Zoomer? Bloomer? Doomer?

We love to categorize things. Categories (and their corporate cousins, Frameworks) make it easier for us to reason about the world. Otherwise we need to confront nuance, and who has time for that?

In the AI world, we categorize people based on how they feel about AI and its prospects for humanity. You are either a Zoomer, a Doomer, or a Bloomer¹.

🚀 Zoomer

No, this isn’t someone who uses Zoom, or is born between 1997 and 2012. In the AI context, a Zoomer is an unabashed AI cheerleader. They can’t get enough of it. They see AI as the second coming. It’s basically rapturous with these folks. For me, it’s beautifully epitomized when Sam Altman (a Zoomer), upon being asked by a reporter how OpenAI will make money responded 

The snake is eating its itself².

😱 Doomer

Much more descriptive, these folks are skeptical, scared, and often criticize AI leaders (mostly those trying to sell you something). These are the voices that continue to bring up responsible AI, bias and ethical concerns, data privacy, misinformation, job loss, existential worries, and often point to flawed business models. They’re also typically found among the 6 month pause camp³.

🌸 Bloomer

Bloomer wouldn’t have been my first choice to describe those who are cautiously optimistic but want to move thoughtfully, considering what’s helpful and what’s harmful, one step at a time. Yet here we are. Most non-tech CEOs and some AI leaders also take this middle of the road approach. And so it seems, does the public.

⭐️ *oomer

Of course, the reality is more complicated than this. While there are some dogmatists on either end, most of us are somewhere in the middle - I guess we’re Bloomers?

Personally, I bounce between the three. When I read up on AlphaEvolve⁴ , or quickly get deep research from Deep Research, or watch as Lovable writes entire apps in front of me, I’m all in, elbow-deep in the AI Kool-Aid.

Then ChatGPT spits back some AI bullshit, I listen to experts talk about the limits of our current models, and read more about astronomical valuations⁵ and I can’t help but feel skeptical.

But ultimately I land where I typically do with this stuff, which is somewhere in the boring middle.

• It’s beyond useful, it’s transformational. How can something that simply predicts the next token lead to such magical outputs?⁶

• Do I think it’s overhyped? Yes. But that’s mostly because the hype is effectively unbounded. Especially when there are big bucks behind this stuff.

• I also think we haven’t seen enough AI related nightmares. It’s true that they exist, but until someone famous is wearing an orange jumpsuit, or important companies lose a lot of money, AI will continue to accumulate tons of potential energy, waiting to be released on the unsuspecting public. Or we could wait until our geriatric representatives⁷ in the US government figure this out (age limits FTW!) or a younger cohort takes over and puts in some guardrails.

😅 What can you do?

As I mentioned before, it starts with education. Read about this stuff, learn from trusted sources, experiment safely. Don’t be afraid of it, but also appreciate that this is new for everyone.

Let me repeat myself - GenAI, in its current form, is ~2.5 years old⁸. And only in the past 12 months have companies been taking it seriously as foundational models increasingly improve enough for prime time use cases. Most of the voices out there are not experts - just enthusiasts, informed folks and some snake oil salespeople trying to ride the wave.

So be skeptical, follow the money, and use that critical reasoning many of us learned, in school or life, before ChatGPT rendered it obsolete.

¹ Reid Hoffman also talks about Gloomers - those who begrudgingly accept the slow march of AI, as it replaces jobs and people, leading to an empty existence. Definitely an apt description, but I would combine them with Doomers in the “anti / reluctant AI camp”.

² Also its definitely the right answer.

³ Though some people apparently changed their mind (for no reason at all I’m sure).

⁴ Nerd aside: AlphaEvolve, Deepmind’s Alpha model (remember AlphaGo, AlphaZero and AlphaFold?) is a coding agent that uses evolutionary algorithms to design and improve programs - basically, it writes code and then figures out how to make that code even better without needing a human to intervene (definitely not a precursor to Skynet). It also figured out how to multiply matrices (which lies at the core of all Machine Learning) more efficiently than anyone has to date (and humans have been trying since the 50s!).

⁵ Although it can lead to heart warming stories.

⁶ A perfect illustration of my favorite natural phenomenon, Emergence.

⁷ The median age of the House of Representatives has increased from 54 years old in 2000 to 57 years old in 2025.

The median age of the Senate has increased from 59 years old in 2000 to 65 years old in 2025. And I don’t have to tell you the ages of the last couple of presidents.

Our government leaders are getting older while the technology they need to regulate is getting faster, more powerful, and more societally important than ever before. It’s a bad combo 🙅 

⁸ Excluding AI researchers and some leaders who’ve been studying this stuff for decades