# Strategic Decision Stacks in the AI Era

**Podcast:** Product Momentum Podcast
**Published:** 2026-11-10

## Transcript

So first, you know, the decision stack was vision, strategy, objectives, opportunities, and principle.
Why strategy before objectives?
Yeah, that's a, I've had that question before.
I think for me, we have to make the right choices about like, you know, I use the classic Roger Martin thing around where to play, how to win, right?
Those are strategic choices for me, and I think we have to make those before we can then set the objectives and goals.
I think people have different answers to those questions.
So really for me, it's the five questions, right?
So where are we going?
How are we going to get there?
What matters right now on that journey?
What are the actions we're going to take to move forward?
And then how do we choose between those actions?
And I think that opens it up a bit more.
So one of the things I really love, you know, that resonated in your talk was, you know, you're talking about, you know, assumptions baked in at every level of the decision stack.
How can we better get those assumptions out in the open?
Yeah, and I think, I mean, that was kind of my call to arms today, right?
It's like...
I think it's every product person's responsibility to make sure that we have those conversations internally.
I think product people have these superpowers around how do we do assumption testing?
How do we do hypothesis testing?
Like, let's take that out to stack and let's challenge the rest of our organization.
And that's just a different way to challenge our leadership on that question without being confrontational about telling them their strategy isn't working anymore.
You mentioned something I love, don't trust the computer to make management decisions.
I'm curious what advice you have for product folks out there.
who are struggling to like hold on to the decision making right.
Yeah, I think it comes back to like, what are we using AI to do internally?
So I talked a lot about always the strategy and the kind of the what we're doing in our product, but we're also using it as efficiency, right?
Like how are we getting more efficient in our jobs?
What are we trying to do with that time?
But I think we actually have to flip the question and say, what is the thing I want to be spending more time on so that I can then how can I carve out the other stuff?
More often than not, the strategy is not changing.
I'm curious, advice for the folks, how as product leaders do we kind of maintain a level of calm and discipline when that's happening to not just go, okay, this, now this.
And I think that's the other thing I kind of hammer on about the decision stack for is the consistency to commitment, right?
So we've made some decisions.
We want to be committed to those decisions.
But here's how we know whether we're heading to the right track or not and when we need to change those.
And I think that forces a level of clarity, not just in the decisions we made, but when we have to make change.
Sean.
We are here in Dressing Room 5 at the Harris Theater in Chicago, Illinois.
We just sat down with Martin Erickson, had a great conversation.
Martin brings a really modern take on strategy and really how the age of AI is really impacting strategy.
So the first times we've talked about like the impact of AI, but not talked about AI specifically, really excited to bring his viewpoints to our listeners.
Let's do it.
We are here live at Mind the Product.
All of our podcasts are live, so this really isn't too much of a change for us.
But we're here in the basement of the Harris Theater.
We're with Martin Erickson.
Martin is a board member, a strategic advisor, and author of The Decision Stack.
You've already been on stage twice, so thank you for continuing your media tour here today.
You're also a co-founder of Mind the Product.
And they say you can't go home again, but here you are.
Well, I love the community, so I stopped being actively involved in 2022, but I just love being in the community.
And anytime I get invited to speak, of course, it's an extra bonus.
I'm happy to be here.
Yeah.
Thanks for being with us.
You were the second speaker today.
Your talk was really centered around your concept of the decision stack and then really some musings on how AI kind of applies to this.
So first, the decision stack was vision, strategy, objectives.
opportunities and principles, right?
We teach a framework called the vision stack.
So we've now, we're competing frameworks here.
Okay.
Why strategy before objectives?
Yeah, that's a, I've had that question before.
I think for me, we have to make the right choices about like, you know, I use the Cossack, Roger Martin thing around where to play, how to win, right?
Those are strategic choices for me.
And I think we have to make those before we can then set the objectives and goals of like, okay, well, how are we actually going to achieve that?
So for me, it comes just that order round.
I do think that's why I kind of abstract the decision stack out sometimes as well.
I think people have different answers to those questions.
So really, for me, it's the five questions, right?
So where are we going?
How are we going to get there?
What matters right now on that journey?
What are the actions you're going to take to move forward?
And then how do we choose between those actions?
And I think that opens it up a bit more to like, well, OK, you don't like OKRs, you can use something else.
Or you want to have a different way to answer that question about where are we going?
That's fine.
I'm less dogmatic about the kind of...
vision, strategy, objectives piece of it.
Because I think it has to flex into how organizations want to work.
But I think you have to have answers to those questions, basically.
Okay.
Our friend Mary is here from NatGeo.
She was in your workshop yesterday.
So this is actually your fourth thing that you're doing.
She really loved your concept of principles.
Tell us a little bit about principles.
Yeah, so I think it really grew out of, I mean, the example I always give is my first product job was 1999 at Monster, right?
The job board.
And as a job board, it's a two-sided marketplace.
So every product thing we were looking at the time, We had this massive debate, right?
Do we do it in the job seeker friendly way or do we do it in the recruiter friendly way?
And we just spend ages kind of having that debate until I kind of pulled a founder into the room once and asked him the question.
He's like, wait a minute, if we do, you know, the job seeker always comes first because if we do a great experience for them, then the recruiter has to follow.
And I was kind of in our strategy, but it had never been articulated as that trade-off of like job seekers should always come first.
And suddenly those debates go away, right?
We're just not having that debate.
We just know every time we're looking at it, every time it comes into conflict, the job seeker should come first, right?
Doesn't mean the recruiter is not important.
They pay the bills at the end of the day.
But in any trade-off scenario, we want everyone to go, okay, well, actually what we want to do is build up the best possible experience for job seekers.
So principles really are that articulation of your strategy for me.
And they're there to help your teams make better decisions faster without having to escalate every single decision or have to, you know, relitigate that debate every single time it comes up.
Almost call it North Star.
And like, yeah, the North Star strategy, I think that was big like two years ago.
Yeah.
But you might have a couple, right?
So that's the simple one in a two-sided marketplace, but you might also have a few others around how you want to do it on like mobile, even over desktop, or conversion, even over revenue, like things that you really want people to focus on and make those decisions faster.
Right.
So one of the things I really love, you know, that resonated in your talk was, you know, you're talking about, you know, assumptions baked in at every level of decision stack and how often we focus on assumptions at the project implementation level and then higher up.
Nobody talks about those because maybe the strategy is a thing that you saw once in an all-hands eight months ago.
How can we better get those assumptions out in the open, higher up in the stack?
Yeah, and I think, I mean, that was kind of my cold arms today, right?
Is like, I think it's every product person's responsibility to make sure that we have those conversations internally, right?
So like, we should be there to challenge our whole stack, right?
And look at it and use the tools that we have, right?
I think product people have these superpowers around how do we do assumption testing?
How do we do high pulses testing?
Okay.
let's not just use that at the feature level or the opportunity level.
Like, let's take that out the stack and let's challenge the rest of our organization.
Like, hey, wait a minute, our strategy, you know, if we actually go ask that question, what would have to be true for our strategy to happen?
A bunch of assumptions are going to fall out of that.
And then you realize, wait a minute, two or three of those have actually changed massively because of AI.
Maybe we need to question that strategy, right?
And I think, again, that's just a different way to challenge our leadership on that question without being confrontational about telling them their strategy isn't working anymore, right?
Right, that never really goes that well.
Yeah.
So, like, it's a different conversation when you come in and, like, hey, our strategy is awesome, but we've realized that, like, it's probably based on these two, three assumptions, and one of those seems to have changed, right?
Do we need to revisit this conversation?
And that's a much friendlier way to have that conversation, right?
You challenged the concept of the SaaSpocalypse, right?
And you went through some stats that were really interesting.
I like the fact that you said, like, not everybody wants AI.
Four or five people in the world have not tried AI.
But we...
kind of are biased into thinking that everybody does because we're, especially the people at this conference, we're in the bubble.
Describe the bubble to us and Mike's on those stats.
Yeah, so it's kind of, I mean, there's a lot of stats around this, but if you look at the global level, it is something like four and five people, so 80% of people have never even touched AI yet, right?
Even if you look at like Western economies, the US, I think it's 50% probably haven't touched AI.
And I think as tech people, right, like we love this stuff, right?
Like I am a tech guy.
I love building.
I'm hacking away at this stuff.
I'm playing with the vibe coding.
I'm using cloud code.
Like I love it.
But we have to remember that our customers don't, right?
They don't care about the technology.
They just want the problem solved, right?
They want the pain point.
You're eliminated.
And some of them will pick it up, right?
It's gotten easier.
It has definitely democratized software and people will build stuff.
But then you have to remember the maintenance of it.
You have to remember the support of it.
Like I've built some apps that fall over on lovable and it's like, it's not a great experience, but it's fine because it's free.
But like, I would never want to ship that to an end user, right?
And I think fundamentally, our customers want the problem solved in a way that lets them focus on whatever their business is about, right?
So I use the example of the restaurant manager, right?
They just want stuff that gets out of the way so they can focus on their customers.
They don't want to sit there and hack around with Cloud Code to build a better point of sale system.
They will start asking better questions of their, suppliers, I think, like, wait a minute, why can't this software be better?
Or can't I customize this better?
Or like, can I have a better user interface for it?
For sure.
So like, we have to step up our game, but I don't think that person's going to go build their own software to solve the problem, right?
Yeah.
I think you're hitting on something really important.
I've always considered software, we're tool makers.
Yeah.
And it's so easy for us to get lost in the sauce of like the amazingness of our tool, but like the people that go there and they're just trying to get, they just want to use the things they get on with their day, right?
And like keeping that in mind is so important.
You mentioned that just mentioning an AI feature in some of your marketing copy is starting to reduce the purchase intent.
Why is that?
I think there's a lot of backlash.
I think we have probably miscommunicated AI.
Obviously, there's all the stories about this 10% chance of killing us all and it's going to take everyone's job.
Of course, people are nervous about it.
And then I think, you know, even more localized, there is a lot of resistance to data centers.
There's a lot of questions about the environmental impact and like there's a lot of challenge back on it.
So again, AI in this, just for the sake of AI is not something a customer wants, right?
They don't care.
And it's actually now showing, this was a, I think it was a Washington State University study that it has a negative impact on purchase intent if you kind of have artificial intelligence in the product description.
So we really just have to be mindful of that product.
You know, looping back to April's conversation, like it's not about AI, it's how are you solving the customer's problem better?
And if you're using AI to do that, great.
But like, again, they don't care.
They didn't care whether we were using, you know, what version of SQL we were using.
They didn't care if it was PHP or code.
Like, are you solving my problem better?
Cool.
Great.
Let's move on.
Right.
Yeah.
So I think we have to remember that, again, it's just falling in love with that problem.
And how do we solve that better for the customer?
You mentioned something I love, right?
Don't trust the computer to make management decisions, which I love, right?
Because, yeah.
There's so much happening now.
You have a million tasks to do.
You pump something AI, it gives you something good back.
Yeah, I'm curious what advice you have for product folks out there who are struggling to hold on to the decision-making rights and actually owning it when it's so easy to do.
Yeah, I think it comes back to what are we using AI to do internally, right?
So I talked a lot about always the strategy and what we're doing in our product, but we're also using it as efficiency, right?
How are we getting more efficient in our jobs?
What are we trying to do with that time, right?
Like, where do we want to be spending our time?
And I think it's easy to start looking at it like, oh, well, I'm spending two hours on this a week.
I should automate that away.
But I think we actually have to flip the question and say, what is the thing I want to be spending more time on?
And then how can I carve out the other stuff?
And I think it comes down to me for like user research, customer research.
It comes down to decision making, strategic thinking.
Like those are the things you want to hold on to, right?
So how do we make more time for that, not less?
How do we not think about, oh, I'm going to automate away.
writing this strategy doc and hand that over to Claude, right?
Because that's probably where you want to have the most impact.
And how do you automate the way the things that give you time to do that instead, basically?
Staying on the advice for product people route, you know, as a board member and as a strategic advisor, if you're going to hear a challenge to a corporate strategy, what are you looking for from a product person?
Like, what are you hoping to hear that you think is going to change your mind?
That the strategy sucks.
Probably not that, right?
Yeah, it fundamentally comes down to evidence, right?
If we have opinions, then, you know, we have the concept of the HIPAA, right?
The highest paid person's opinion.
If it's all about opinions, the HIPAA is going to win, right?
They're going to trample all over us.
So if you come in going, I don't think this is right, or this is not the right way to do it, or I think the strategy sucks, like that's never the right way to start the conversation.
If you come at it with evidence of like, oh, we have, you know, I've seen this assumption seems to be failing, or I have new evidence from customers that like they don't want this, or we're seeing market trends move this way, and here's the evidence for that.
That's always, again, it depersonalizes the argument, right?
You're not challenging the person, you're challenging the argument.
And so I always find that the best way to do it.
And I think the more you can just dig in and come in with a story of like, I think we should make this change because of X, Y, Z.
Here's the evidence for it.
Here's a better approach that we can take.
And here's why I think that's going to work.
And here's how do you risk that?
Like, that's an amazing conversation to have, right, with anybody.
And again, I think this is where product people, we have superpowers in this, right?
Whether you're a product manager, designer, data scientist, engineer.
This is what we do every single day down at the feature level.
Like we just have to bring that conversation up and we have to bring that challenge up to the strategy level, I think.
We at our conference last year had a speaker come in, David Pereira, and he actually ran a workshop for us that was actually built around like challenging your assumptions, but also just becoming like aware of your assumptions, right?
You mentioned assumptions in your talk.
April touched on assumptions in her talk.
Is this something new that we're discussing for like the first time, becoming more aware of because of this new technology that we're all able to use?
Or is this like getting back to fundamentals thing?
I think it's a bit of getting back to fundamentals, but then elevating the conversation as well, right?
So I think assumptions is something that we've talked a lot about over the last 10 or plus years.
I mean, this came out of assumption mapping stuff that I think originally came out of Janice Fraser and others in San Francisco, and then David Bland and Alex Osterwalder have been building on it, right?
with the assumptions mapping exercise.
But we're very good at using it, again, at that feature level, I think.
But what we have to do is bring that conversation up.
And I think maybe why it's having its moment right now is because so many of those core assumptions have changed, right?
And that's how the rug's been pulled out from under us.
And we're like, hang on, why did the strategy break?
It's because these assumptions have changed, right?
And so I think that's why it's maybe coming back into, well, being talked about more, at least.
But again, I think, and I was talking to David Bland, the other, week and you know we had this conversation and it was his frustration is that it was never meant to be a future level thing was never meant to be just a product tool it was meant to be a strategic tool right and so that's just what we're trying to do is like how do we raise that conversation right you said something else in the talk that really stuck news right humans are inherently awful at predicting the future yeah and then the idea of you know when you're looking at vision and strategy that you need to account for a range of outcomes um curious, you know, how to strategy level, you can reasonably like run like a pre-mortem on a strategy and at a cadence that's kind of keeping pace with the world, but not happening so often that all you're doing is running pre-mortems and you're not actually doing anything.
Right.
And this is where I think like the decision stack has helpful because each of those has different timelines, right?
So your vision is probably something fairly static.
Doesn't change very often.
You'd hope.
I mean, maybe, you know, with AI, you have to question that, but.
Then your strategy, obviously, I think is changing more often than it used to.
We used to talk about three-year, five-year strategies.
Those cycles are much shorter.
And I think that's where it can be helpful to companies because you don't have to relitigate everything every single time.
You just have to go up as far as the assumptions don't hold anymore or circumstances have changed.
I mean, premortem is a great way to do it, right?
It's just talk about in the five years, what would have made this succeed or what would have made this fail?
Even just having that conversation is more assumptions testing, more hypothesis testing than most do, right?
I kind of made the joke in passing on stage that like we put all this rigor into how we build product features, right?
And we test everything and we go through it like endlessly.
And then we, you know, we go to an offsite in Lisbon and we pass a strategy on vibes, right?
And over cocktails and then we kind of move on.
So I think we just have to bring that rigor up to that conversation because we have the tools already.
And I think it's not about consistently changing it every quarter or whatever cycle you need to find.
But it is checking in, like, are we still on the right track?
And like, do these assumptions still hold?
Has anything changed in the market?
Okay, cool.
We're still good to go.
Let's keep going.
Which is going to be the answer most of the time anyway.
And then sometimes you're going to be like, wait a minute.
No, this thing has changed or Claude just dropped something or, you know, something has fundamentally changed the strategy and you have to have the conversation again.
But yeah, I think it is just having, treating strategy as a product, right?
Like how do we test these things?
How do we de-risk these things more often than we have in the past?
Yeah.
And you just said something interesting, right?
Like more often than not, the strategy is not changing.
Yeah.
And I'm curious, advice for the folks, I think there's a tendency sometimes when there is a lot of chaos, right?
When things are moving quickly to want to react quickly and how to, as product leaders, do we kind of maintain a level of calm and discipline when that's happening to not just go, okay, this, now this, right?
And I think that's the other thing I kind of.
hammer on about the decision stack for is the consistency and to commitment, right?
So we've made some decisions.
We want to be committed to those decisions, but here's how we know whether we're heading to our track or not and when we need to change those.
And I think that forces a level of clarity, not just in the decisions we've made, but when we have to make change, right?
So, okay, something has changed.
Now we have to go through the whole process again of like, how do we commit to that change?
How do we commit to the thing?
But I think it's important because, to your point, I don't think the strategy changes as often or needs to change as often as we think it does.
And so if we can be consistent with that, like, no, we are still focused on this customer target.
We still think that's how we're going to win.
The tools we're going to use to do that, the features, of course that's going to change.
Something has happened, some new options arrived, right?
But we're still solving the same fundamental customer problem, right?
Going back to, again, April's point as well, like, we have to be consistent about who are we solving this for?
What is the problem?
You know, who's our competition?
What are we actually solving for?
And I think those change a lot less than we think they do, right?
The fundamental user problems, customer problems don't change ever often, right?
Yeah, I don't know.
I think you mentioned, you know, cocktail-laden strategy sessions in Lisbon.
That really sounds like my speed.
Yeah, I mean, I'm hoping that eventually we come back to that.
I want to take a minute and just ask you about, you know, writing the decision stack.
What was your motivation behind that?
So I think it started as a...
talk I gave at a conference in Hamburg in 2019.
And I kind of gave it as sort of a, I mean, I don't want to sound dismissive, but sort of a throwaway talk.
I'm like, this seems pretty obvious, right?
This is how everyone thinks.
And it turns out it wasn't.
And so I've kind of been honing it ever since.
And then over the last seven years or so, I've advised nearly 150 companies and been talking through them about like strategy and org design, all this stuff.
And just started using these tools as like, this is a better way to have a conversation and bring that clarity and connect things for people.
And so over time, it's just become one of these things where I think every couple of months, someone asks me like, when's the book coming?
And I'm like, I guess I should sit down and finally write it.
But that's a great signal, right?
It's a great command signal and pull that like people wanted this.
It was helpful to people.
And I think the hard part is it's easy to talk about this stuff in theory when you're looking at, you know, the visualization and like a simple slide deck.
And then you get into writing the book and you're like, okay, well, what about this case?
And what about this side thing?
And what happens if this changes?
And like, yeah, the complexity of it kind of exploded a little bit.
But yeah, it was really driven by pull.
I think that this clarity is needed.
And I think the final thought on that is for me, as well as kind of a continuation from Product Leadership, the book that I co-authored in 2017, right?
Where I think the outcome of that book really was, you know, early days at the time, talking about empowered teams, right?
That the best possible power teams out there are the ones that are most empowered.
And I think the missing piece to that is, you know, what Marty King calls strategic context.
It is the clarity within which to have that empowerment.
And I think that's where the decision stack can kind of help close the gap.
All right.
So we need the decision stack on our bookshelf.
We need product leadership on our bookshelf.
What are other, like, we try to take the opportunity when we have authors on, like, what are other accompanying books that you think would really help round out some, like, changes in thought?
So I think it's interesting that, like, there's a bunch of us now who've been talking much more about.
impact, right, and commercial impact.
So I really love Matt LeMay's impact for his product.
Huge fans.
I'm a huge fan of that.
And I know he's been on before.
He's a good friend of mine as well, lives in London.
And I think they're very complimentary, right, because he's thinking very much from the team and I'm thinking more of the strategy level and we're actually doing more work together as well.
I think Rich Marinov's money stories have been amazing as well.
Like, how do we have that conversation again with leadership?
How do we challenge them?
How do we have better conversations?
I love his line that like...
you know, your C-suite doesn't hear anything, any sentence that doesn't have a dollar sign in it.
Yeah.
And so it's a great book.
Nice short book as well on that.
I think continuing on the assumptions, I think David Bland and Alex Osterweiler's Testing Business Ideas is a fantastic field guide.
It has like 40 experiments of how you can actually go test this stuff in the real world.
So yeah, those would be some of my favorites right now, but I think it's all about that impact, right?
Get those in the show notes for sure.
Yeah, a new one for us.
And we get to close with talking about our friends, Matt and Rich.
Exactly.
Exactly.
Martin, thank you so much.
I know this was your fourth thing in the last two days.
Thank you so much for having me.
It's been great.