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Every AI PM hiring decision comes down to one question: can you prove you can do this work? A portfolio with structured case studies is the most direct proof that exists. Build yours here.
Resumes tell hiring managers what you did. Portfolios show them how you think.
Hiring managers review 200+ applications per AI PM role. A portfolio link in your application makes you one of maybe 3 candidates who included concrete proof of their thinking.
Resumes say 'Led evaluation framework design.' Portfolios show the actual framework: what metrics you chose, why you weighted precision over recall, and what the model got wrong.
A message saying 'I admire your work' gets ignored. A message saying 'I wrote a case study on the same problem your team is solving' gets a reply. Portfolios give you something real to share.
Every case study you publish makes the next one easier to write and the next conversation easier to have. It becomes a living record of your growth as an AI PM.
This is what a portfolio looks like when it is built to prove capability, not list responsibilities.
Principal Product Manager | Enterprise Agentic AI
20+ years driving $100M+ programs across AI/ML strategy, telecom, and enterprise platforms. Currently leading AI-powered virtual agent strategy and ITSM backlog governance at T-Mobile.
Gen AI Partner Configuration Wizard
80% manual effort reduction. Processing time from 3 weeks to 3 days. Built with Gen AI, automation, and B2B integration.
Next-Gen Wholesale Billing Platform
Consolidated 3 billing systems supporting 50M+ accounts. $20M annual OPEX savings.
Enterprise Agentic AI Platform
AI-powered virtual agent strategy for enterprise support transformation using ServiceNow and NLP.
See the difference a case study link makes in cold outreach.
“Hi Sarah, I'm a PM looking to transition into AI PM roles. I admire the work your team is doing at Anthropic. Would you be open to a quick chat about what the role is like?”
“Hi Sarah, I recently wrote a case study on building an evaluation framework for an LLM-powered content moderation system (link). I noticed your team shipped something similar for Claude. I'd love to hear how you approached the precision-recall tradeoff for safety-critical classifications. Happy to share my framework if useful.”
Four sections. Structured prompts. Real examples. This is how AI PM hiring managers want to see your work.
What was broken? What user pain or business metric needed to move? Ground it in real numbers, not vague pain.
Example
Uber Eats merchant dashboard had a 30% abandonment rate. Root cause: mandatory menu photo upload blocked merchants with limited photography resources.
How did you validate? User interviews, data analysis, competitive benchmarks. What did you learn that surprised you?
Example
Analyzed 12K merchant sessions. Interviewed 15 merchants. Found 73% of abandonments happened at the photo step, not the menu data entry step everyone assumed.
What did you build and why? Key tradeoffs, alternatives you rejected, and the reasoning behind your approach.
Example
Built AI-generated menu photos from dish descriptions. Rejected stock photo library (too generic) and professional photography service (too slow). Chose DALL-E with merchant approval step.
What shipped and what moved? Quantified impact. Be honest about what worked and what you'd do differently.
Example
Merchant onboarding completion rate increased from 70% to 91%. Time-to-first-order dropped by 4 days. 18% of merchants later replaced AI photos with real ones.
Not a generic website builder. A structured portfolio tool designed for the content hiring managers want to see.
Write like a PM, not a blogger.
Follow the Problem-Discovery-Solution-Outcome framework. Each section has guided prompts, word count targets, and examples from real AI PM case studies. No blank page anxiety.
Screenshots, diagrams, and metrics that prove impact.
Add product screenshots, architecture diagrams, evaluation dashboards, and metric charts directly into your case study. Visual evidence makes abstract PM work concrete.
Group case studies by skill area.
Organize projects by category: AI/ML features, evaluation frameworks, data pipelines, launch strategy. Feature your strongest work at the top. Drag to reorder as you add more.
One link. Every hiring manager.
Get a clean portfolio URL you can drop into applications, LinkedIn, and cold outreach emails. Each case study has its own shareable link for targeted conversations.
Speak the language hiring managers search for.
The editor flags when your case study is missing AI PM signals: evaluation frameworks, model performance metrics, RAG architectures, prompt engineering decisions. Add them naturally.
Sharpen, don't fabricate.
Highlight any section and get AI suggestions to make it more specific, add metrics, or reframe for AI PM relevance. The AI improves your real work, not generates fictional experiences.
No AI PM experience yet? These projects give you realistic problems to solve. Complete one, write it up as a case study, and you have your first portfolio piece.
Build a product spec and prototype for a semantic search feature that understands user intent beyond keyword matching.
Design a content moderation pipeline that uses LLMs to detect and handle harmful content at scale.
Design a conversational AI assistant that personalizes the onboarding experience for a B2B SaaS product.
Redesign a recommendation system to balance personalization, diversity, and business objectives.
Design a data collection and feedback loop system that makes an AI product smarter over time.
Plan and execute the rollout strategy for a high-stakes AI feature in a regulated industry.
Pick a starter project or write up your own work. Follow the framework. Ship a case study that shows hiring managers exactly how you think, build, and ship AI products.
Start Your Portfolio