Inside my typical week as an AI Product Manager

Harnessing the Double Trio Framework - and a Cup of Coffee ☕️ - to Drive AI Success

JaserBK

Jun 16, 2024

#beyondAI

At times when it’s really quiet and I’m listening closely as an AI Product Manager, I hear the Double Trio arguing:

Data: Hey AI, you know you need me, right?

AI: Please, Data, without me, you’re just a dusty pile of numbers in an IT dungeon, unloved and forgotten.

IT: Exactly, AI. And without me, you’d just be a theoretical concept in some obscure research paper.

Governance: Ah, the rebels. Without my rules, you’d all be starring in a sci-fi disaster movie.

Business: You’re all hilarious. Without me, nobody would even care about your existence!

People: Business is right, but without us, there is no data, AI, IT, Governance, or Business.

And then suddenly, out of nowhere, someone asks:

Who wants coffee? ☕️

As AI Product Managers, our ultimate goal is to bring everyone together, leveraging our gravitational power to build AI solutions that people need and are willing to pay for. For me, that gravitational power translates to many sessions with various stakeholders from all dimensions of the Double Trio, often with a cup of coffee or tea in hand.

With this issue, I'd like to invite you to a coffee (or tea) to experience a typical week in my life as an AI Product Manager.

So, back to the question: Who wants a coffee? ☕️

Happy reading 🛋️

A Week in My Life as an Internal AI Product Manager: Embracing the Double Trio

My weekdays start quite early, not because I need to start working early but to prepare myself mentally and physically for the day. This routine has evolved over the years and has become integral to my performance. I love my routine, and even on days when I can't wake up early, I still make time for it. I like to start my day smoothly and slowly with workouts, yoga sessions, a shower, and a cup of coffee. I also set aside time to write a bit. In fact, this piece of text was written while I enjoyed my first and last coffee of the day.

My workdays are quite intense, and the Double Trio always demands my attention. Not everything goes as planned, but I've found that the better I am at establishing a morning routine, the better I can handle setbacks, personal mistakes, and motivational lows throughout the day. It actually helps me be a more balanced husband too—at least that's what my wife says 🧘🏻 ☺️.

I mention this upfront to emphasize that no matter how well-educated and experienced you are as an AI Product Manager, you need balance outside of work to perform at a high level and avoid becoming overwhelmed by the intense nature of our profession. Sure, there will be slower weeks and less pressure-filled times, but these are more the exception than the rule.

So, let’s take a look at how a typical workweek unfolds as I strive to transform an AI solution into an AI product.

Monday

The week begins with the sun peeking through the curtains, my morning routine in full swing, and a strong cup of coffee in hand. As an internal AI Product Manager, I quickly review the week’s agenda, knowing that balancing the Technical Trio (Data, IT, AI) and the Operational Trio (Governance, Business, People) keeps my adrenaline levels high. Today, I’m particularly excited about the progress we might make with our AI Model Development.

9:15 AM - Data Quality Review

This week kicks off with the data team. A major internal project is underway, and we’re scrutinizing the latest data sets. We discover some inconsistencies, causing a bit of a stir. By noon, we’ve identified the source of the problem and set corrective measures in motion. It’s clear we need to tighten our data governance practices, as these data sets will be crucial for our future AI Model Development.

1:00 PM - IT Infrastructure Planning

The IT department briefs me on upcoming infrastructure upgrades. We need to ensure our systems can scale to handle increased AI processing demands. Mid-meeting, we hit a roadblock: budget constraints. We brainstorm cost-effective solutions, like leveraging cloud resources more efficiently. It’s a tense but productive session.

3:00 PM - AI Model Refinement

Later, I join the data scientists to refine our AI models. The algorithms are performing well and are better in precision than expected, but integration challenges into target systems persist. We decide to bring in an expert from another team for a second opinion. It’s a bit of a setback, but having fresh eyes on the problem could be the breakthrough we need.

5:00 PM - Recap and Preparing for Tomorrow

The day wraps up with sorting and refining my notes taken during the day and checking if tomorrow or the following days need any special preparation. I arrange my tasks by the Dimensions of the Double Trio and also check if there is a need to put some of the tasks into our Teams Jira Backlog.

Tuesday

This day starts even earlier with my usual routine of workouts, yoga, and coffee. Today, I spend extra time reviewing the notes and tasks for the day, knowing that a crucial sprint planning session is coming up tomorrow.

9:00 AM - Team Standup

I join the team standup to sync up with everyone on their current tasks. This meeting helps us align our efforts and address any immediate concerns. It’s a quick but essential start to the collaborative day.

10:00 AM - Data Governance Review

Following the data quality issues identified yesterday, I meet with the data governance team. We discuss tightening our data policies and implementing more robust checks. This meeting is critical to ensure the integrity of our data going forward.

1:00 PM - Business Stakeholder Meeting

In the afternoon, I meet with business stakeholders to discuss the impact of our AI initiatives. We review key performance indicators and potential areas of improvement. These insights are crucial for aligning our technical work with business objectives.

3:00 PM - Preparing for Sprint Planning

I dedicate the rest of the afternoon to preparing for tomorrow's sprint planning session. This involves reviewing current progress, identifying key areas of focus, and gathering input from various team members and the other Double Trios. I also prepare detailed documentation to ensure the session runs smoothly.

6:00 PM - Wrap Up

I wrap up the day by organizing my notes and ensuring everything is set for the intensive planning session tomorrow. It’s a long day, but preparation is key to a productive sprint planning. Fortunately, my habit of organizing sprint planning sessions daily allows me to turn off my laptop earlier than I used to the day before a planning session earlier in my career 🤣.

Wednesday

Despite the busy schedule ahead, I start my day with my usual routine to maintain focus and balance.

9:00 AM - Sprint Planning Session

The four-hour sprint planning session kicks off with data scientists and data engineers. We review the past sprint, discuss challenges, and plan the next three weeks in detail. This session is intense, involving deep dives into technical issues and setting clear goals. Thanks to our typical refinement sessions during our three-week sprints, we are quite productive and efficient.

1:00 PM - Extra Long Break

After the long planning session, I take a well-deserved extra-long lunch break and do something completely random, maybe not even work-related. Sometimes, I incorporate elements of my morning routine into this break. This is absolutely mandatory for me, as these four-hour sessions are so exhaustive that if I want to stay productive for the rest of the day, I need to refill my energy quickly. This is my solution for that.

1:45 PM - Follow-Up Meetings

Post-lunch, I have follow-up meetings with individual team members to clarify tasks and answer any questions arising from the planning session. Ensuring everyone is on the same page is crucial. My experience shows that allowing everyone to take time after the intense session to digest the happenings and then follow up the same day is a good practice. It clarifies any misunderstandings or inconsistencies that may have come up.

4:00 PM - Governance and Compliance Check-In

I have a brief meeting with the governance team to ensure that our new sprint goals align with regulatory and compliance requirements. This is an ongoing task to prevent any compliance issues down the line, focusing only on tasks identified to have some relation to governance or compliance. But these don't come up after each planning.

5:00 PM - End of Day Recap

I spend the last hour of the day organizing my notes from the sprint planning session and updating our Jira backlog. This is not an enjoyable task for the end of the day and sometimes gets postponed to tomorrow 😃, but it is essential to keep our tasks transparent and trackable.

Thursday

Another early start with my routine. Today, I'm tempted to have a second coffee, but I resist. Let’s get started.

9:00 AM - Standup Meeting

The day begins with the daily standup meeting, where the team provides updates on their progress and any blockers they’re facing. Actually, we can’t call them daily, as we only have them twice a week and typically not the day after a planning session. Seems like I’ve forgotten to delete this session from our calendars. My fault, team 🥰.

10:00 AM - AI Strategy Session

I meet with the senior leadership team to discuss long-term AI strategy. We evaluate current projects, explore new opportunities, and align our AI initiatives with the company’s strategic goals. I present our latest progress on evolving our AI solution into an AI product and provide timelines for expected results for the AI use case for our business stakeholders. I always have a standard slide deck, where I just need to adjust the figures. I am a genius 🤓.

1:00 PM - Lunch with a Mentor

I take a break to have lunch with a mentor. These sessions are invaluable for gaining insights and advice on managing complex AI projects from both technical and organizational perspectives, as well as for personal career development. What started as casual virtual coffee sessions has evolved into a mentoring relationship, though I still need to officially tell him he’s become my mentor 😄.

2:00 PM - Model Performance Review

In the afternoon, I sit down with the data science team to review the performance of our current AI models after integrating additional data. We analyze results, discuss any discrepancies, and plan adjustments to improve accuracy and efficiency. They are the experts, and I challenge them as much as my knowledge allows. However, the final decision about the direction—provided it aligns with our goals and restrictions—is theirs. I’m lucky to have these experts on my side.

4:00 PM - Training and Development

I attend a training session focused on the latest AI technologies and methodologies. This time, it’s about advanced techniques to derive causation from AI models. I chose this because our stakeholders need more transparency from our AI models and want to understand why the model reaches specific decisions.

5:30 PM - Wind Down and Planning

The day ends with winding down my activities and planning for the final day of the week. It’s been a tough one so far. I review upcoming tasks and ensure everything is in place for a productive Friday. I am pretty sure I just believe everything is in place; typically, Fridays always have some surprises for me. I am skeptical but turn off the lights. See you tomorrow.

Friday

I start my last workday of the week with an extra-long mental training integrated into my routine. I’m energized and focused, but still skeptical. Luckily, my first meeting today starts at 10:00 AM, so I have some time to prepare for any surprises.

10:00 AM - Project Deep Dives

I spend the morning in several deep dive sessions reviewing the progress of our key AI projects. We have some ongoing AI-related data projects, a major IT infrastructure progress update, and one about the latest implementation into our AI and data governance. We discuss challenges, successes, and next steps. These sessions typically give me a bird's-eye view of all relevant aspects my product and team depend on. Usually, these sessions are the reason I am so skeptical about Fridays, but this time, everything went well.

1:00 PM - Networking Lunch

I have a networking lunch with colleagues from different departments. These sessions are great for building relationships and gaining diverse perspectives on our AI initiatives. And you know what? I think I even found a second AI use case that could potentially be enabled with our AI product. I quickly pitched it, and we will have a follow-up session early next week. Maybe Fridays aren’t so bad after all.

2:30 PM - Unexpected Call from a Data Scientist

“Hey Jaser, listen…”, when my Data Scientist calls me unexpectedly and starts with this, I normally brace myself for bad news, something like: “Our latest AI performance progress was actually a false positive,” translating to, “Our latest AI performances were not correct.” But this time, he said: “We were experimenting with a new model architecture and the first results are promising. It could help us enable far more AI use cases.”

Well, I think this Friday is actually a great outlier, and it’s much appreciated that it turned out to be an outlier this week. Thank you.

3:30 PM - Wrapping Up the Week

I spend the final hours wrapping up the week’s work, organizing my notes, and preparing a brief report for senior management. I also set my priorities for the following week.

6:00 PM - Unwind and Relax

With the workweek officially over, I unwind and relax, reflecting on the week’s achievements and recharging for the next one. And the biggest realization: sometimes even outliers can be a blessing in the life of an AI Product Manager.

As an internal AI Product Manager, each week is a journey filled with ups and downs. The Double Trio framework guides me through the complexities, ensuring that all aspects of AI product development are balanced and aligned. Here’s to another week of bridging the technical and operational worlds, making sure our AI products are built to last and thrive.

And yes, I’ll take that second coffee now! ☕️

JBK 🕊

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