The best AI product manager portfolio examples do one thing a normal PM portfolio does not: they show how the PM defined good model behavior, measured it, and shipped anyway. AllthingsPM is an AI PM course and PM interview prep platform, and its free PM Portfolios directory lists 455 real portfolio sites, 93 of them from AI/ML product people, filterable by level from PM to VP/CPO. This page picks 18 of those 93, says what each does well, and turns the patterns into a build plan you can finish with the AllthingsPM AI PM course.
If you only open three: Aman Khan for writing about non-deterministic systems, David Jones for a VP who lists 43 hands-on AI projects, and Sparsh Nagpal for an early-career AI PM who leads with scale.
Which AI product manager portfolios are worth studying?
Here are the 18, grouped by level, all taken from the AI/ML filter of the AllthingsPM directory. Titles and focus come from each person's directory entry and site, read on 26 September 2026.
| # | Portfolio | Level | AI focus | Copy this |
|---|---|---|---|---|
| 1 | AllthingsPM PM Portfolios directory | All levels | 93 AI/ML sites, 455 total | Filter by your level and study five people one step above you |
| 2 | Aman Khan | Head of Product, Arize AI | Evals and observability | A point of view on non-deterministic AI |
| 3 | David Jones | VP of Product Management | AI integration, productivity | 43 projects built hands-on, as a VP |
| 4 | Chad Holdorf | CPO / SVP / VP of Product | AI platforms | Executive story anchored in known companies |
| 5 | Juliet Shen | Head of Product, ROOST | ML and trust and safety | A clear specialty, not "AI in general" |
| 6 | Jaclyn Konzelmann | Director of PM, Google Labs | Zero to one AI and creative tools | Zero to one framing |
| 7 | Sherif Maktabi | Director of PM for Agents, UiPath | Coding agents | A one-line thesis on agents |
| 8 | Vamsee Jasti | Senior Director of PM, Meta | AI Search | Scope stated in products people know |
| 9 | Kartikay Dhar | Director of Product, AI, Sprouts.ai | Enterprise AI | Case studies from concept to adoption |
| 10 | Chirag Soni | Senior AI Architect PM, Microsoft | Copilot and agents platform | Research publications plus side projects |
| 11 | Suhel Parekh | Principal Product Lead, Microsoft | M365 Copilot grounding | 25+ AI apps built on the side |
| 12 | Priyanka Shetty | Principal PM turned architect | Agentic product operating system | A named framework she built |
| 13 | Elena Calvillo | Senior PM | RAG agents, automation | A "lab" of vibe-coded products |
| 14 | Shubhang Yadav | Senior AI PM, 73 Strings | LLM products, agents, chatbots | The exact AI surfaces he shipped |
| 15 | Robert Bye | PM, Anthropic | Claude | Design craft plus PM, visually shown |
| 16 | Sparsh Nagpal | AI PM | LLM, RAG, generative AI | Scale numbers up front |
| 17 | Kevin Astuhuaman | AI PM | AI/ML observability | Career progression told as a story |
| 18 | Laniah Lewis | AI PM | Cameras, sensors, data pipelines | Human experience meets ML |
What do the best AI PM portfolios have in common?
Reading all 93 AI/ML sites side by side, four patterns repeat.
They name a specific AI surface. "AI product leader" is weak. "M365 Copilot web grounding" (Suhel Parekh) or "AI Search for Facebook" (Vamsee Jasti) tells a hiring manager exactly what problems you have seen.
They show building, at every level. David Jones is a VP and still lists 43 hands-on projects. Elena Calvillo runs a lab of small products. Priyanka Shetty built her own agentic operating system. In the AI set, building is not a junior signal.
They lead with outcomes and scale. Sparsh Nagpal's site states LLM, RAG and generative AI products serving 3.5M+ daily active users. Umang Thakkar's says 14+ AI products reaching 5M+ users. Numbers sit in the first screen, not the fourth case study.
They have a point of view. Aman Khan writes for PMs working with non-deterministic AI systems. Sherif Maktabi frames his work around rebuilding a platform for coding agents. A thesis is what makes a portfolio memorable.
Akhil Tiwari summed up the shift in January 2026: "AI PMs are not hired to design features. They're hired to own system behavior." The portfolios above make that visible.
How AllthingsPM does this: the AI PM course is organised around exactly these skills: a chapter on evals, one on agents and agentic architecture, and one on proving it paid off. Each ends in a graded case study you can publish as a portfolio piece.
What should an AI product manager portfolio include?
Every serious guide we read in 2026 converges on the same short list.
| Piece | What it proves | What to show | Who recommends it |
|---|---|---|---|
| A small AI product you built | You can ship | Problem, users, the decisions, what broke | HelloPM, Institute of AI PM, ShipSet |
| A teardown of an AI product | Judgment | Where it fails, why, what you would change | HelloPM, Institute of AI PM |
| An evals plan or eval table | You take quality seriously | Test inputs, rubric, pass or fail, notes | HelloPM, Institute of AI PM, ShipSet |
| A behavior spec | You define correct behavior | What the system should and must not do | Akhil Tiwari |
| A decision log | Your reasoning | Why this model, this prompt, this fallback | ShipSet |
HelloPM's July 2026 guide puts it bluntly: "A portfolio with one real thing you built and can reason about beats a stack of certificates every time." The Institute of AI PM suggests "three to five deep case studies" and describes the eval piece as "a spreadsheet or notebook with 50 to 200 test inputs, the model output for each, and a score against your rubric."
ShipSet's advice for the demo is the most practical line we found: "Talk about the decisions, not the buttons." Explain why you set a temperature, why you refused certain inputs, why the fallback exists.
What to cut, per Tiwari: UI screenshots with no system context, long PRDs, generic metrics like DAU and CTR, and lists of AI tools you used.
How AllthingsPM does this: the course lesson on the take-home, the presentation, and the portfolio recruiters read first walks through which of your pieces to put up front. The multimodal evals lesson shows you how to build a golden set, which is the eval table these guides ask for.
Which examples are best for senior AI product leaders?
Directors and VPs in the directory use the portfolio differently. It is less a case-study gallery and more a statement of what they believe.
- Aman Khan, Head of Product at Arize AI: writing first, on evals and observability.
- Chad Holdorf: CPO, SVP and VP roles across Demandbase, Pendo and Salesforce, framed around AI platforms.
- Jenna Minnix, VP of Product at Beautiful.ai: traces her path from analyst to VP, with a focus on AI-enabled scaling.
- Maura K. Randall: platform leadership at Atlassian, eBay, Yahoo! and Conde Nast, now AI-native product leadership, on a free GitHub Pages site.
- Rangaprabhu Parthasarathy, Director of Product for AI Wearables at Meta: 25 years of consumer products including Echo, Kindle and Oculus Quest.
- Timothy Buck, Product Director at Meta: builds AI products for billions of people.
The pattern: one sentence of scope, recognisable products, and a clear area of expertise. Of the 93 AI/ML portfolios, 15 are VP/CPO level and 10 are Director level.
How AllthingsPM does this: senior candidates get grilled on strategy and economics. Chapter 13 of the course, Lead the room, covers staff moves, the forward-deployed PM role and the portfolio, and the question bank holds 4,122 real questions from 260 companies to rehearse the strategy rounds.
Which examples are best for early-career AI PMs?
The PM-level group is the biggest slice of the AI set: 37 of the 93. These sites have less history, so they lean on building.
- Sparsh Nagpal: LLM, RAG and generative AI products, with reach and business value numbers up front.
- Umang Thakkar: 14+ AI products and 5M+ users, on a simple Vercel site.
- Sidharth N: 4+ years shipping AI products from zero to one, from a consumer app with 100K+ users to enterprise platforms.
- Naresh Silla, AI PM at Capillary Technologies: generative AI for customer engagement, and an AI product hackathon win.
- Justina Yoo: GenAI, LLM and RAG, framed as end-to-end AI transformation.
- Vishant Batta, PM at Writesonic: a Notion page, proof you do not need a custom site.
Hosting is cheap here. At least seven of the 93 AI/ML portfolios run on vercel.app, and others use Notion, GitHub Pages, Webflow, Netlify and Lovable. Nobody hires you for the domain.
How AllthingsPM does this: if you have no shipped AI product yet, the course's graded case studies give you something real to write up, and the capstone teardown is the teardown piece every guide asks for. Browse the PM-level AI portfolios to see how others with similar experience framed theirs.
How do you build an AI PM portfolio in four weeks?
A plan that fits around a full-time job, built from the patterns above.
- Week 1: pick one AI surface and read. Choose a problem area (support agents, search, coding agents). Open 5 portfolios in that area on the directory and write down what they lead with.
- Week 2: build something small. A narrow AI feature with real inputs. Keep a decision log as you go: model choice, prompt changes, what you refused to support.
- Week 3: write the eval table. 50 or more test inputs, a rubric, pass or fail, a note per failure. Group failures by cause. This is the piece most candidates skip.
- Week 4: teardown and publish. Tear down one public AI product in about 1,500 words, then publish all three with a short summary at the top of each.
Then practise talking about it. As HelloPM notes, a hiring manager "can tell the difference in about two minutes." The portfolio gets you the call; the interview is where you defend it.
How AllthingsPM does this: paste the job description you want into the JD mock interview and practise walking through your project against that role, in text or voice, with follow-ups and a score. Check the resume review against a JD so the resume points to the same projects. Looking for roles to aim at? The jobs catalog has 116 live PM job descriptions at 18 AI companies, such as Product Lead, AI/ML (Evals) at Abridge.
What mistakes make AI PM portfolios weak?
- Naming tools instead of decisions. "Used GPT and LangChain" says nothing. Tiwari lists this among things to remove.
- Screens with no system. A chatbot screenshot without the behavior spec or eval results reads as a demo, not product work.
- Generic metrics. DAU and CTR miss what AI hiring managers ask about: quality, failure rates, cost.
- Too many pieces. The Institute of AI PM caps it at five case studies. Three strong ones beat eight thin ones.
- Hiding the failures. The GitHub portfolio of one AI PM candidate describes "honestly-reported evals". Showing what failed and why is a strength.
How AllthingsPM does this: the evals chapter is titled "define good and make the number defensible", which is exactly the gap these mistakes expose. Read our AI evals guide for product managers for a shorter version.
Why AllthingsPM is the better choice for AI PM portfolio examples
Most pages on this topic give advice without examples, or list a handful of sites. AllthingsPM gives you both sides of the job in one place.
First, the examples. The PM Portfolios directory holds 455 real portfolio sites from people at PM level or above, 93 of them in AI/ML, from Anthropic, Google Labs, Meta, Microsoft, UiPath and Arize AI to early-career AI PMs on free Vercel sites. You filter by level and industry and study people one step ahead of you.
Second, the pieces. The AI PM course is built from 604 real PM job postings and has 14 graded case studies, including a teardown capstone that ends with a portfolio. That is the "one real thing you built" every guide asks for.
Third, the interview. A JD-based mock turns any posting into a scored practice interview, and the question bank has 4,122 real questions from 260 companies, each with its own page and answer guide.
HelloPM, the Institute of AI PM and ShipSet publish good project advice, and it is worth reading. For examples, the course that produces the pieces, and the practice to defend them, at $20 a month or $120 a year with a free tier, use AllthingsPM. Start with the free directory.
Frequently asked questions
What is the best place to find AI product manager portfolio examples?
AllthingsPM's free PM Portfolios directory lists 455 real PM portfolio sites, 93 of them in AI/ML, filterable by level and industry. Guides from HelloPM and the Institute of AI PM are useful for project ideas.
How many projects should an AI PM portfolio have?
Three is enough for most people: one thing you built, one teardown and one evals plan. The Institute of AI PM recommends three to five deep case studies and treats five as the maximum.
Do I need to code to build an AI PM portfolio?
No. Many portfolios in the directory are built on Notion, Webflow or no-code tools. What matters is showing that you defined good behavior, measured it and made tradeoffs.
What makes an AI PM portfolio different from a regular PM portfolio?
It shows system behavior: behavior specs, eval tables, failure analysis and the decisions behind prompts and fallbacks. A regular PM portfolio can lean on feature launches and funnel metrics.
Can I use course projects in my portfolio?
Yes, if you did the work and can defend it. The AllthingsPM course has 14 graded case studies and a teardown capstone. Guides also suggest adding at least one project from outside any course.
Where should I host my AI PM portfolio?
Anywhere simple. Of the 93 AI/ML portfolios in the AllthingsPM directory, at least seven are on vercel.app, and others use Notion, GitHub Pages, Webflow, Netlify and Lovable.
Ready to build yours? Browse the 93 AI portfolios free, then start the AI PM course to make your first piece.
Sources
- AllthingsPM, PM Portfolios directory, 455 sites, 93 tagged AI/ML; level, industry and hosting counts computed 26 September 2026.
- The 18 featured portfolio sites, each linked above, with titles and focus from their directory entries, 26 September 2026.
- Keerti Chandnani, HelloPM, 3 AI Product Manager Portfolio Projects That Get You Interviews, July 2026.
- Institute of AI Product Management, How to Build an AI Product Manager Portfolio That Hiring Managers Actually Read, May 2026.
- Akhil Tiwari, The Product Space, What an AI PM Portfolio Must Show in 2026, January 2026.
- ShipSet, The 10 AI PM Portfolio Projects That Actually Get You Hired, May 2026.
- vishalhabib99, ai-pm-portfolio on GitHub, AI PM portfolio with PRDs, prototypes and honestly-reported evals.
- AllthingsPM, State of AI PM Hiring 2026, 604 PM job postings.
- AllthingsPM, Product Manager Portfolio Examples and How to Become an AI Product Manager.
