Weedmaps

Senior AI Product Manager, Search and Personalization

Systems of Impact

AI Product Management Consultant

Product Manager Accelerator

Product Mentor

Mozilla

Achievements:
•	Led a 5-person cross-functional team to implement the first experimental design with AI/ML experimental capabilities at Pocket, a B2C social bookmarking product for storing, sharing and discovering web bookmarks.
•	$3M revenue growth by expanding Pocket Recommended content to international markets.
•	Managed the Go-to-Market (GTM) strategy for the B2C AI/ML home surface product, impacting 600k monthly active users (MAU), leading to an 8.18.% increase in customer engagement.

Responsibilities:
•	Managed 3 B2C AI/ML products, including a B2C AI/ML content delivery product, a cross-platform B2C AI/ML home surface product, and a B2C AI/ML international expansion product.
•	Led Product Roadmap, design, and MVP of B2C AI/ML platform in order to decrease machine learning model time to production.
•	Led the Product Roadmap for the B2C AI/ML content delivery product in order to decrease the bounce rate on the Home page.
•	Prioritized requirements for B2C product user onboarding by completing user interviews (Voice of Customer) to decrease Home bounce rate.
•	Wrote and prioritized User Stories, requirements, enhancements, and issues for a B2C AI/ML Pocket recommended content based on strategic, product, and business goals.
•	Set data-driven OKRs and KPIs in order to drive prioritization and roadmap decisions.
•	Collaborated cross-functionally to deliver B2C AI/ML Pocket-recommended content to new markets via Firefox New Tab (France, Italy, & Spain).

Staff Product Manager, Data Products & Machine Learning at Pocket

GameStop

Achievements:
•	Collaborated with the Product Details Page (PDP) team to increase and improve the recommendations shown on the page, leading to a 30% increase in average order value.
•	Led a 12-person team to implement in-house recommendations using Google Cloud Platform (GCP) across the entire product catalog, leading to increased recommendation placement by 75%, engagement by 11%, and overall rec revenue by 10%.

Responsibilities:
•	Led the Product Roadmap for a B2C AI/ML personalization product in order to increase average order value (AOV).
•	Collaborated cross-organization to re-platform the pricing engine MVP and its go-to-market (GTM) rollout across 3500 stores, leading to an estimated 75% reduction in manual pricing and pricing exceptions.
•	Interviewed 12+ customers and studied e-commerce market trends to understand customer needs and converted them into actionable engineering-focused user stories.
•	Set data-driven OKRs and KPIs in order to drive prioritization and roadmap decisions.
•	Organized and led agile ceremonies to prioritize user stories, provide guidance, and drive progress.

Senior Product Manager - Recommendations

MGM Resorts International

Achievements:
•	Launched the first personalized content within MGM in collaboration with Microsoft which resulted in $500k in net new revenue over a 90-day period.
•	Launched a Recommendation-as-a-Service Product (RaaS) serving both external and internal customers.

Responsibilities:
•	Wrote user stories, requirements, and prioritized for a B2C AI/ML product in Azure.
•	Conducted Voice of Customer Interviews and studied hospitality trends to understand customer needs, and converted them to actionable engineering-facing user stories.
•	Collaborated cross-functionally across 8 lines of business and engineering channel partners to scope, build requirements, develop, and deploy a RaaS Product.

Senior Product Manager - Personalization & Loyalty

Achievements: 
•	Led a 2-person team to launch a 0 to 1 MVP for restaurant recommendations via email, leading to $50k in net new revenue over 30 days.
•	Launched the first personalized content within MGM in collaboration with Microsoft which resulted in $500k in net new revenue over a 90-day period.

Responsibilities: 
•	Conducted Voice of Customer Interviews and studied hospitality trends to understand customer needs, and converted them to actionable engineering-facing user stories.

Product Manager - Customer Insights & Growth

Lender Toolkit, LLC

- Worked with customers to refine their processes and improve delivery times by up to 20%
- Created implementation analytics with Engineering team using PowerBI to track delivery times
- Worked with Ellie Mae to build and implement new cloud based software platform for next-gen experience

Product Manager / Implementation Project Manager

Reflex Media Inc

- Wrote user stories and Implemented ML-powered moderation techniques to manage messages and reduce customer support burden for a marketing agency, reducing support moderation by over 90% through ML image classification and natural language processing (NLP).
- Initiated work with Data Science to implement machine learning systems to improve user recommendations and increase user engagement
- Initiated work to understand the Google Ad Manager platform to work with Data Science and Digital Marketing to implement site-wide analytics and improve site ad conversion
- Initiated Ownership of Messaging and User Engagement of the Seeking site, increasing member engagement by 13%
- Worked within the Atlassian ecosystem (JIRA/Confluence) and managed feature backlog and spec creation for Dev, including prioritization

Associate Product Manager

Workfront

- Developed user interview strategy to improve Digital Asset Management (DAM) product offering
- Developed metadata reporting structure to understand user metrics and usage
- Owned product from Ideation through initial Growth phase
- Increased from 20 base customers to 132 customers in 6 months with no marketing, a 560% increase

Product Related:
- Part of core team to establish/test/deploy new Digital Asset Management (DAM) offering via agile product management methodology
- Initiated/Completed Market research of asset management competition
- Created insights, personas, user stories, and prioritization from interview process to establish an MVP
- Launched white label beta product to 20 businesses for testing and feedback
- Developed implementation methodology and initial KPI measurements to report to executive management
- Revised Digital Asset Management (DAM) process upon feedback and analytics of usage

Design Consultant Related:
- Created and tested new ways to deliver implementations using lean/agile methodology improving certain implementation tier delivery times down to 60 days from 4 to 6 months
- Process Mapped and streamlined customer processes thru Lean Six Sigma methodologies and worked with the customer to build into the Workfront tool

Associate Product Manager / CX Design Consultant

- Worked with “At Risk” clients to re-engage Executive management and increase Workfront usage
- In a year’s time, worked with nearly $5M worth of Annual Run Rate (ARR) At Risk clients and only had a $180k reduction in ARR
- Worked within our strategic team to develop product offerings whose end results were pushed out to the entire company, adding 10 additional products for Sales to generate revenue
- Worked with executive management on user adoption strategies and built process around it for additional product offerings for Customer Success to reduce overall cost center
- Subject Matter Expert (SME) for End-to-End solution for Workfront, Proof HQ, and Workfront DAM for Customer Success and Ops departments

Strategic Services Consultant

Primary Residential Mortgage

- Created and Developed a Project Management Office (PMO), creating a new department within the company
- Developed training programs to improve project management culture within the enterprise
- Head of the Project Review Committee, other members include C-Level and SVPs
- Managed projects with budgets of $250k up through $25M+
-- Cross-departmental collaboration of 24 different departments (inc vendors)
-- Timelines that spanned from a few months up to 1.5 years
- Researched and procured new PPM/Work Management solution (AtTask).
- Developed and Launched AtTask/Workfront to company of 2000 users over the course of 6 months

PMO Project Manager

- Project Management of new programs, initiatives and revenue channels.
- Contract Negotiation with External Vendors and Investors.
- Review and interpret Investor/Agency/MI memos and determine impact to the corporation.
- Identify/implement opportunities to leverage systems to reduce risk associated with programs.
- Research and gather business and/or financial information, perform ad hoc analysis to support business decisions and provide feedback to executive management regarding results.
- Develop a thorough understanding of the business and its functions, processes and operations.
- Keep abreast of business and market trends, which may affect the organization.
- Research new investors, establish any requirements, determine market need, build out program, launch to company

Program Administrator / Product Manager

- Facilitate and manage the lock pipeline for Secondary.
- Analyze existing reports used by the Secondary Marketing team to ensure accuracy and completeness of data. 
- Identify issues with current reporting mechanisms, determine cause and recommend solution to ensure accuracy and completeness.
- Analyze the delivery and transaction functions to identify opportunities to become more efficient.
- Assists in identifying and implementing process improvements for secondary marketing functions.
- Supports the Capital Market team as needed to assist in the fulfillment of trades.
- Supports the Program Admin team on the implementation of new products.

Secondary Marketing Analyst

Struggling to transition your product management skills into the AI domain? I’ve got the roadmap you need.

You have two options:

1. Wing it and hope to navigate the complexities of AI product management on your own.
2. Sign up for the AI PM Ready waitlist and get a structured roadmap tailored to non-technical product managers.

If you are:

• Frustrated at not knowing where to start
• Seeking a clear roadmap to transition into AI PM
• Unsure how to build technical influence with engineering partners
  
The AI PM Ready Program can help by:

• Providing a structured roadmap to build AI product management skills
• Offering insights into understanding ML concepts
• Helping you articulate strategies and best practices for AI PM

I'm Sam, a Senior AI Product Manager with over 8 years of experience in product management, focusing deeply on AI/ML. I specialize in transforming traditional product management into AI-driven product strategies. My journey includes managing over 10 AI products, generating over $250M in revenue, and mentoring product managers to transition into AI PM roles.

Send me a DM with "AI PM" to find out more.

Ready to level up your product management skills? Connect with me to join the AI PM Ready Waitlist: https://systems-of-impact.beehiiv.com/c/ai-pm-waitlist

Let’s connect if you're passionate about AI and product management!

Looking for a PM role in today's Market? 

@Weedmaps has opened up a new PM role. 

This role does prefer a hybrid role in Irvine, CA. 

It will focus on the following:

• Product Roadmap Execution
• A/B Test Experimentation
• Data Analysis and Insights
• Scrum Management
• Cross-Functional Collaboration

Requirements: 

• 2+ years product management experience in a technological industry
• 1+ years experience in consumer-facing online commerce, point-of-sale, or marketplace
• Experience with Native Product development
• Experience managing agile software development with scrum preferred
• Bachelor’s degree or equivalent work experience 
• Strong analytical and quantitative skills; strong bias towards data-based decision making and comfort with pro-forma financial and operational analysis
• Experience with A/B testing methodologies and experimentation frameworks
• Excellent customer experience intuition; demonstrated success in creating innovative and user-friendly websites and customer-facing features

Edit: Due to sheer volume, I won’t be able to respond to all inquiries. Good luck!

Sam Montoya

boards.greenhouse.io

Product Manager (Hybrid)

The top 3 habits that have made me a better PM. 

None of them deal with product. 

1. Daily Writing Habit

→ Helps build communication skills and clear thinking.

2. Get Up and Move

→ Helps creativity and reduces stress.

3. Growth Mindset

→ Always be learning and embracing challenges.

Bonus: 

4. Failure Isn't Fatal

→ Failure is the most data rich information source.

P.S. What habit has helped you be a better PM?

The one book PMs should consider.

Regardless of specialty. It’s that good. 

The book is by Sol Rashidi 
Your AI Survival Guide.
It's one of the most actionable books I have ever read.

A lot of books have a lot of fluff. 

They pad the runtime. 
There's a lot of theory. 
There's not enough meat. 

This book is the exact opposite. 

The book is focused on AI. 
However, I suggest reading chapter 4. 
It can apply to any PM. 

Chapter 4 focuses on the following: 

• Frameworks for AI initiatives
• Phase 1: Conduct a Readiness Assessment
• Phase 2: Your AI Strategy
• Phase 3: Creating and Selecting Use Cases
• Phase 4: Preparing and Designing
• Phase 5: Selecting a Solution
• Phase 6: Deploying and Going Live

That's a lot for one chapter. 

There is zero fluff. 
It's one of the most actionable chapters. 
It's one of the best chapters I've read in a book. 

Ever. 

P.S. What book would you suggest?

With seven years of product management experience, Sam is an experienced ML/AI-focused Product Manager with a successful track record in strategic planning, revenue growth, and customer engagement. Sam is proficient in cross-functional collaboration, agile methodologies, and ML technologies.

Sam enjoys staying up on technology trends, personal development, career development, movies, music, and video games. 

Touch base if there’s something he can help you achieve, or you enjoy tech and would like to geek out and talk shop.

Sol Rashidi

Not getting the results from AI as a PM? 

It's probably easier than you think. 

Here's a refresher on the prompt framework I use. 

RODEN: 

• R: Role
• O: Objective/Instruction
• D: Details
• E: Examples
• N: Narrowing/Constraints

I've seen a lot of prompts over the past year. 

Whether it's a Zero-Shot, or Chain of Thought, 
There's usually two missing components of a prompt. 

1. Examples
2. Narrowing

Examples are massive. 
If you don't provide a good example to an LLM, 
It will default to what it knows. 

It may not be exactly what you want. 

Narrowing, is also key. 
If you don't provide a constraint, it can run wild. 
Again, it will default to what it knows. 

Again, it may not be exactly what you want. 

Tell the model exactly what you want.
Give the model good examples of what you want. 
Tell the model exactly what you don't want.  

Doing this will help you start getting better results.

Missing AI Prompt Frameworks

3 days to get Chat GPT to give me code that worked. 

A lot of frustration was involved. 

Outcome I was working towards: 
• Run on device
• Identify products
• Identify their categories
• Generate a summary. 

The proposed approach: 
• Three different roBERTa models
• Meta model that trained on the 3 models
• T5 model for summarization

What happened for three days? 

I got the exact same error code. 
It happened at roughly 40%. 
After roughly 2000 seconds. 

Every. 
Single. 
Time. 

I was pulling my hair out. 

I took the code and gave to Claude. 
It noticed a few items to fix. 
It provided the code I needed. 

What happened? 

The. 
Exact. 
Same. 
Error. 
Again. 

The error referenced a line of code that wasn't there. 

I was frustrated. 
But then I went for a walk. 
And I had an idea. 

What if I started a new file and saw what happened?

The code ran. 
It ran properly. 
I got a brand new error. 

The lesson? 

Sometimes you need to start over. 
Sometimes you need to start from scratch. 
Wipe the slate clean and start again.

Wondering what the basics of AI are? 

This is key for anyone trying to become an AI PM. 

What is AI? 

A field of computer science.
Enables machines to perform tasks.
Tasks that typically require human intelligence.

How does AI try to mimic human intelligence?

Sense
• Image Detection
• Speech Detection
• Object Recognition

Understand
• Predict
• Recommendations

Create
• Content

What types of AI are there? 

Machine Learning
• Supervised Learning
• Unsupervised Learning
• Reinforced Learning
• Neural Networks
• Autoencoders
• Convolutional Neural Network (CNN)
• Natural Language Processing (NLP) 
• Deep learning

Computer Vision
Robotics

Where are the models?

Each section above has applicable models. 
Model selection depends on the outcome. 
As an AI PM, you don't need to know every model. 

You drive the outcome. 

P.S. Follow for more AI Product Management content.

Image Source: Product Faculty

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