Leader Spotlight: The shift from execution to strategic thinking, with Chantal Cox
Chantal Cox is Director of Product at LTK, a global technology platform. She started her career as a senior product manager at eBay and concurrently ran her own consultancy business for angel and Series A startups. Chantal then joined Credit Karma as a senior product manager before transitioning to Adobe, where she helped lead the Photoshop product. Before her current position at LTK, she served as Director of Product Management at Amazon and Senior Manager, Product Management at Meta.
In our conversation, Chantal talks about the shift from execution to strategic thinking within the product management function, especially as AI technology becomes prevalent. She discusses how she foresees the current product workforce re-skilling to meet new expectations and demands, as well as how she encourages her teams to use AI personally and professionally.
The shift of the PM role
The PM role is shifting from execution to strategic thinking. How does this pivot impact the way in which you grow your team?
It’s shifting now faster than I thought it would. I’ve noticed, having hired a few roles this past year, that my evaluation criteria have shifted. Also, there are still layoffs happening across all these huge companies, like Google, Meta, etc. People were focused on why we need so many PMs when AI can analyze users, do UXRs, write PRDs, etc. That streamlining will happen, but it’s not as aggressive or to the extent that it was after the first big AI wave.
Product management is no longer what it used to be, and it’s going to continue to shift. The PMs who are not upskilling will become redundant in modern tech companies. With that, there are a lot of unmet needs that AI still can’t get to. Yes, it can do UXR, but LLMs are just spitting things out that we already know. If someone wants to do something novel, that won’t be suggested by an AI. If it’s not written or published somewhere, the LLM won’t know about it.
Also, LLMs are not good at influencing and aligning execs. It can tell you this is what we need to do, but that doesn’t mean you need to do it. There are elements of risk, appetite for business, politics, and team dynamics at play that LLMs don’t know about. Same with morale. This new era of product management will surface the product managers who will shine through, and it’s going to really elevate the discipline.
You mentioned that your evaluation criteria for hiring PMs have shifted. How do you gauge these new PM skills in your hiring process?
I want to measure outcomes. I’m looking for someone who can make good decisions. Why should we do this? Instead of just building the thing that they’re asked to do, I need someone who can provide a decision and clarity to unlock options. Can they not only provide a recommendation on things to unblock, but also make good decisions around them?
Further, I look for people who understand what data they need to make these decisions. That’s difficult sometimes, especially with all of the analytics tools available. Can they identify the KPIs and track down segmented data in a way that makes sense to create that answer? Also, communication skills are critical. I look for people who can communicate crisply and clearly.
Finally is product sense. This is the skill that gets people to ask “why?” It’s very hard to teach product sense. Some people just have it. They know why something feels right compared to another thing, and I think the ability to structure that thinking and go deep into a subject is a super skill in this market. I want to test that early.
Re-skilling and empowering product sense
How do you see the role of leadership pushing for these qualities, like product sense and thoughtful decision-making?
I’ve seen firsthand how much leadership shapes the culture around product sense and decision-making. At Meta, Amazon, and even at LTK, I have had to push back on top-down directives, and I have been very fortunate to have had leaders who have backed me up. That kind of support sends a clear signal: Leadership isn’t about being agreeable, it’s about being empowered to do what’s right for the product.
I still take on IC work when needed. I write product proposals and decision documents, and I get into the weeds because it keeps me grounded in what we’re building. I’ll push back when I disagree, and if we don’t fully align, we disagree and commit. That’s what thoughtful decision-making looks like in practice. It only works if leaders actively create the space for it and reward people for using good judgment, not just for going with the flow.
Do you foresee this shift continuing to evolve over the coming years, especially with new technologies?
Yes, I see this shift continuing and possibly even accelerating with the introduction of new technologies like AI.
We’re already seeing it with the wave of layoffs at big tech companies: Many of those employees are being forced to re-skill, and in doing so, often take roles at startups with lower compensation but far more hands-on impact.
It’s a humbling shift, especially coming from environments with generous comp structures and more siloed scopes. But what’s interesting is that this transition often leads to real upskilling — people move from operating within mature systems to actually building them from scratch. That builds product sense, execution muscle, and sharper decision-making.
Leaders who’ve left big companies, sometimes shedding golden handcuffs, often discover a renewed sense of purpose at startups. They’re expected to make tangible contributions, which forces them to stay sharp and push their thinking. And with the velocity AI is enabling, those who can combine deep product instincts with a builder’s mindset will not only thrive — they’ll help these startups grow faster than ever before.
Are there core concepts that you think every PM should understand today when it comes to AI?
This is a very interesting topic, because a lot of people have recommended I take courses on AI. It reminds me of how, as a PM 10 years ago, everyone told you you had to be an engineer because it would help your career substantially. Before, having a computer science background as a PM was golden, and now it’s all about data science.
But, for the vast majority of PMs, we now have to fundamentally rethink how products deliver value. This shift demands new skills, as well as a new mindset and a new kind of leadership. First, PMs need to understand AI capabilities. What can LLMs do for you? Can they generate text or video? You need to stay up to date with the latest developments, and they’re moving fast. You also need a sense of what it takes to build something like that from an architecture perspective.
Becoming a PM now requires an even higher barrier to entry. I’m personally excited about it. You need to design products that embrace AI’s unique characteristics. You need to understand the interactions required to get accuracy out of AI, and how to balance fast results with accurate ones. There are also ethical considerations, and the use of trust alongside technical performance. As I said, the role is getting harder. It’s going to be a lot different than ever before.
Encouraging AI as a function of the role
How do you encourage PMs that you’re interviewing or that you hire onto your teams to leverage AI tools?
I actively encourage PM candidates to treat AI tools like LLMs as essential to how they work and prepare. I tell our recruiter to encourage candidates to use tools like ChatGPT during interview prep: Upload a case study and ask, “What questions might I get?” It’s no different than moving on from mailing resumes; if you’re not preparing and working with modern tools, you’re behind.
On my teams, LLMs are integrated into the workflow. They transcribe meetings, summarize action items, and even help with prototyping. We’re still in the testing phase with what’s possible, but my expectations have evolved. One of the criteria I now evaluate PMs on is how effectively they use AI tools. I don’t want to see docs with typos or poor formatting; those should be fixed in seconds with a prompt. It’s not about replacing critical thinking; it’s about raising the bar on quality and speed.
What advice would you give to PMs when it comes to shifting how they define problems and frame solutions in an AI-first world?
In an AI-first world, PMs need to shift from static specs to dynamic, decision-driven thinking. I’m a big believer in decision docs, more than PRDs, because product development is no longer just about feature trade-offs. It’s about navigating a growing web of complexity: ethics, data costs, engineering feasibility, design systems, and user trust. I use decision docs as a core expectation on my team; they help clarify intent, frame the problem in terms of data and outcomes, and support faster iteration. I actually think PRDs will fade out within the next year or two, replaced by more collaborative, real-time workflows that reside within design systems. With tools like Lovable or Bolt on the rise, you’ll soon be able to upload your design libraries, co-create with UXR and design, and feed that directly into metrics. The future is about fast prototyping, clear decision-making, and AI-enhanced systems thinking.
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