Amir Piltan

Define High-Impact AI Agents with a Practical Framework

Zalando

Siemens

Philips

AI Product Leader

Understand why teams struggle to turn AI ideas into real product concepts and how to cut through the noise.

Understand the #1 Challenge: Where to Start With AI Agents

High-level intro to a structured & practical framework to discover, define, prioritize & evaluate high-Impact AI Agents.

Preview AI Agent Opportunity Discovery & Define Framework

Hands-on example to map a current workflow, find pains & decision points, and design an AI Agent–powered workflow.

Define Your AI Agent–Powered User Journey or Workflow

A better way to decide what’s actually worth building

Director of AI

Schlumberger

Intel

KPMG

Swarovski

Dalibor Jovic

Leadership & Product Excellence Coach

Tryg

Odfjell

StormGeo

ConocoPhillips

Hussam Ahmad

Cohort 2

Cohort 1

There is no shortage of AI ideas, but most teams are chasing AI features blindly.Many impressive demos never translate into real customer value or business impact.The people who stand out today can clearly answer:<ul><li>Is this a real opportunity or just AI hype?</li><li>Will this actually create value or just look impressive as a demo?</li></ul>👉 Identifying high-impact AI opportunities is becoming a core product leadership capability.In this workshop, you’ll learn how to systematically separate signal from noise using three key dimensions:<ol><li>Shared Value: Does this solve a meaningful problem for both the business and the user? Or is it a “nice-to-have” dressed up as innovation?</li><li>Feasibility: Can this actually be built with your current data, systems, and constraints? Or is it dependent on unrealistic assumptions?</li><li>Real-World Fit: Will this work in practice and inside real workflows, real behaviors, and real markets?</li></ol>These three lenses help you quickly filter out low-impact ideas and focus on opportunities that actually move the needle.This workshop helps you move from vague AI ambition to confident product decisions.

Identify high‑impact AI opportunities, cut through hype, and lead smarter product decisions with confidence in today’s AI‑driven landscape.

How to identify High‑Impact Opportunities

Learn  how to Prioritize Opportunities

Evaluate Feasibility with Confidence

Lead AI Conversations with Authority

Make Clear, Defensible Product Decisions

CxOs / ExecutivesLeaders shaping strategy who need clarity on where AI creates real value and how to avoid costly, low‑impact bets.

Product Leaders &amp; PMsWho are responsible for AI decisions and want a practical way to identify high‑impact opportunities with confidence.

Consultants &amp; AdvisorsHelping clients define AI direction and need a structured way to assess opportunities and guide better decisions.

A practical workshop on evaluating AI agents before launch

Founder & CEO | Ex-Adobe, WF, eBay | HBS

Adobe

Wells Fargo

eBay

Ganesan Anand

Founder, Formerly AI Product & Tech Leader (Adobe, Wells Fargo, eBay) · HBS alum

Next Cohort

<blockquote>Move your AI features from a vibe check to a value check. “Did the agent do the right thing? Would I catch it if it didn’t?” Every team shipping AI features is asking some version of these questions without a reliable way to answer them. An agent doesn’t just say the wrong thing. It does the wrong thing, and teams often find out from a user.Typical AI training falls into two traps: abstract theory that never leaves the slide deck, or disconnected techniques that stop short of a production-ready system. This workshop bridges that gap. I build enterprise infrastructure for AI evaluation every day, and I’ve seen that real adoption only happens when teams can trust their AI to perform consistently.You’ll learn a repeatable method for applying Responsible AI in practice, with a focus on reliability and safety. You’ll learn which metrics matter for your product, identify the edge cases that undermine trust, define how the product should respond, and prove it works before customers see a problem.</blockquote>

Learn a repeatable evaluation framework for building and releasing reliable AI features.

Know exactly what to measure

Find failures before your users do

Get a pass/fail read before release

Keep quality from slipping after launch

Access to leading commercial and open-source AI models is provided during the session for the eval exercises. Nothing to set up or pay for.

Model access is provided

Come ready to dig into how AI features fail and how to catch it. That mindset is all it takes.

Curiosity about AI quality

The session is live and remote, so a solid connection matters. Everything runs in-browser, and the no-code evaluation platform is provided.

Stable internet

AI engineers and product managers building, evaluating, or preparing to release AI features

Founders turning an AI prototype into a reliable product

Engineering and product leaders accountable for AI quality, safety, and release decisions

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

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.

Bring one real workflow and leave with clearer roles for AI and people to test 

Human-AI Work & Systems Advisor

Joyce Ventures

University of Wisconsin-Madison

Center on PBIS

Joyce White Nelson 

Systems-Change Advisor | Human Judgment & AI-Assisted Work | Founder, iQuoteHero

Founding Live Workflow Lab — September 2026

AI can help you move faster and sound 'good'. But if the workflow is unclear, speed and false positives can also create rework, weak review, lost context, generic output, or confusion about who owns the result.In this working Lab, you will bring one real AI-assisted workflow, decision, client deliverable, communication, or recurring task. You will map how the work currently happens, identify what AI should assist with, decide what needs human judgment and verification, and redesign with clearer roles for you, AI, and anyone else involved.Send me your workflow, decision, or use case ahead of time. That helps me shape examples and guidance around real situations.You will leave with:<ul><li>A completed Human + AI Workflow Map.</li><li>Clear decisions about what to delegate, retain, verify, or change.</li><li>Defined accountability and judgment points.</li><li>One practical experiment to test in your work.</li><li>A reusable method for evaluating future AI-assisted workflows.</li></ul>After the workshop, I will follow up by email or brief review call to help you examine what happened when you tested the workflow. We will look at what improved, what created friction, and what to keep, revise, or stop.

Redesign one real AI-assisted workflow so the Human/AI roles are defined and make  human judgment, accountability, or expertise visible.

 Map one workflow as it works today

Decide where AI belongs

. Protect human judgment and accountability

 Identify the most important risk or rework point

 Design one improved workflow experiment

Workflow to measure the outcome 

Experienced entrepreneurs and founders Already using AI and want clearer judgment, better workflows, and less hidden rework.

Consultants, coaches, and advisors Use AI in client work but want to protect quality, credibility, voice, and professional responsibility.

Leaders, educators, and team facilitators Need ways to decide where AI helps, where humans stay accountable, and people keep learning.

Define High-Impact AI Agents with a Practical Framework

What you'll learn

Why this topic matters

You'll learn from

Amir Piltan