You are NOT an AI Product Manager IF you can't solve problems…
You are NOT an AI Product Manager IF you can't solve problems…
Be the entrepreneur of your product.
Before starting: If you’ve found my posts valuable, consider supporting my work. While I’m not accepting payments, you can help by sharing, liking, and commenting on my LinkedIn posts introducing this issue. This helps me reach more people on this journey. Thank you for supporting and motivating me to continue sharing my experience with you. Thanks for being part of this community ❤️.
#beyondAI
The only skill I truly care about when hiring AI Product Managers is problem-solving. And I'm not just looking for buzzwords listed on a CV. I want to see tangible, real-life examples that prove their problem-solving mentality.
In our field, challenges are abundant and complex. You know, I always talk about the Double Trio, which keeps our adrenaline levels high. That's why I value a mindset capable of dissecting issues, innovating solutions, and transforming obstacles into stepping stones. Fancy terminology and theoretical knowledge alone do not impress me. What truly captures my attention is an AI PM who can demonstrate their ability to navigate the intricate landscape of AI product development and management.
Even when I talk with aspiring AI Product Managers who have experience with other types of digital products, or even no product management experience at all, I emphasize the importance of showcasing their problem-solving skills in their own domains. I would rather hire a Product Manager without specific AI skills but with extraordinary problem-solving abilities than someone who knows AI but lacks that crucial skill.
In AI product ambitions, there are plenty of reasons why they fail. So, you will always impress me or any other hiring manager when you demonstrate that if the project is about to fail, you at least went through the effort to solve the problem.
Show me how you took an AI product with lackluster user engagement metrics and transformed it into a success story. Walk me through the steps you took to identify bottlenecks, propose creative solutions, and implement changes that drove engagement metrics through the roof. Let me hear about the collaboration with your team, the analytical thinking you employed, and the resourcefulness that led to results.
Tell me about the time you faced data privacy concerns head-on. Explain how you didn't just follow regulations blindly but actively sought innovative ways to enhance data privacy while preserving model performance. Share how you collaborated with legal and technical teams to create a solution that satisfied both compliance requirements and customer trust.
Narrate your experience of addressing performance issues in an AI system. Describe the strategies you and the rest of the team employed to optimize algorithms, streamline processes, and achieve a balance between speed and accuracy. Paint a picture of the challenges you encountered, the decisions you made, and the persistence that paid off in the end.
Show me how you took an AI product that was struggling with negative customer feedback and turned it into a user-favorite. Walk me through the process of how you collected, analyzed, and interpreted customer feedback. Describe the steps you took to identify common pain points and areas for improvement. Explain how you worked closely with your team to develop and implement solutions that addressed these issues. Let me hear about the innovative methods you used to gather insights, the collaborative spirit that drove the changes, and the tangible improvements in customer satisfaction and retention.
Tell me about the time you managed an AI product facing scalability issues as it gained popularity. Describe how you identified the limitations in your current infrastructure and the impact it had on user experience. Walk me through your approach to designing a scalable solution, whether it involved optimizing existing resources, integrating new technologies, or re-architecting the system. Share the collaborative efforts with your engineering team, the strategic planning involved, and the successful implementation that allowed the product to handle increased load without compromising performance.
Narrate your experience with an AI product that raised ethical concerns among stakeholders and users. Explain how you recognized the ethical implications of your product's use and the steps you took to address them. Describe how you engaged with diverse teams, including ethicists, engineers, and user representatives, to develop guidelines and safeguards. Share how you balanced ethical considerations with business goals, ensuring the product remained both responsible and effective. Highlight the transparency measures you implemented and the trust you built with your user base by demonstrating a commitment to ethical AI practices.
Tell me about a time when you had to revamp an AI product’s user interface to improve usability and user experience. Describe the process of gathering user feedback, conducting usability tests, and identifying key areas for improvement. Explain how you collaborated with UX designers and developers to create a more intuitive and engaging interface, and share the impact of these changes on user satisfaction and engagement.
Show me how you addressed a critical security vulnerability in an AI product. Detail the steps you took to identify the vulnerability, assess its potential impact, and develop a mitigation plan. Describe how you worked with security experts and your development team to implement robust security measures, and explain how you communicated these changes to users to maintain their trust.
Tell me about a time when you had to manage cross-functional teams to integrate a new feature into an AI product. Explain how you coordinated efforts between data scientists, engineers, marketers, and other stakeholders to ensure a seamless integration. Highlight the challenges you faced, such as conflicting priorities or resource constraints, and how you overcame them to deliver a successful feature launch.
Describe an instance where you had to pivot the direction of an AI product based on market feedback or business process changes. Explain the process of gathering and analyzing data, identifying new opportunities or threats, and making strategic decisions to pivot the product. Share how you communicated this pivot to your team and stakeholders, and the results of this strategic shift.
Tell me how you addressed a significant drop in user engagement due to changes in market trends, business processes, or user behaviors. Describe how you analyzed user data to understand the root cause of the drop, and the strategies you implemented to re-engage users. Highlight the collaboration with your marketing and product teams to create campaigns or product adjustments that brought users back.
Tell me about a time when you had to balance innovation with risk management in an AI project. Describe how you identified potential risks associated with a new technology or approach, and the measures you took to mitigate these risks. Explain how you communicated the balance between innovation and risk to your team and stakeholders, ensuring that the project moved forward while minimizing potential negative impacts.
Your roadmapping skills, Jira expertise, and Udacity and Coursera certifications don't concern me. What truly matters is finding someone who recognizes that the responsibilities of Data Scientists, Data Engineers, UX Designers, Privacy Managers, and everyone else contributing to product development ultimately fall within your realm of accountability.
Ensure that problems are resolved, whether by them or by your own initiative—as long as it's within legal bounds and maintains a courteous approach, any method is fair game. 🏆
If you're the AI PM in charge of the product—and that's your gig—then any issue that crops up with the product is on your plate. It's all about owning it. That's why you're the one taking home the paycheck, and honestly, it's a pretty good deal!
So please don’t be that PM who complains about hurdles and difficulties within company processes, saying they are slow and hindering your progress. Don’t be the one who gives up when business stakeholders are not paying attention to your work because of their other priorities.
Be the one who finds solutions.
Also for those, … no, I’m sorry: Especially for those that go beyond AI.
Be the entrepreneur of your product.
JBK 🕊️
P.S and a friendly reminder:
If you’ve found my posts valuable, consider supporting my work. While I’m not accepting payments, you can help by sharing, liking, and commenting on my LinkedIn posts introducing this issue. This helps me reach more people on this journey.
Thank you for supporting and motivating me to continue sharing my experience with you. Thanks for being part of this community ❤️.