Deepak Mukunthu
Senior Director of Product, Generative AI Platform (Einstein GPT), Salesforce
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • February 22
Aspiring technical product managers should consider developing the following skills and background: 1. Technical expertise: A strong understanding of technology and the ability to communicate effectively with technical teams is essential for technical product managers. Familiarity with coding languages, software development methodologies, and industry-standard tools can help aspiring technical product managers gain credibility with their teams. 2. Customer empathy: Technical product managers should have a deep understanding of their customers' needs and pain points. They should be able to conduct customer research and use this information to inform their product development decisions. 3. Business acumen: Technical product managers should have a good understanding of the business context in which their products operate. This includes understanding the competitive landscape, market trends, and financial metrics. They should be able to use this information to make informed decisions about their product development priorities. 4. Analytical skills: Technical product managers should be able to analyze data, draw insights from it and use it to make informed decisions. 5. Communication skills: Technical product managers need to be able to communicate effectively with both technical and non-technical stakeholders. They should be able to explain complex technical concepts in a way that is easy for non-technical stakeholders to understand, and be able to negotiate and influence stakeholders to achieve their product goals.
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • September 28
It really depends on the phase of your product definition/execution, but at a high level, you spend ~30% of your time working with customers, ~20% of your time in market research, compete analysis, drafting vision/strategy, ~20% of your time working with Engineering teams on execution and rest of your time working with cross-functional teams managing the product lifecycle including ideation, design, customer/user studies, legal/privacy/security, documentation, marketing, sales.
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • September 29
From metrics perspective, it's no different from standard product metrics. I've seen many different metrics frameworks being used, all of which essentially boil down to these 4 metric categories: 1. Operational metrics: Is the product functioning as expected? Success rates, Latency etc. 2. Usage metrics: Is the product being used? DAU/MAU, Frequency of use, customer retention/churn, Requests/sec, data volume etc. 3. Satisfaction metrics: Are customers satisfied? In-product feedback (thumbs-up, thumbs-down), NPS scores via surveys etc. 4. Impact metrics: How is the product helping customers achieve business impact? This is subjective and need to be defined per product and is also typically based on customer scenarios.
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • September 28
Depending on the phase of the project or lifecycle stage of the product, a product manager collaborates with many different functions. During intial phases, you work with customer/account teams to understand demand, then with designers and user research teams to perform user research, usability studies, focus groups to understand and define. Once you an MVP, work with customers and account teams to get feedback. When you are ready to ship public offering, work with documentation and marketing team. As you scale sales, you work with sales/field enablement team to streamline that process. Through out this journey, you work with legal, compliance, privacy and security champs to get your approach, design and product reviewed.
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • September 29
As a Product Manager, you are responsible for: 1. Defining product vision/strategy/roadmap based on deep understand of customers, business and competitive landscape 2. Working with various cross-functional stakeholders and partners to execute on your roadmap and ship product/features 3. Establishing processes to gather customer feedback to continuously evolve the product Platform Product Manager role is very different except the product is a platform and hence your customers are the ones using the platform. Exact customer persona will depend on the specifics of the platform. Success is typically measured by adoption of your platform, customer satisfaction and the business impact your platform has. See this question for more details on metrics: https://sharebird.com/h/product-management/q/what-metrics-do-you-focus-on-as-platform-product-manager
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • June 28
Assuming you are specifically interested in AI product management, I would suggest these approaches to get started with ML. While I was new to ML/AI, these approaches helped me. 1. Online courses 2. Part-time certifications 3. Conferences 4. Kaggle 5. Publish your work 6. Internship/Volunteering I covered this in my session on AI/ML Product Management: https://www.linkedin.com/video/event/urn:li:ugcPost:6929801568753971200/ If you are looking for guidance on general product management, let me know. There is a lot of material online and I can point you to.
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • September 28
If you are referring to individual products using capabilities from broader platform, I would categorize those products are target customer scenarios that the platform enables. As you come up with the roadmap for your platform, you need to work closely with all those scenario owners / customers and align your roadmap to enable those scenarios to succeed. While you decide on platform capabilities based on deep understanding of customer scenarios, if you align the execution of your roadmap with the scenario timeline, you have a higher chances of success. In other words, don't just build a platform but line up your execution to align with the consuming scenario so you can demonstrate clear business impact. Different companies/teams use differnt tools to align roadmaps. More than aligning roadmaps, you align on success metrics (you can use frameworks like OKR framework) and your execution dependencies/timelines (you can use any schedule tracking tools or excel simplistically).
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • September 29
As a Product Manager, you are responsible for: 1. Defining product vision/strategy/roadmap based on deep understand of customers, business and competitive landscape 2. Working with various cross-functional stakeholders and partners to execute on your roadmap and ship product/features 3. Establishing processes to gather customer feedback to continuously evolve the product Platform Product Manager role is very different except the product is a platform and hence your customers are the ones using the platform. Exact customer persona will depend on the specifics of the platform. Success is typically measured by adoption of your platform, customer satisfaction and the business impact your platform has. See this question for more details on metrics: https://sharebird.com/h/product-management/q/what-metrics-do-you-focus-on-as-platform-product-manager
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • February 22
The ideal product manager-to-engineer ratio can vary depending on the nature and complexity of the products being developed, the size and stage of the organization, and other factors such as the development process, company culture, and resources available. However, a common rule of thumb is to aim for a ratio of 1 product manager to 8-10 engineers. This ratio provides enough product management oversight and guidance to the engineering team while allowing engineers to have enough autonomy and ownership over their work. As the organization scales, this ratio can be adjusted to maintain the appropriate level of oversight and support for the engineering team.
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Deepak Mukunthu
Salesforce Senior Director of Product, Generative AI Platform (Einstein GPT) • September 29
Yes, customer feedback is one of the most critical inputs to prioritization. For Platforms, you typically focus on 2 sets of customers: 1. Direct customers: These are users of the platform. Exact customer persona will depend on the specifics of the platform. For e.g., if you are building an ML platform, your typical persona would be data scientists, ML engineers. 2. Indirect customers: These are users who will see the value of the work your direct customers are doing. Depending on whether you are building an internal or external facing platform, level of focus on these 2 segments of customers will vary. As Platform Product Manager, you focus on direct customers using your platform but also focus on the business impact it has on indirect customers. Hence, it is recommended that you have a good line of sight on business impact as part of your platform roadmap.
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Credentials & Highlights
Senior Director of Product, Generative AI Platform (Einstein GPT) at Salesforce
Product Management AMA Contributor
Top 10 Product Management Contributor
Lives In Redmond, Washington, United States
Knows About AI Product Management, Technical Product Management