Summary of "Webinar: How PMs Use AI to 10X Their Productivity by Product School EiR, Samantha Stevens"

Summary: “How PMs Use AI to 10X Their Productivity” Webinar by Samantha Stevens, Product School EiR

Presenter Background

Samantha Stevens is an AI Executive and Product School Entrepreneur in Residence (EiR). She is the founder of Catalyst, an AI project management assistant currently in closed beta.

Her past roles include: - Product Manager at American Express (Windows 10 app) - Director of Product at Tinder (growth, revenue, new product development) - Early LLM integration at Google Assistant - YouTube monetization, where she launched the “Super Thanks” feature

Key Frameworks and Methodologies for PMs Using AI

1. Using AI as a Thought Partner in Product Strategy

Samantha recommends a three-step funnel approach:

Cast a Wide Net Use large language models (LLMs) like GPT-4, Claude, or Perplexity to brainstorm a broad range of ideas.
- Provide context and steer AI with examples or options already considered or ruled out.
- Treat AI interaction as iterative; continuously refine prompts.
Weigh Pros and Cons
- Input comprehensive data such as customer personas and Northstar metrics.
- Ask AI to list all possible courses of action, including overlooked options.
- Create structured comparisons (e.g., tables) weighing pros and cons.
- Combine AI insights with human judgment to make final decisions.
- Document alternatives and rationale for transparency and team alignment.
Identify Blind Spots
- Upload draft strategies or memos for AI critique.
- Ask AI to identify unintended consequences, risks, and suggest improvements.
- Evaluate AI feedback critically but remain open to novel insights.
- Use findings to strengthen risk mitigation and prepare for counterarguments.

2. Using AI to Optimize Daily Productivity and Execution

Breaking Down Big Goals into Actionable Tasks Use prompt templates to prime AI with context and ask clarifying questions before solutioning. For example, transform vague goals like “improve stakeholder management” into specific, manageable tasks.
Daily Planning and Time Management Use AI to create optimized daily schedules based on personalized inputs such as:
- Energy levels
- Task durations
- Priorities and goals

Emphasize detailed, granular input to improve AI output quality. Time-boxing and calendar management are critical for PM productivity.

General Recommendation Experiment with different AI tools and models to find what fits your workflow best.

3. Using AI to Analyze User Feedback and Data

Context PMs often need to analyze large volumes of qualitative data (e.g., user comments, survey responses) without dedicated data science resources.
Case Study: YouTube “Super Thanks” Feature Manual analysis of approximately 1,000 comments took 20–40 hours. Using GPT-4 reduced this time to 30–45 minutes.
Process for AI-Assisted Feedback Analysis
1. Prepare data: clean, filter spam/non-English comments, label columns clearly.
2. Upload CSV/spreadsheet to an LLM-enabled tool with code interpreter (e.g., ChatGPT Advanced).
3. Use detailed prompts to:
  - Identify themes/categories (aim for mutually exclusive and collectively exhaustive).
  - Sort/tag comments into categories (few-shot learning with examples improves accuracy).
  - Generate summaries, memos, and visualizations (graphs, pie charts).
4. Always review AI output for accuracy; expect some misclassifications.
Benefits
- Massive reduction in time and effort.
- Enables PMs to focus on strategic insights rather than manual data wrangling.

Actionable Recommendations & Best Practices

Treat AI as an iterative, interactive partner rather than a one-off tool.
Provide detailed context and clear instructions to maximize AI effectiveness.
Combine AI outputs with human judgment; maintain skepticism but stay open-minded.
Document AI-assisted decisions thoroughly for team transparency and alignment.
Use AI to free up time for high-value strategic work and relationship-building.
Experiment with multiple AI models/tools to find the best fit for different tasks.
Follow company policies regarding AI usage and data privacy.

Key Metrics and KPIs Mentioned

No explicit numeric KPIs or revenue targets discussed.
Productivity gain implied: 10x improvement in time spent on tasks like user feedback analysis (from 20–40 hours down to ~30–45 minutes).
Emphasis on qualitative improvement in decision-making speed, risk mitigation, and strategic clarity.

Tools and Platforms Referenced

GPT-4 (ChatGPT Premium, GPT-4 Playground)
Claude, Perplexity (alternative LLMs)
Google Sheets (data cleaning, language detection)
ChatGPT Advanced with Code Interpreter for data analysis
Catalyst.ai (AI project management assistant, in closed beta)

Presenters / Sources

Samantha Stevens — AI Executive, Product School Entrepreneur in Residence, founder of Catalyst, former PM at American Express, Tinder, Google, and YouTube.

This webinar offers a practical playbook for product managers to integrate AI into strategic planning, daily execution, and user feedback analysis. It emphasizes iterative human-AI collaboration and detailed contextual inputs to unlock productivity and decision quality gains.