Seattle vs. San Francisco
As a long time Seattleite who has traveled to Silicon Valley a ton over the last decade, my trips always follow a predictable trajectory:
Day 1
Wow! It is like Stanford meets Disneyland here! Everyone is living in the future! This place is magical!
Day 2
I love the intensity. I am using my brain in stretchy ways, talking to smart people about interesting problems. (Also, my kids are in Seattle and I am only responsible for myself, so yes I can meet you for that 9pm drink!)
Day 3
Jeez, does anyone ever talk about anything other than tech/AI/their startup? Gonna take Waymo instead of Uber just so I don't have to hear another pitch.
Day 3 evening, landing in Seattle
[exhale]
Then a few weeks later, I live the same movie over again. Repeat. Repeat. Repeat.
Seattle vs. San Francisco, the data
Ten years ago, I published some Textio data showing that San Francisco job posts used the word awesome 1.5x more often than Seattle job posts; on the other hand, Seattle used the word honest 1.5x more often than San Francisco. New Yorkers spiked high on creative; people from Honolulu picked laid back. The piece ended up hugely popular because you could see each city's local culture reflected in the data.
I was thinking about this last week when I went to SF for a business trip. I've spent a lot of time in the last few months talking to tech execs in Seattle and SF about AI transformation, and I've noticed some small but significant differences in how people talk about it. I wondered: Could I do better than anecdata?
For this 75th issue of nerd processor, I went back to where it all started: the job posts.
AI by any other name
For this story, I looked at 1,000 AI-related job posts in the Bay Area, Seattle, NYC, and Austin, TX. I chose the first 250 relevant posts I found on LinkedIn for each location. Why these spots? I picked the three biggest tech hubs in the US, plus the biggest hub in Texas for some variety away from the coasts.
I only included posts where the job location matched the company's HQ. For instance, I did not include Google jobs in Austin or Microsoft jobs in NYC. I did not include remote roles at all. I included technical jobs, marketing jobs, policy jobs, ops jobs, and more. Jobs across the seniority spectrum. Jobs at startups and big companies.
In other words, not totally scientific, but directionally interesting.
Next, I analyzed all roles for six classes of language. The classes are pretty big, so I've given some examples below to illustrate what each one contains:
- Hype: Vacuous, empty stuff like disruptive, innovative, cutting-edge
- Responsibility: Discussion of concepts like ethics, responsible AI, sustainability
- Enterprise: Language focused specifically on serving the enterprise, like enterprise-ready, production-grade, global customers
- Speed: Language focused on speed of execution, like move fast, rapid prototyping, agility
- Transformation: Focused on reimagining and rebuilding existing processes and systems, with language like transform, rearchitect, reinvent
- Research: Language with a strong research orientation, like PhD, research, publication
I left my hype in San Francisco
Naturally, a single job post can contain language from multiple categories. Check out the (real) job post excerpt below:
As you can see, just this one paragraph includes four of the six categories.
I expected to find that most posts contained language from nearly every category, regardless of the job's location. But while many posts did contain language from more than one category, few contained language from all of them. Instead, I saw significant regional variation in how people talked about AI. (Not the first time I've seen this kind of AI regional variation.)
The chart below shows the % of job posts in each location that contain language from each category:
Perhaps unsurprisingly, no one spikes higher on hype and speed than San Francisco. No one talks more about responsibility than Seattle. New York is enterprise central. And in every dimension, Austin is like San Francisco's little sister.
The bottom line: Tech may ostensibly share an industry and a language, but culture is still deeply local. Who knows what we'd find in Honolulu?
Kieran
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