Sean Lynch on balancing art and science, how Gen AI is like MS Excel, and agency product management
Product State Q&A
Sean Lynch is the Head of Product at MetaLab. He was formerly Director of Product Management and Strategy at Huge. He also held roles at BBYO and Deloitte.
EC: Leading Product at a Product Studio, how do you balance art and science?
SL: Finding the right balance between intuition and data can be challenging in product development. When you need to prove a business case or provide rationale, leaning into data is useful. However, to create a product that has soul and feels natural — leaning into the art is necessary.
This means using your instinct and truly embracing the signals around how, where, and when a product will be used.
From there, it’s about making a judgment call on whether the proposed product will ‘feel natural’ or ‘feel special’ in that environment.
This process might feel scary at first but the more revs you get under your belt the more comfortable you’ll get at trusting your instincts. You can always use data to fine-tune the details and back up your assumptions.
EC: What are some practical ways you’re using Gen AI?
SL: I’m not fully on the generative AI hype bandwagon yet. Having experimented with it many times, I don’t see it replacing us anytime soon. And frankly, we should not build it up in a way that makes people fearful.
Rather, we should think of it as a tool to free up our time and energy for work that has the greatest impact.
Here are a few areas I’m experimenting with:
Quickly validating completeness of feature definition - ‘What edge cases am I missing in [this onboarding experience]?’
Rapidly brief a team in on a new industry - ‘Tell me about [industry], who are the major players — and what are the current trends?’
Provide a starting place for a competitive/landscape audit - ‘Who are the top five competitors to [use case]?’
In my opinion, this use of Gen AI is no different than how we use Excel. When analyzing a data set, do you manually calculate the average? Or do you just use AVERAGE(). From there, you can formulate your insight that Excel can’t.
EC: What are the differences between internal vs external product management?
SL: Product managers come in all shapes and sizes. Countless articles have been published on this, but most don’t cover the ‘agency product manager’ — those who work in a professional services setting, and are hired by organizations to help them achieve their outcome.
From my perspective, there are two key differences between external PMs and those in-house:
In-house PMs typically have more expertise in the ongoing iteration of a Product. External PMs typically have more expertise getting a product from Zero to One or taking products through massive transformations. External PMs are often brought in when nothing exists to help a team stand up a product, or when a product needs a significant overhaul for it to be impactful.
In-house PMs typically have deep subject matter expertise in an industry and/or product type. External PMs have experience across product types and industries. This experience enables external PMs to bring a POV to a client that will differentiate them from their competitive set. They’re highly skilled at quickly understanding the nuances of a new vertical, but will also challenge the status quo.
From my perspective, the best time to bring in an external PM is when you’re looking to uncover your differentiation, ship your initial product, or take it through a major transformation. That’s where you’ll see the biggest value and impact from them.
Typically, the ongoing BAU iteration on a product is best handled by an in-house PM given their skill set.
However, when post-MVP iterative design and development are being done by a single agency partner/service provider, their PM can help ensure the team is operating at peak performance. The best setup here is to have an in-house Product leader who can pair with the agency PM.
“To create a product that has soul and feels natural — leaning into the art is necessary.”
- Sean Lynch
