Volume 196: The 10X Marketer.
The 10X Marketer.
tl;dr: The AI-era will be very different from the ZIRP-era.
If the last fifteen years, also known as the ZIRP-era, was defined by the myth of the “10X developer,” the AI-era will be defined by the need for “10X marketers.”
The reasons are simple: Economic conditions, market dynamics, and technical limitations will be radically different in the AI-era compared to the ZIRP-era.
Where the ZIRP-era bred a generation of tactical marketers proficient at wielding dashboards, the AI era will require a new generation of strategic thinker. Where the ZIRP-era led to a new category of product marketers, the AI-era will require an equally new generation of brand-builders. And where the ZIRP-era ended abruptly with a shift to the technocratic, anti-human management philosophy of Measureship, the AI-era will require a new management philosophy of creative, pro-human leadership that seeks love. (No matter the nihilism of marketing scientists on this topic, the idealism of seeking to create something so good that people will love it remains an exceptional aspiration for anyone seeking growth in a moat-less world; more on that in a bit).
More specifically, AI-era corporations will need to make three big shifts relative to their ZIRP-era forebears:
Look different; leave the luxury of blanding behind.
Be different; think bigger than product.
Optimize differently; capture the imagination.
Here's why.
With the benefit of 20:20 hindsight, the ZIRP era was a historical aberration driven by global economic policies that started in 2008/9 to stave off the very real threat of a global depression. This dropped interest rates to zero worldwide, precipitating a previously unimaginable fifteen-year flood of ‘dumb money’ into the venture capital system, which was then allocated to startups with wildly varying chances of success.
According to a recent Bloomberg article, circa 1,200 ZIRP-era venture-backed unicorns in the US have yet to go public or be acquired. Unfortunately, their prospects don’t look great in the post-ZIRP environment: IPOs have collapsed, growth has stalled, bankruptcies and asset fire-sales have increased, and capital raising (where it is achievable at all) is happening at massive discounts to the past.
This means that after the free flow of capital ended, we’re left with a generation of stalled-out zombie unicorns that will likely become uni-corpses unless something drastic changes. And those were the success stories. While estimates vary, only around 1% of startups become unicorns, with 90%+ going out of business entirely.
How we got here isn’t all that surprising. The go-go investment days of the ZIRP era meant a decade and a half of VCs having more capital to allocate than good ideas to allocate it to, which led to a combination of bad investment decisions and twisted incentives. The most obvious being the zero-sum ‘blitzscale until you monopolize” mindset that kinda worked when capital was freely available but collapsed in 2022 when the money dried up due to a combination of interest rate rises and a newfound VC obsession with AI.
More nuanced, but no less catastrophic, was that during these heady days, the free flow of capital meant lax discipline around basic business principles such as having a durable business model, creating a differentiated offering, having distinctive branding, delivering a superior customer experience, and pricing at a level that might someday create an actual profit.
In other words, huge capital injections meant ZIRP-era corporations lost sight of what it meant to be competitive and forgot how hard it is to grow sustainably and make profits, which is now returning to haunt them.
As a result, as we abruptly shift from the ZIRP-era to the AI-era, we will need to leave behind the management baggage of a prior generation that no longer works. Put simply, if we follow the ZIRP playbook in the AI-era, we will fail because we’ll be pursuing a path that was totally dependent upon unlimited capital long after it has dried up while also operating under very different marketplace conditions.
When Deepseek demonstrated that vastly cheaper and more efficient foundational GenAI models are possible, it turned the prevailing beliefs in the category on its head -that cost is the moat- by making true the observation that “AI has no moat.” (As an aside, whether Deepseek is or is not Chinese spyware has no bearing on this. Since its technology was released under an open-source license, others can now replicate, innovate, improve upon, and fork what it did. And they already are).
Having no moat translates into this: In the upcoming AI-era, barriers to entry will be very low, copying will be easy, options will proliferate, and there will be very few ‘structural’ opportunities to create an unassailable economic advantage.
More broadly, eliminating the cost moat Big Tech thought it had leads to an inevitable shift in topline narrative from investment to innovation. This moves the emphasis away from Big Tech as the feudal digital landlords of the future and instead places it slap-bang on application, or product layer, innovation. Startups focused here had previously been viewed as second-class citizens, permanently dependent as they would be upon rent-seeking Big Tech. However, they are rapidly becoming the focal point of the GenAI narrative as radically lower costs increase the viability of a swathe of new and often niche propositions. (A phenomenon I previously labeled ‘GarageAI’)
To put where we are in context, foundational models such as ChatGPT, Claude, Llama, Grok, and Deepseek aren’t products per-se, even though we interact with them as if they are. Instead, they’re closer to what we might refer to as generalized “core technologies.” As an analogy, this is a little like AWS or Azure offering the technology of cloud computing, upon which product/application-layer innovators then built entirely new business categories, such as streaming (Netflix et al.) and SaaS (Salesforce et al.).
It’s important to note that while AI's replicability means that it has no moat, this does not mean new players in the space cannot build moats. Handily for this newsletter, one of the primary economic moats this new breed of company has the opportunity to build is a brand moat. And if brand moats can be built for pure commodities such as water, they can certainly be built for AI products - such as agents, especially agents we’re expected to trust spending money on our behalf - no matter how replicable and thus commoditized these offerings may appear before the fact.
So, while we cannot see the future, we can see where ZIRP-era thinking no longer works. So here are three ZIRP-era traps to avoid, alongside some observations on what a ‘10X marketer’ oriented startup might do instead. (Important to consider since, as far as I can see, ZIRP-era mistakes abound among AI-era startups today)
1. Look Different: Blanding was a ZIRP-era luxury.
ZIRP-era startups embraced the foolish “de-branding” and “blanding” movements with gusto, manifesting as a boring, bland melange of interchangeable and utterly forgettable me-too aesthetic and verbal codes.
While the empirical evidence pointed toward this being value-destructive behavior, and while people like me warned that it was equivalent to standing in the street and lighting your money on fire, it happened anyway…until the money ran out.
AI-era startups looking at how badly this served their ZIRP-era forebears will have to be smarter. They should embrace the empirical evidence and ensure they look, feel, and act distinctively, uniquely, and memorably. They need to understand that the job is to stand out from the crowd rather than fit in and to be uniquely themselves rather than some identikit version of others.
In other words, they should treat this as an opportunity to radically disrupt the status quo and create a new set of unique, memorable, and distinctive brand codes for themselves.
So far, they’re doing terribly.
2. Be Different: Product isn’t enough; you need a Big B brand strategy.
Brands become economic moats by accelerating the performance of the underlying business model via demand effects that increase volume and pricing effects that increase margin. To maximize the demand (penetration) and pricing (margin) effects of a brand multiplier, brand strategy must align closely with the business strategy and operate in a way that helps orchestrate the interdependent business systems that make up the company. Of course, achieving this means we must bring a strong understanding of the customer, what drives their desires, and what will mitigate their fears (to raise demand), as well as understanding what they value (to help price at a level where unit economics are positive) all tied together with the imagination to synthesize this into something magical (more on that in a bit). As a result, brand strategy becomes the interface between this deep understanding of the customer, the orchestration of the company’s business systems to deliver, and the imagination to create magic. If you’re wondering where product sits in this, it’s downstream. While the following may sound like heresy to many, one of the great weaknesses of the ZIRP-era was the elevation of product to the detriment of all else. Instead, it’s often better to think about products as the carriers of expectations of the brand rather than somehow living independently of it. This does not in any way deprecate the importance of having a great product; it’s simply an acknowledgment of two things we’ve witnessed for a while now:
The days of the MVP are long behind us. Product excellence is increasingly a minimum expectation, meaning it becomes a cost of entry rather than the sole source of competitive advantage. Furthermore, there is little empirical evidence that the “best product” wins in competitive environments where customers have multiple choices, which is exactly the challenge that AI startups will face… because AI has no moat.
While products are critical, people often buy based on non-product factors, especially when there is perceived product parity (e.g., customer service, partnership, trust, desire, social approval, meaning, innovation, roadmap, familiarity, availability, fame, FOMO, etc.), which means we need to align and orchestrate much more than just the product to differentiate and succeed.
This is very different from the way brand strategy operated among ZIRP-era startups, which was notable for its focus on factors extrinsic to the activities of the business:
Too many ZIRP-era startups followed ineffective, generic brand strategy playbooks, with ‘purpose’ and Sinek’s ‘Golden Circle’ being the most egregious. Neither does a good job of enabling the brand's accelerating effects on the business; neither is particularly customer-value-oriented nor customer-insight-heavy; neither helps orchestrate the business systems, nor do they synthesize the imagination-magic necessary to deliver a multiplier effect. Instead, such strategies commonly exist as little more than the intro pages to brand guidelines.
Too often, the creation of brand assets was confused with the creation of the brand. Having a positioning statement, a logo, and an identity system does not mean we have a brand. This means we have the intent and some of the necessary assets to build one.
Too often, ‘brand’ groups within ZIRP-era startups sat separately within the marketing organization, focusing on PR and comms “buzz” but with very little influence over the overall value proposition, experience, innovation, product, or service proposition, which was instead handled by...
Product marketing, which became dominant due to the internal elevation of the product as the defining reason for being, deprecating the brand to little more than PR activity. This led to undesirable second-and-third-order effects, including incrementalism, generic and fragmented brands, confused and chaotic product mixes, economically nonviable pricing, atomized marketing spend, and ultimately, a stalling of growth.
In sum, AI-era startups will need to break the internal philosophy of product dominance, for products alone will not be enough to create a brand moat. For that, we must elevate the importance of the brand as an orchestrating tool for the business and think of product as a critically important carrier of the brand's expectations, alongside other carriers such as innovation, service, experience, marketing, etc.
3. Optimize Differently: Capture the Imagination
One of the worst things we can do when a business is small is ape the behavior of large businesses in the false belief that it will make us large too. As any historian will point out, this is rarely the case. While nobody today would accuse Anheuser Busch of being category-creative or innovative, it used to be. Many moons ago, the growth of its flagship brand, Budweiser, was driven by the constraint of having a tiny home market in St. Louis. This constraint then drove considerable innovation in parent company Anheuser Busch as it pioneered the commercialization of mass production, mass advertising, pasteurization, and refrigeration to create something we now take for granted: the at-home market for beer. (As an aside, the value proposition for Budweiser was never that it was a great-tasting beer but that it was consistent bottle to bottle, which was impossible in a pre-refrigeration, pre-pasteurization world).
So, rather than paying attention to what is happening with Big Tech today, we should first examine Silicon Valley’s past growth to see what we can learn for tomorrow.
Long before we thought of Big Tech as feudal rent-seeking landlords, it was instead viewed through a lens of magic, wonder, and possibility. This created a phenomenon known as the ‘Silicon Valley Dividend,’ where technology was viewed as a driver of societal progress, and new categories, such as the ‘sharing economy,’ captured the imagination. However, even as it leveraged this aspirational and emotional value to drive its own growth, Big Tech subsequently left it behind as monopolistic power drove it to extract value rather than create it.
While the Silicon Valley Dividend is long gone, there’s no good reason why the magic, wonder, and sense of possibility should be gone, too…unless you’re one of the enshittifying Big Tech firms that can no longer deliver it.
However, look at the startup landscape today. It’s all sadly, boringly, monotonous: The same brutalist wireframes, the same copy-styles, the same aesthetic tropes, the same products, the same outsourcing of brand personality to ‘influencers,’ the same origin story, the same investor pitch shining through, and - if you’re in B2B land - the same inquiry forms and attempts to sign you up to a product long before you even know what it does. Dive a little deeper, and it gets worse. Low value, execrable quality “content marketing,” email spam, discount code proliferation, a lack of customer insight, and, and, and…driven primarily - I think - by a past dependence on unlimited capital and the rise of the Measureship management philosophy with its myopic focus on incremental anti-human optimizations.
Here’s the problem: nobody ever grew from small to large because of their mastery of tiny incremental optimizations. As a result, incrementalism masquerading as innovation is a conceit of the very large and poison for everyone else. While for the very large, incremental improvements can add millions or even billions of dollars to the bottom line, when you’re small, it’s little more than a rounding error on the path to obscurity.
Instead, AI-era startups need to optimize for the imagination. Specifically, to capture the imagination by creating magical, wondrous, and possibility-filled experiences that get you noticed, remembered, and ideally…loved. Not because you’re big but because you’re special.
By contrast, today's AI-era startups are much more likely to be dragged down by the baggage of ZIRP-era optimization failure while claiming an almost impossible-to-find difference. As competition intensifies, this simply won’t cut it anymore. Boring incremental conformity won’t work. It barely worked in the ZIRP era when unlimited capital hid its ineffectiveness; it definitely won’t work now.
Instead, optimize for the imagination, be magical, be possibility-filled, and win by truly understanding people’s aspirations and desires rather than understanding how to create a 0.0001% uplift on campaign ROI.
So, there you have it. My suggestions, for what they’re worth:
Look different; leave the luxury of blanding behind.
Be different; think bigger than product.
Optimize differently; capture the imagination.
This is why the AI-era will metaphorically depend more on the 10X marketer than the 10X developer. None of these components of building a brand moat are engineering-led. Instead, they’ll require a unicorn-like combination of strategic nous, imagination, orchestration, and an ongoing flow of ideas that create experiences that people will fall in love with. And, just like with engineering, much of the tactics this kind of thinking generates will be executed by AI itself.
The rhetoric of the 10X developer is ending; long live the 10X marketer.