Yoram Friedman, MD
AI product management · Enterprise leadership
Walmart
I build enterprise AI and data platforms, lead product teams, and bring clinical judgment to complex decisions.
Today, I lead product areas for SAP’s Business AI Platform. My experience spans SAP, Walmart, Microsoft and digital health—from defining the roadmap to helping people use and trust what we build.
Years in enterprise product
SAP, Walmart, Microsoft & digital health
PMs in the global teams I led
Walmart · Director of Product Management
Learners reached
Through a co-created OpenSAP course
01 / Product leadership
Enterprise data, cloud infrastructure and digital health. Concrete product responsibilities, across strategy, teams, delivery and adoption.
Enterprise data & AI
I lead product areas spanning developer experience, extensibility, data products and governance for SAP’s Business AI Platform.
I define product priorities and work across teams on how data products are consumed, extended and governed. Earlier, I brought SAP Connected Goods from concept to an enterprise IoT platform.
Director of Product Management
I built and led a global team of six to eight product managers and defined the multi-year roadmap for a multi-cloud platform across private cloud, Azure and GCP.
The remit connected provisioning, automation and governance with engineering delivery, reliability at peak retail events, and organizational adoption.
Digital health
As the sole product manager, I worked across patient and clinician experiences and payer integrations for a regulated remote cardiac monitoring platform.
The work spanned patient and clinician workflows, eligibility, claims and incentives. My clinical experience brings domain knowledge to decisions involving clinicians, patients and healthcare organizations.
Independent experimentation
I maintain my own AI testing environment, building supervised agents with local and frontier models. I evaluate models, tools, and technologies against real workflows to understand where AI adds value and where human judgment remains essential.
This hands-on work puts my frameworks to the test across the full agentic lifecycle: defining the problem, designing the workflow, evaluating behavior, and exploring how supervision, monitoring, and continuous improvement should work together.
02 / Expertise & perspective
My training in anesthesiology and radiology gives me direct experience of healthcare workflows, decisions under uncertainty and the consequences of getting them wrong.
I have worked as both a product organization leader and a senior individual contributor. Across those roles, I focus on the human and cultural side of change: how teams adopt new tools, where resistance comes from, and how rollouts fit real workflows.
Technology that isn’t adopted isn’t a product. It’s a cost.
03 / Product management practice
The Agentic AI PM Lifecycle: six phases, with the deliverables and questions that make them useful. Most teams enter Discover without first building AI literacy.
A state of the organization, not a project stage. The PM enters Discover already carrying the vocabulary and mental models agent work requires.
Decide whether an agent is the right solution before engineering begins. Most expensive failures are prevented here.
Design the two products: the agent and the supervisory system. Runtime behavior engineered deliberately, not by default.
Prove readiness through evidence. Replaces the single pass-fail gate with distribution, projection, and state-validation.
Measure what the agent is actually doing in production. The continuous front end of Operate.
Act on what Observe is showing. Governance runs at runtime. Drift, silent degradation, and retirement are named stages.
Observe and Operate form a continuous loop: one measures what happens; the other responds. This framework underpins the series, the articles and the SAP Community posts, and can support multi-session PM upskilling.
Explore the framework in the book04 / Frameworks & mental models
Nine of the 50+ named models developed across my writing—covering data context, supervision, autonomy and the gap between a model’s answer and a product’s outcome.
You moved the data. The meaning stayed behind.
Regulatory intensity tracks clinical claims, not patient risk.
The framework assumes someone is watching.
The model learned the end. It is deployed at the beginning.
Intelligence without context is just confidence.
Design for one customer and forget the other. It fails.
Most PMs design Channel 1. Channel 2 is the supervisor.
Oversight without understanding isn’t safety. It’s sign-off.
Earned, not scheduled. Expand the boundary on evidence, not the calendar.
05 / Teaching & impact
I speak and teach on enterprise data, AI architecture and product strategy. A co-created OpenSAP course reached more than 40,000 enterprise practitioners.
40,000+learners · co-created OpenSAP course
Available for selected speaking engagements, podcasts and advisory discussions on agentic AI product design, governance in regulated environments, and the changing relationship between medicine and AI.
06 / Books & writing
My product frameworks continue in the five-book Agentic AI Series, alongside writing on medicine and authorship. The series is free to read online; print and Kindle editions are available on Amazon.
Forthcoming
Coming October 15.
A five-book arc: the PM lifecycle, product failures, team responsibilities, human judgment and product leadership. Written for teams shipping AI where being wrong has consequences.
Medicine’s professional wall was doing two jobs: controlling who got in, and quietly governing the care inside. AI has dissolved the wall, and almost no one has noticed the second job went with it.
07 / Practical resources
100+ articles on healthcare AI, enterprise data architecture, regulation and the work of moving AI from pilot to production.
A companion skill package for the agentic PM lifecycle, 55 interview questions answered from the product seat, and focused whitepapers.
Let’s talk
I welcome conversations about lead PM and product leadership roles in enterprise AI, data platforms and healthcare, alongside selected teaching, speaking and advisory work.
