one-page agent opportunity map for your own product, ready for your next planning cycle.

Module 8: Responsible & Safe Agent Deployment

Agents act autonomously — which makes guardrails a product requirement, not an afterthought. Learn permission models, human-in-the-loop checkpoints, audit trails, and rollback strategies. Understand the failure stories behind each guardrail, and design the safety case that lets legal, security, and leadership say yes to your agent.

Instructor Led Step By Step Agent Development

Build a real, working AI agent alongside the instructor — from use case to deployment.

Module 1: Use Case Selection & Agent PRD

Pick the right problem before writing a single prompt. Apply a scoring framework that separates agent-worthy workflows from jobs a simple automation should do. Write an agent PRD that defines the goal, the tools the agent may use, the boundaries it must respect, and the success metrics — the document your engineering team will actually want to receive.

Module 2: Architecture & Tool Design

Translate the PRD into a working architecture with the instructor. Choose between single-agent and orchestrated patterns, design the toolset the agent needs, and connect data sources through MCP. Learn to draw the architecture diagram that makes an agent system explainable to executives and engineers alike.

Module 3: Build, Test & Eval

Assemble the agent live in n8n with Claude as the reasoning engine: triggers, prompts, tool calls, and outputs. Then prove it works — build the eval set together, run failure-mode testing, and tune prompts and thresholds until the agent clears the reliability bar you defined in the PRD.

Module 4: Deploy, Monitor & Iterate

Put the agent to work on a real schedule with real data. Set up monitoring for task success, cost, and drift; add the human-in-the-loop checkpoints that catch bad outputs before they reach users; and establish the iteration cadence that keeps an autonomous system trustworthy over time.

AI Agent Capstone Project

Showcase your mastery by designing, building, and shipping your own AI agent from 0 to 1.

Project Part 1: Use Case & Agent PRD

Choose a workflow from your own job or product that deserves an agent, and make the case for it. Score it with the use-case framework, write the agent PRD with goals, tools, boundaries, and metrics, and defend the choice in a design review with the instructor — exactly as you would inside a company.

Project Part 2: Architecture & Build

Design your agent's architecture and build it: reasoning prompts, tool integrations, memory, and error handling. Apply the patterns from the instructor-led build with office-hours support when you hit walls. The goal is a running agent you assembled and understand end to end.

Project Part 3: Evals & Hardening

Prove your agent is more than a demo. Build an eval suite for its core tasks, measure success rates honestly, and harden the failure modes you find: bad inputs, tool outages, hallucinated outputs. Add the guardrails and human checkpoints that would make it deployable in a real organization.

Project Part 4: Deploy & Present

Run your agent live on a real schedule and present the results in the final session: the use case, the architecture, the eval scores, and what you would do next at production scale. Get instructor and peer feedback, add the project to your portfolio, and earn your Applied AI Agents for Product Managers certificate.

Become the Agent PM Every Company Is Hiring For

Agent product roles are the fastest-growing PM specialty — position yourself to win them.

Module 1: Positioning for Agent PM Roles

Every major product org is adding agentic features, and PMs who can speak architecture, evals, and agent economics are scarce. Learn to present your capstone as the centerpiece of your candidacy: how to frame agent work on your resume, walk an interviewer through your architecture and eval decisions, and answer the system-design questions agent PM interviews now include.

Module 2: Launching an Agent-Powered Startup

Vertical AI agents are one of the largest startup opportunities of this decade. Learn how to spot a niche workflow worth automating, validate demand before building, and turn the agent you can now build into an MVP. Understand what investors look for in agent startups: distribution, reliability story, and unit economics that improve as models get cheaper.

1 on 1 AI Product Management Coaching

Accelerate your career transition with personalized guidance from an industry expert.

Session 1: Career Path & Skill Gap Analysis

Receive personalized guidance to accelerate your AI PM career trajectory. In this focused 30 minute session, work one on one with an experienced AI product leader to assess your current skill set objectively, identify critical gaps blocking your progress, and chart a clear, actionable path forward. Receive customized recommendations on learning priorities, experience building opportunities, and strategic career moves that align with your unique background and goals.

Session 2: Resume & Interview Strategy

Transform your professional materials and interview approach with expert coaching. Spend 30 minutes working directly with a seasoned AI product leader to optimize your resume, ensuring it highlights AI relevant experiences and speaks the language hiring managers understand. Learn to tell compelling stories about your work, articulate your value proposition clearly, and handle challenging questions with confidence.

Session 3: Networking & Job Search Tactics

Master the networking and job search strategies that land elite AI PM roles. In this focused 30 minute coaching session, learn to build an influential presence in the AI ecosystem through strategic networking, leverage LinkedIn effectively, access hidden opportunities, navigate recruiter relationships, and position yourself as an ideal candidate with tactics tailored to your unique background and target companies.

Meet Your Instructor

Ata Tahiroglu

Senior Director, Product Management @ Salesforce

Columbia University Lecturer

Ata is a seasoned Senior Director of Product Management at Salesforce leading the development of cutting edge AI agents at scale — the exact discipline this certificate teaches. Prior to Salesforce, he led AI/ML product initiatives at Apple, building innovative AI products used by millions. He also has extensive experience in hedge fund technology, where he built ML-based equity research products that revolutionized investment decision-making. He has lectured over 4k students in his teaching career, including courses at Columbia University. Based in the San Francisco Bay Area, he brings real world expertise from the world's leading technology companies to help you master the art and science of AI product management.

Upcoming Cohorts

Applied AI Agents for Product Managers

July 7th, 2026 - July 30th, 2026

Instructor: Ata Tahiroglu

Tuesdays & Thursdays, 5:30 PM to 8:30 PM PST

Timezone: America / Los Angeles

3 hour live online session

Including 15 min break

Spots available. Secure your place today!

Looking for the Masterclass or Claude Code cohorts? See all cohorts.

What Our Students Are Saying

★★★★★5.0

“Ata is knowledgeable, passionate about the subject, and very patient. His experience really comes through, bringing the content to life with real, applicable examples you can actually use in your work. Highly recommend it.”

Karen Assis Rahme

Director, Financial Products at Grupo Farid

★★★★★4.8

“As a non-technical lawyer I finally feel confident building AI powered law products. The curriculum is practical and immediately applicable.”

Aksel Kokkilinc

Head of Legal Products at Kökkılınç Law

★★★★★4.8

“Ata breaks down complex AI concepts in a way that makes them actionable. I walked away knowing exactly how to build AI into my product.”

Philippe Berk De Andria

SaaS Entrepreneur

★★★★★5.0

Karen Assis Rahme

Director, Financial Products at Grupo Farid

Why This Certificate?

Built for PMs, Not Engineers

NVIDIA and GitHub certify engineers; Harvard briefs executives. This is the program in between — the product layer of agents: use cases, architecture decisions, evals, and economics.

Hands on Experience

Build two real agents — one with the instructor, one as your capstone — so you understand every component because you assembled every component. No code required.

Evals & Reliability Discipline

Most agent training stops at the demo. This program teaches the quality bar — eval suites, failure modes, guardrails — that separates agent products from agent prototypes.

The Fastest-Growing PM Specialty

Every major product org is adding agentic features and hiring PMs who can lead them. Walk into those interviews with a shipped agent and the vocabulary to defend its design.

Taught by a Salesforce Agents Leader

Your instructor leads AI agent development at Salesforce at enterprise scale — you learn the patterns and failure stories from someone shipping agents to real customers today.

Architecture Fluency Without the CS Degree

Planning loops, tool use, orchestration, MCP, context windows — gain the conceptual depth to lead architecture conversations with engineers without pretending to be one.

Tools You Will Master

N8N

The visual workflow platform where you assemble your agents: triggers, reasoning steps, tool calls, and integrations — sophisticated agent architectures without writing code.

Claude & the Anthropic API

The reasoning engine inside your agents. Learn model selection, prompt design for autonomous behavior, and the cost and latency levers that shape agent economics.

MCP

Model Context Protocol — the integration standard for agent tool use. Connect agents to databases, APIs, and company systems with the right security guardrails.

Openrouter

Multi-model routing for agent systems: compare models on the same task, manage costs across providers, and build agents that aren't locked to a single vendor.

Eval & Monitoring Tooling

The measurement layer for non-deterministic products: eval suites, task success dashboards, drift detection, and the human-in-the-loop checkpoints that keep agents trustworthy.

Huggingface

The open-model ecosystem: discover and evaluate open source models for agent components where cost, privacy, or control argue against commercial APIs.

Real World Templates Included

Access battle-tested agent templates and frameworks used by top AI product teams.

Agent PRD Template

The requirements document built for autonomous systems: goals, allowed tools, boundaries, escalation rules, and success metrics — the spec your engineers will thank you for.

Agent Use-Case Scoring Framework

The worksheet that separates agent-worthy workflows from jobs a simple automation should do — scored on value, frequency, failure tolerance, and data readiness.

N8N Agent Workflow Templates

Importable n8n workflows for the core patterns: single agent with tools, research-and-report pipelines, and a multi-agent orchestration starter — ready to customize.

Agent Eval Suite Starter

A ready-to-adapt eval framework: task success rubrics, hallucination checks, regression test structure, and the reliability scorecard that decides when an agent ships.

Agent Cost & Economics Model

A spreadsheet model for agentic features: token costs per task, latency budgets, pricing scenarios, and break-even analysis — the numbers leadership asks for.

Guardrails & Safety Checklist

The pre-launch checklist for autonomous systems: permission models, human-in-the-loop checkpoints, audit trails, and rollback plans — the safety case that gets stakeholder sign-off.

Risk-Free Enrollment

Money-Back Guarantee

We're confident in the transformative value of the Applied AI Agents for Product Managers certificate program. If you're not completely satisfied after attending day 1 of the class, simply let us know and we'll provide a full refund – no questions asked. That's how certain we are that this program will equip you to lead the agent era of product management. Contact us with any questions.