Taste in the Age of AI
When that job posting’s too good to be true
Over the last year, I’ve seen several job advertising content marketing or content strategy roles at AI companies with exorbitant salaries.
What do I mean? Over $250,000 a year up to $400,000 (Canada or the U.S.). Typically, only marketing executives are paid in that range.
Such postings generate a lot of discussion in my communities. Our questions range from “What the heck is this?” to “Is it a scam?” to “How would you actually measure ROI in a job like that?”
For a long time, the postings made no sense. They’re so wildly out of proportion to what most content roles are paid. I couldn’t see the logic.
Now, I’ve got a hunch.
Leigh Bardugo is sick of cute cat slop
Fantasy author Leigh Bardugo launched Dead Beat this month, the last book in her Alex Stern trilogy. In her September newsletter, she describes being enchanted by a particular video of a cat encountering the ocean for the first time.
Her algorithm promptly showed her dozens of similar videos, none with the same impact.
Why? The confluence of mood, timing, and perspective wasn’t repeatable, even when other videos shared similar qualities. Bardugo describes a similar experience with the Netflix recommendations that appear when she finishes a show.
I’ve noticed the same pattern when I stream music. I can toggle options for “discovery” or “niche” to mix up my selections a little. Yet I often end up sinking in a tunnel of sameness and experiencing frustration that rapidly turns to boredom.
Hockey didn’t drive Heated Rivalry’s success
In recent interviews, Jacob Tierney, the showrunner for Crave’s breakout hit, Heated Rivalry, talks about a similar pattern. After the show’s success, executives said, “Oh, people want more hockey stories.”
Tierney’s the first to note that, no, that’s not quite it.
Rachel Reid’s books are obviously popular and had an existing audience. But what made Heated Rivalry an unlikely TV breakout is how Tierney’s adaptation served two wildly undervalued audience markets: romance appreciators and a diverse 2SLGBTQI+ audience.
In an interview with Kara Swisher for NPR’s podcast, Planet Money, Tierney and producing partner Brendon Brady explained their approach: identifying “a massive fan base that have not had their stories taken seriously,” purposely making a show that leaned into the books’ most popular aspects, and the fortunate casting of talented unknowns.
Tierney’s team produced a queer love story that takes connection seriously and—most importantly—doesn’t end in heartbreak. The show’s alchemy rests on its particular mix of story, casting, the existing fanbase, and a specific audience lens.
The hockey setting magnifies the tension and the stakes. It’s not the intrinsic draw.
Taste making is a fundamental human activity
Heated Rivalry isn’t the breakout success that an algorithm would have picked before November 2025. Now that it’s been done, the same forces that would send Bardugo ‘cat explores ocean’ videos until the end of time are encouraging studios to greenlight more hockey shows.
Bardugo’s newsletter and Tierney’s recent interviews both emphasize the importance of point of view in creative decisions—cultivating a unique take over time on the stories they want to tell which created the global fanbases they currently enjoy.
When I think back to those AI content job postings, what I suspect they signal is a search for people to inform an algorithm’s sense of taste while breaking slop loops.
You may not remember Twitter’s early days of “global town square,” but I do. It was easy to find people who had extraordinary taste on a variety of topics. Following their feeds enriched my life while teaching me a myriad of things and opening my thinking to new perspectives.
More than any other aspect of early-days Twitter, it’s the curation informed by taste that modern algorithms lack.
Because they aren’t people.
And it shows.
Cool. What does that mean for my career strategy?
Generative algorithms are based on predictive math. As we’ve seen, it can line up beautifully with our expectations or deliver a slop basket of diminishing returns.
If AI is incapable of human taste, one key to career longevity is having—and articulating—a unique perspective and take on your industry and its problems.
What does that mean? It’s hard to give specifics without knowing who you are and what you’ve done.
But it could mean how you:
- Structure and build products
- Make design decisions
- Communicate and brand ideas
- Assemble and lead teams
- Engage with customers and stakeholders
If you’re in the “I use AI for brainstorming” camp, you’re offloading the beginning of that taste journey to a machine that has no concept of style.
I don’t, for example, use chatbots to brainstorm this newsletter. Ever. If you want bot content, you can find it anywhere. Hell, if you want a robot’s take, every search engine feed in existence will now happily slip the AI response at the top of the page.
But thinking and perspective inform your distinct taste-making engine. If you’re several years into your career, you’ve already spent a considerable amount of your working life developing a huge internal taste engine on a variety of topics.
The question I’d put to you is:
- How can you apply that insight to your career in a way others can’t?
- Whose needs are underserved or not being taken seriously?
- What’s the niche, taste-driven perspective you bring to the table?
More importantly, does any of that perspective and the work supporting it currently show up in your LinkedIn profile, portfolio, resume, and/or on other job search materials?
In the age of AI, that’s career longevity a bot can’t generate.
I support human creativity. While the stock photos used in this post appear under an Unsplash free license, I’d like to credit Maksym Kaharlytskyi and Chelsea Pridham for their stellar work.
