8400+ hours unlocked with AI automation
Real-world stories of PMs using AI to automate routine tasks and boost their productivity
For nearly two years, I've been helping product managers use AI to boost their productivity.
When I tell people AI can reduce time by 80% or more, many find it hard to believe. They nod politely, but their expressions betray their skepticism.
So allow me to show you. After all, seeing is believing.
Today, I’m sharing real stories from my latest 10x PM Productivity with AI Bootcamp. In just three weeks, this cohort automated 15 routine tasks that will save them over 8,000 annualized hours.
These stories come from a diverse group—product managers, product owners, engineering managers, directors, VPs, and a CTO.
So, let me step back and let these examples do the talking.
#1. Jon Tallon
VP Engineering, symplr
Project Planning Automation
Jon Tallon focused on enhancing the thoroughness and quality of project plans. By automating the research of vague project descriptions and turning them into detailed project plans, Jon was able to identify potential compliance issues and ensure comprehensive project planning.
Key Benefits:
Time Saved: Saves about 1 to 1.5 days per project. Assuming 100 projects a year, this results in an estimated savings of 3600 hours annually.
Improved Quality: Identifies potential missing tasks and ensures comprehensive project planning.
Efficiency: Improves overall project quality by including compliance considerations.
Motivation: To improve the thoroughness and quality of project plans.
Memorable Quote:
"By giving the AI different roles for different tasks, I can now get better quality responses every time. It's honing in on what I'm looking for.”
#2. Alex Marciante
Product Manager, symplr
Feature Development Automation
Alex Marciante tackled the challenge of standardizing and streamlining feature documentation. Alex leveraged AI to automate the creation of problem statements, benefit hypotheses, acceptance criteria, release notes, sales team copy, executive summaries, and support team summaries from feature descriptions.
Key Benefits:
Time Saved: Saves about 1 hour per feature. Alex does 400 features annually, resulting in an estimated savings of 400 hours annually.
Improved Quality: Significantly improves the quality and consistency of feature descriptions.
Efficiency: Provides a reliable and efficient workflow.
Motivation: To streamline and standardize feature documentation, ensuring all necessary details are included and reducing the chance of missing tasks.
Memorable Quote:
"It's really interesting what came back. Is it 100%? No, but is it 90% there? You bet it is.”
#3. Jim Anderson
Senior Product Manager, Skillsoft
RFP (Request for Proposal) Response Automation
Jim Anderson focused on reducing the time and effort required to respond to RFPs. By creating an AI to respond using a library of previous responses, Jim drastically cut down response times and improved consistency.
Key Benefits:
Time Saved: The goal is to reduce response time from 20 days to 1 day.
Improved Quality: Ensures high accuracy and consistency in responses.
Efficiency: Allows AES and other team members to quickly generate responses and enhances overall proposal quality.
Motivation: To reduce the time and effort required to respond to RFPs.
Memorable Quote:
"Taking this into our own ChatGPT within our system, and I've been pretty impressed so far with the answers."
#4. Ken Manthorne
Senior Product Manager, symplr
Feature Description Enhancement
Ken focused on improving the clarity and quality of feature descriptions migrated from JIRA to Aha!. Ken significantly enhanced documentation quality by automating the expansion and elaboration of feature descriptions, including problem statements, benefits, and overviews.
Key Benefits:
Time Saved: Saves approximately 2-3 hours per feature. Potential savings of 100-150 hours per month, or 1200-1800 hours annually.
Improved Quality: Enhances clarity and detail in feature descriptions.
Efficiency: Improves documentation quality and facilitates better communication with stakeholders.
Motivation: To clean up and standardize feature descriptions migrated from JIRA to Aha!.
Memorable Quote:
"I ran this same exact prompt across all the AIs. Like that we can use this across AIs. And I really liked using Claude. It gave me the best answer.”
#5. Jeffrey Peterson
CTO, symplr
Job Description Generation
Jeffrey focused on streamlining the creation of job descriptions by automating the process. By providing context and format specifications, Jeffrey quickly and consistently generated job descriptions for various roles.
Key Benefits:
Time Saved: Automates the creation of job descriptions, significantly reducing the time required to generate them manually.
Improved Quality: Ensures standardized job descriptions that adhere to company formats and standards.
Efficiency: Quick generation of job descriptions allows for timely hiring processes and consistent documentation.
Motivation: To quickly and consistently generate job descriptions for various roles.
#6. Ben Nuque
Snr. Product Manager, CSA Group
Hypothesis and Testing Plan Generation
Ben focused on quickly generating and validating hypotheses with industry benchmarks. Ben improved the decision-making process by automating the creation of hypotheses, testing plans, and finding referential sites for best practices.
Key Benefits:
Time Saved: Generates three hypotheses within an hour, a process that could take several days manually. Assuming this is done monthly, the estimated annual savings is approximately 288 hours.
Improved Quality: Provides validated hypotheses with industry benchmarks.
Efficiency: Offers cost estimation and improves overall decision-making.
Motivation: To quickly generate and validate hypotheses with industry benchmarks.
Memorable Quote:
"The generated hypotheses not only saved time but also provided insights I might not have considered otherwise"
#7. Pirmin Froehlicher
Snr Director Products, 4G Clinical
Release Notes Creation
Pirmin focused on improving the efficiency and consistency of release note creation in a regulated industry. By automating the generation of customer-facing release notes from JIRA descriptions and acceptance criteria, Pirmin was able to streamline the process and ensure high-quality documentation.
Key Benefits:
Time Saved: Saves 1-2 days per release. Assuming 6 releases per year, this results in an estimated savings of 48-96 hours annually.
Improved Quality: Provides more consistent and accurate release notes.
Efficiency: Reduces workload on senior PMs and speeds up the review process.
Motivation: To improve the efficiency and consistency of release note creation in a regulated industry.
Memorable Quote:
“Each of my four features I have a nice description. It's not 100% that but it's a really, really good starting point. Next, I want to try feeding it many tickets at a time and see if it works”
#9. Smita Singh
VP of Engineering, symplr
Employee Survey Analysis
Smith focused on summarizing employee survey data to find patterns and provide actionable insights. Using AI to analyze and summarize feedback from employee surveys, Smita quickly identifed key themes and areas for improvement.
Key Benefits:
Time Saved: Summarizes employee feedback from 200 rows in just 10 minutes, a task that typically takes a couple of hours.
Improved Quality: Identifies patterns and key themes in the feedback.
Efficiency: Provides actionable insights for improving employee satisfaction.
Motivation: To efficiently analyze employee survey data and extract meaningful insights.
Memorable Quote:
"It usually takes me a couple of hours to go through them and find patterns. When I uploaded it in Claude and asked to summarize, it took me like 10 minutes."
#10. Dinesh Thiyagaranjan
Group Product Manager, symplr
Support Defect Analysis
Dinesh focused on analyzing support defects raised over the last six months to identify patterns and trends, ultimately aiming to prevent such defects in the future. By using AI to automate this analysis, Dinesh drastically reduced the time required to perform this task.
Key Benefits:
Time Saved: Reduced analysis time from six hours over a week to just 20 minutes. Assuming 12 analyses a year, that is 68 hours saved.
Improved Quality: Identified common trends and patterns in defects.
Efficiency: Provided actionable recommendations and validated the accuracy of trends with at least 90% accuracy.
Motivation: To identify patterns and trends in support defects to prevent future issues.
Memorable Quote:
"The patterns that got recognized based on the inputs were impressive. The recommendations or the action plan that the LLM came up with were even more impressive."
#11. Vidya Balasubramanian
Product Leader, Startup
Functional Ideas Generation
Vidya focused on generating functional ideas to aid in product development. By leveraging AI to create a list of functional ideas, including user stories and acceptance criteria, Vidya tapped into the creative capabilities of AI to enhance her ideation process.
Key Benefits:
Time Saved: Generates a diverse set of functional ideas quickly, saving several hours of brainstorming and ideation.
Improved Quality: Provides detailed user stories and acceptance criteria that enhance product development.
Creativity: Expands creative possibilities by tapping into AI-generated ideas.
Motivation: To generate a wide range of functional ideas quickly and efficiently for product development.
Memorable Quote:
"I felt it was really good. I was tapping into ChatGPT’s creativity because a lot of the functional ideas were not what I was thinking about."
#12. Nydia Boswell
Director Product Management, symplr
Customer Advisory Board Welcome Letter Generation
Nydia focused on automating the creation of welcome letters for a Customer Advisory Board. Using AI to generate these letters, Nydia efficiently produced customer-facing copy.
Key Benefits:
Time Saved: Automates the creation of customer-facing welcome letters, significantly reducing the time required to manually write them.
Improved Quality: Ensures well-framed and concise communication.
Efficiency: Provides a reliable workflow for generating consistent and professional customer communications.
Motivation: To simplify and expedite the creation of customer-facing welcome letters, which is typically a task that can be delayed.
Memorable Quote:
"Whenever it comes to customer-facing copy, that is a task I can procrastinate, so this definitely made it easier."
#13. Jennifer Kendrick
Senior Product Manager
Epic and User Story Generation
Jennifer focused on streamlining the creation of epics and user stories. By automating this process for a given problem, Jennifer was able to ensure clear, testable components and improve ideation quality.
Key Benefits:
Time Saved: Saves several days per project; automation process takes less than an hour. Estimated annual savings based on frequent use.
Improved Quality: Produces highly detailed and concise epics, comparable to or better than manually written ones.
Efficiency: Ensures comprehensive and organized documentation, facilitating a smoother development process.
Motivation: To streamline the creation of epics and user stories with clear, testable components.
Memorable Quote: "Rather than trying to put everything in one prompt, breaking it down into micro tasks worked a lot better. There were some things that came up that I might not have at first glance even considered.
#14. Cheyenne Roinestad
Technical Product Owner, symplr
Meeting Transcript Analysis
Cheyenne Roinestad focused on improving the management and summarization of meeting notes. Cheyenne significantly enhanced her meeting productivity by automating the extraction of positive feedback, negative feedback, summary, key takeaways, and problem statements from meeting transcripts.
Key Benefits:
Time Saved: Automates the creation of meeting recaps, allowing more time to focus on essential tasks.
Improved Quality: Brings substantial focus into events by providing structured and actionable summaries.
Efficiency: Reduces the time spent figuring out next steps.
Motivation: To better manage and summarize meeting notes, allowing for greater focus on the content during meetings.
Memorable Quote:
"This will speed up my ability to get recaps out and spend less time trying to figure out what I need to do next.”
#15. Chuck Warren
Principal Products Operations Manager, Skillsoft
Vendor Research Automation
Chuck focused on quickly providing a starting point for vendor selection and saving research time. Chuck automated the generation of a list of potential vendors and relevant details based on minimal input.
Key Benefits:
Time Saved: Saves at least 1-2 hours of initial research time. Assuming similar research twice a year, the estimated annual savings is approximately 24 hours.
Improved Quality: Quickly provides a starting point for vendor selection.
Efficiency: Enhances decision-making efficiency and reduces the need for extensive manual research.
Motivation: To quickly provide a starting point for vendor selection and save research time.
Memorable Quote:
"In a matter of few minutes, really. I had a list of decent vendors. Making it much easier to start the selection process. It easily saved an hour of other decent output that we kind of at least start a conversation."
The above success stories are the result of capstone projects completed in my 10x PM Productivity Bootcamp.
If you want to enjoy similar results, check out the 10x PM Productivity Bootcamp (next cohort starts 6/7). Details here.
Give it a try, and you’ll be amazed at what you can automate, how much time you can save, and deliver top-notch results with less effort.
Happy Building!
Whenever you are ready, here are 2 ways that I can help you:
#1. 10x Product Manager Productivity With AI Bootcamp (public): An intense 3-week bootcamp, where PMs learn how to leverage AI to save time, deliver top-notch work, and accelerate velocity. New cohort starts 6/7.
#2. 10x Product Teams Productivity With AI Bootcamp (private): Private version of the above bootcamp. 100% customized to your organization. Includes hackathons, coaching, mentoring, and executive playbacks.