This isn’t about a contest about what cohort is more or less valuable. It’s an exploration into different types of skillsets and some of what’s been going on lately with AI.

Let’s run a thought experiment about workers in general and ageism in particular. With all the talk of AI displacement, I keep wondering if there’s a less dystopian view. A lot of roles may change or vanish, but we could also see growth in niche areas. And maybe the loud claim that “we won’t need so many people” turns out to be overstated. If so, do deep skills and hard-earned judgment become more valuable, not less?

All of a sudden, some who shed too much staff, (and as is often the case, the wrong people), need to hire at least some back. Meanwhile, the nature of expertise changes such that “older” workers, wherever you want to draw that line, turn out to have a lot more value because a) the smarter machines are amazing, but turn out to still have limits, and b) AI may hollow out some early-career task bundles, and that can raise the relative value of people who can frame problems, validate outputs, and take responsibility for outcomes. I’m a huge fan of the latest AI tools and a frequent user of multiple models, several bots and agentic workflows. I’m fully buzzword compliant! And yet, in spite of the dire warnings of the viral Shumer post “Something Big Is Happening“, there may be a still be a place for talented and experienced humans. See Joe Procopio’s “It Turns Out, AI Agents Suck At Replacing White-Collar Workers” for one of many examples.

Some companies who claim they’ve cut staff thanks to AI may discover they cut too deep, losing exactly the people they really need. Meanwhile, expertise may be repriced. AI is impressive, but has limits, and it can hollow out early-career task bundles. That raises the value of people who can frame problems, validate outputs, and own outcomes. I’m a heavy user of modern AI tools and workflows, yet even with the “Something Big Is Happening” hype, there still seems to be plenty of room for talented, experienced humans See Joe Procopio’s “It Turns Out, AI Agents Suck At Replacing White-Collar Workers” for one of many examples.

Maybe this sounds naïve, but perhaps multiple cohorts will remain valuable, just in different ways. Through it’s looking to be a rocky transition. Yes, Skynet could wake up next week, but there’s also a world where things mostly work out fine. I know I’m supposed to say “if you’re not using AI in the shower, you’re doing it wrong.” I’ll work on the clickbait. For now, let’s talk about what’s actually changing.

Kids These Days

They’re often far more fluent with modern tools than we were, and they’ve grown up swimming in information; more volume, more variety, better teaching methods. But by definition, most early-career workers have limited lived experience. They may have had a few jobs in high school and college, maybe even a small side hustle, but the rest has been school, hobbies, and a first job or two.

They may also have less intuition than older cohorts did at the same age, not because they’re incapable, but because so much is abstracted away. More services handle more of life, reducing cognitive load in ways that can erode “practice-based” skills (navigation via GPS is the cliché example). Sol Rashidi calls this “Intellectual Atrophy™.” Even if that term is AI-focused, the broader pattern predates LLMs. And yet, younger workers can be astonishingly capable especially in tech while still missing some “common sense” that usually comes from scar tissue plus environment.

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First off, apologies for the bad puns in the headline. I am a dad though. So bad dad puns just come with the territory. Here, I saw a chance for a double, so had to take it.

Today it’s time to discuss some pros, cons, risks, and mitigations for the reality that our cellphones have accidentally become our gatekeepers to all manner of things digital. And often physical as well. You likely already know how integrated, (and dependent), a lot of digital activities have become on our mobile devices. But how? And what might this mean? Smartphones as identity gatekeepers has been discussed before. However, what we’re experiencing now in the mid 2020s is arguably a new level.

How did our cell phone companies become the gatekeepers of our identities?

How many things now push for multi-factor authentication via our smartphones? There’s products where it seems if you don’t have a smartphone, you’re simply not going to be able to participate. How might this play out? Do phone companies know about this? Of course. Will they try to exploit this role to just extract more fees given they’re arguably in strategically poor commodity businesses with competitive margin pressure?

Phones are no longer just credentials; they’re becoming identity custodians. Security is often thought of as three things: What you have, (such as debit card), what you know, (PIN code), and what you are, (biometrics.) With our phones we seem to have shifted from just something you have to the thing that vouches for everything else.

Recovery, coercion, or loss were not first-class design considerations.

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If you follow crypto, you’ve likely noticed the rise in DeFi activity the past several months. As Traditional Finance (TradFi) evolves and co-opts parts of crypto, we’re seeing emergence of a hybrid model called Centralized Finance (CeFi) and watching what may be an inflection year. Every year seems like “the year of SOMEthing,” but with trillions finding new pathways, it seems a fair statement now. Growth of Decentralized Finance (DeFi) despite easier Central Exchange (CEX) options is telling. DeFi remains difficult and risky. Yet it’s growing as percentage of crypto activity. Some of this may be episodic, but it reveals a deeper signal about marketplace pain points: users will endure hardship just to escape worse systems. It’s a story of value over comfort, like drivers taking a pothole-filled detour to avoid a toll road they no longer trust, but there’s someplace they’ve just got to go.

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TL;DR

If you’re a product manager crafting content production workflows for yourself, a client, or your team, start by explicitly defining your values and strategy. (After all, values like authenticity can be core to your strategic edge.) What follows are practical ideas and a walkthrough of how this plays out in a real-world example: a niche medical site powered by AI agents for discovery and ideation.

AI tools don’t need to be garbage generators. They can be useful partners when used thoughtfully with humans in the loop. Here’s just a couple of ways AIs can help in market discovery and content creation, backed by real-world examples from my niche medical community site, ACLSupport.com. Key takeaways: Leverage AI to uncover customer insights quickly and streamline production, while maintaining your unique voice. In a market where AI content tools are projected to reach $2.38 billion by 2032, and the Generative AI In Content Creation Market $134.23 billion, businesses that integrate these tools ethically will gain a competitive edge.

The AI Content Debate: Addressing Key Concerns

As AI reshapes content marketing, backlash centers on two main issues: quality and authenticity.

Quality: The “AI Generates Garbage” Debate

Critics argue AI output often feels generic, optimized for clicks rather than value. This may be true for low-effort prompts churning out clickbait, but it’s not inherent to the technology. Content creators, writers, marketers, understandably worry about disintermediation. Yet, as with any tool, results depend on the user. Poor input yields poor output, much like spellcheckers can’t fix flawed ideas.

Authenticity: The Authenticity Dilemma

The deeper unease stems from the “uncanny valley.” If you haven’t heard of this, it’s kind of a creepy feeling when something mimics humanity imperfectly. We dislike being deceived, especially where source transparency matters. Blockchain might have a partial solution by verifying origins as I’ve written about, but for now, we don’t have this industry infrastructure. According to the Content Marketing Institute’s 2025 B2B Content Marketing report, while 81% of B2B marketers use generative AI, 45% lack usage guidelines, underscoring gaps in prioritizing authenticity. As is often the case, our practices lag the cutting edge tech.

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