Andrew Chen, a16z General Partner and one of Silicon Valley's most influential voices on startup dynamics, recently posed a deceptively simple question: "How many apps on your phone's home screen are AI-native?" His answer reveals a stunning reality that every marketer should understand: we're living in what he calls "the golden age of AI, but it's still incredibly early."

For marketers, Chen's observations about the future of startup building reveal something profound… and potentially terrifying. The same forces that will reshape how companies are built will fundamentally alter what it means to be a valuable marketing professional.

Chen's "Home Screen Test" exposes a critical gap between AI hype and actual adoption. Despite all the excitement, "very few" apps on our phones "are AI-native" beyond the obvious ones like ChatGPT. What makes this observation crucial for marketers? this gap won't last forever.

Chen predicts a future where shouldn't "all 28" apps on our home screen be AI-native? "Where's the AI-native Calendar app, or the AI-native Social network?" When that transformation happens, and Chen believes it's inevitable, every marketing strategy, channel and assumption we have today becomes obsolete overnight.

The marketers who survive this transition won't be those who adapt to AI tools. They'll be those who learn to manage the strategic implications of an entirely AI-native business landscape.

Chen raises a question that should keep every marketing leader awake at night: "Will the startups of the future need fewer (or more) employees?" His analysis suggests we might see "1 person who supervises 1000 agents who code all day, and this becomes a billion dollar company."

For marketers, this creates a fascinating paradox. If AI provides "1000x more leverage," as Chen suggests, the marketing professionals who remain will need to operate at an entirely different strategic level. Instead of managing campaigns, they'll be managing AI systems that manage campaigns. Instead of analysing data, they'll be designing the frameworks that teach AI how to analyse data strategically.

But Chen also identifies the counterargument: if "some percentage of capabilities still have to be done by humans because AI can't handle them yet," companies might still "hire a ton of people." The bottleneck might become "taste" (requiring "a ton of designers") or other uniquely human capabilities.

The implication is clear: marketers who develop irreplaceable strategic judgment and taste will become more valuable than ever. Those who compete on execution? They become obsolete.

Perhaps Chen's most alarming insight for marketers concerns competitive moats. "If it becomes incredibly easy for a product to be copied instantly, how do you define a moat if AI commoditises all capabilities?"

This question strikes at the heart of modern marketing strategy. If AI can instantly replicate any campaign, any creative approach, any tactical innovation, what becomes the source of sustainable competitive advantage?

Chen offers two potential answers, both with profound marketing implications:

Network Effects Domination: In a "low technical differentiation ecosystem, user growth and network effects are all that matter." This elevates growth marketing and community building to existential importance.

Perpetual Innovation: Maybe "the ability to constantly iterate, launch new features, and create new products becomes the differentiation in itself." This requires marketers who can move at AI speed while maintaining strategic coherence.

Chen identifies a crucial tension: "Will AI make startups cheaper or more expensive to build?" While building products might become trivial, "growth and distribution cost a lot of money to get into customers' hands."

This creates a fascinating opportunity for marketers. Even though "it's relatively cheap to build a web app, acquiring users can still cost millions. The failure rate remains high because there are just so many products competing for people's attention."

In an AI-saturated world where everyone can build products instantly, the ability to cut through noise and acquire customers becomes the ultimate differentiator. This is the case for tech, ecommerce and the b2b organisation. The marketers who master this will become more valuable, not less.

Chen's most radical question might be organisational: "Does it still make sense to have separate functions like engineering, product, or design?" As building products becomes "fully multimodal with AI tech," will these disciplines "collapse into one?"

For marketers, this suggests a future where traditional role boundaries dissolve entirely. The marketing professional of tomorrow might need to understand product development, design principles, and technical implementation… not to execute these functions, but to strategically direct AI systems across all of them.

Chen's insights about location and funding have massive implications for marketing talent. If building products becomes "trivially easy," it becomes "almost like a form of content creation," enabling entrepreneurs to be "based anywhere."

This democratisation of startup creation means marketing talent faces global competition in ways never before possible. But it also means opportunity: if products become "super profitable from day one" with just "one or two people," the marketing professionals who can help scale these operations become incredibly valuable.

Chen places this transition in historical context, comparing it to the shift from "artisanal cottage industry" to "massive pools of labor working inside factories." Just as industrialisation required new business structures, AI will demand entirely new ways of organising work.

For marketers, this historical lens is crucial. We're not just adapting to new tools, we're seeing the emergence of entirely new business models that will require fundamentally different marketing approaches.

Chen's optimistic vision offers a roadmap for marketing professionals: a world where "AI enables fewer people to produce more" and where "defensibility will be achieved through killer features and technologies, not by the simple strength of distribution and monopoly."

But he also acknowledges the darker possibility: that "incumbents could slowly convert their pre-AI products into AI-native feature sets, eventually outcompeting startups."

The critical question becomes: "Will incumbents get innovation first? Or startups get distribution first?"

Chen's analysis reveals that the next few years will be defined by those who "build the business logic that sits on top" of foundation models, creating "compelling UI" and implementing AI "into every different kind of vertical industry."

For marketers, this presents both opportunity and existential threat. The professionals who learn to manage AI strategically, who become the architects of business logic rather than executors of tactics, will thrive in Chen's vision of the future.

Those who don't? They will find themselves competing with AI systems that can execute their current responsibilities faster, cheaper, and more consistently.

The startup revolution Chen describes isn't just changing how companies are built, it's redefining what it means to be valuable in the marketing profession. Will this transformation really happen? Chen's analysis suggests it's already underway.

The question is whether you'll learn to manage the machine before the machine-managed startups outmanoeuvre every company that doesn't.

I don’t have the bandwidth to follow every voice on AI. I do, however, listen to the words of those that matter. Andrew is one of those top voices and I’d highly recommend you follow and subscribe to his Substack…

I know there’s a lot of worry out there when you read about how machines can take your job. I get it. I’m championing in-house marketers all day long to help them evolve their role and to embrace AI as they learn how to Manage the Machine. Subscribe below to get my next article delivered to your inbox. All words are mine, no ‘bots are allowed to write here.