We’re back after taking a holiday hiatus, kicking it off with a recap of 2025. Not with another Top 10 whatever list, which are out there, ad nauseam, but rather with a recap of those pivotal moments or items of the year that faded from the headlines like, well, yesterday’s news. So what are some of these things you missed or otherwise overlooked?

First, eyeballs matter. In the Web 1 days, startups didn’t have supporting business models, so the ‘New Economy’s’ stock in trade/measure of success was the number of eyeballs you could muster.

Dirty Little Secret: eyeballs still matter, and now they’re everywhere. Just ask Astronomer CEO Andy Byron and CPO Kristin Cabot, “who viva la vida’d a little too hard at a Coldplay  and the internet noticed,” says Morning Brew, who singled out the episode as the ‘Viral Moment of the Year.’

“During the band’s traditional “Jumbotron Song,” the camera caught the couple mid-canoodle. When they saw themselves on-screen, the two split apart from each other like a pair of dropped AirPods, and Coldplay singer Chris Martin said, “Either they’re having an affair, or they’re just very shy.” The jury’s still out on whether the two were having an affair or, as one source told People, were just too-close friends.”

Byron and Cabot both resigned from Astronomer. At the end of the day, it’s all about trysts   trust.

In Memoriam: The penny 1792 – 2025, RIP The Penny

We always see those lists of famous people who passed this year. In terms of longevity, the penny takes the prize. Considering that the cost of minting a single one rose to 3.69 cents in the last fiscal year, continuing to keep them in circulation just didn’t make sense, pun intended. Not sure that’s the last coin we’ll see dropped by the US Mint.

Dirty litter secret: considering that the US loses about nine cents every time it churns out a new nickel, and truth be told most people pay digitally anyway, will the nickel be next? Penny for your thoughts…

Dirty little (not so) secret: the tech industry and media seem to need a tech bro superstar, a role WeWork founder and master showman Adam Neumann filled brilliantly, for a time. Finally, we have a replacement: Sam Altman, whom we view, on some level, as the alt Adam Neumann, or Adam Neumann 2.0, if you will. Hear us out:

First: consider: they both failed with their first startups. While Neumann was in college, he worked on two business ventures, including a failed idea for collapsible heeled shoe that, pun intended, fell flat. Altman’s was Loopt, “which used location-based services to enable iPhone users to find and meet new people nearby,” says Wikipedia. “Users of Loopt must register their mobile phone number, full name, and date of birth. Loopt’s privacy notice states that users can control who receives geo-location information via privacy settings. When Loopt released its native iPhone application, the software quickly gained notoriety for sending SMS invites to users’ address books, seemingly without the user’s knowledge; additionally, the SMS service failed to respond to the industry-required STOP message. Imagine! Altman ignoring regulatory requirements! No matter, just as Softbank came to Neumann 1.0’s rescue, albeit to no real avail, “after raising more than $30 million in venture capital, Loopt announced it had agreed to be acquired by Green Dot Corporation for $43.4 million in a deal that was most likely orchestrated as a marriage of convenience by joint investor Sequoia Capital.” It’s good to be a tech bro.

Both Neuman 1.0 and 2.0 are visionaries, there’s no doubt. He may not have created the concept of coworking spaces, but 1.0 did add something that had been lacking in prior iterations: community. Enter the Ponzi scheme. 1.0 would rent buildings all over the world, build out a few floors, and sign, we believe, 10-year commitments to complete the rest, declaring that the spaces were ‘90% occupied. Which they were, if you only counted the renovated floors. With a valuation of some $47+B, the company had nowhere to go but to a highly-anticipated IPO. WeWork filed its S-1 registration statement with the SEC. This was the first real look investors had at the company’s finances and governance,” MarketInsider reports, and it was an eye-opener: “losses far exceeded revenues, with no clear path to profitability.”

While 2.0 didn’t invent LLMs, ChatGPT certainly put them in the zeitgeist, making 2.0 something of a visionary as well.  What to speak of the fact that OpenAI, with its circle jerk financing, may well be the Age of AI version of Neumann 1.0’s kicking the can down the road. Which brings us to…

AI and a brand new math. While the focus has been on AI hallucinations and psychosis, not much has been attention has been given to a strange new math that seems to have sprung up in the AI space, with seemingly limitless amounts of money being poured into AI companies and apps of every stripe as far as the eye can see, without a sustainable business model in sight, speaking of WeWorkEconomics. Hopefully, lessons were learned from that debacle (to refresh your memories, WeWork went from $47+B+ to bankrupt). When asked whether he thinks “there’s an enterprise [return on investment] that would justify the spend” on trying to achieve artificial general intelligence (AGI) — OpenAI’s ill-defined priority number one — (IBM CEO Arvind Krishna) laid out some back-of-the-envelope math” for The Verge,” Futurism reported.

Dirty little secret: “It takes about $80 billion to fill up a one-gigawatt data center,” Krishna said. “That’s today’s number. If one company is going to commit 20-30 gigawatts, that’s $1.5 trillion of [capital expenditure]. Considering the “total commits” of “chasing AGI” amounts to 100 gigawatts, he reasoned, that’s “$8 trillion of [capital expenditure]. It’s my view that there’s no way you’re going to get a return on that because $8 trillion of [capital expenditure] means you need roughly $800 billion of profit just to pay for the interest,” he concluded.” Hey, that’s startup math, and we never said it added up.

Since we started with Cold Play, it seems only fitting to wrap up with the black crows – the birds, not the band, which spells its name differently anyway. While Flock has been in the spotlight of late for surveilling a lot more than just license plates, even more worrisome and ubiquitous is that Scientists Used AI to Decode Crow Sounds — What They Found About Humans Is Terrifying. “The real surveillance network is perched on power lines above your head,” reads the YouTube descriptor. ”Scientists recently trained artificial intelligence on thousands of hours of crow vocalizations, expecting meaningless animal noise. Instead, the AI detected structured language, syntax, planning behavior, and something far more disturbing: humans are the primary subject of crow communication. This short documentary explores how crows recognize individual human faces, assign identifiers, share reputations across generations, and coordinate warnings through a global avian network. From facial recognition experiments and tool-making intelligence to crow funerals, justice systems, and possible encrypted communication, the evidence suggests crows are not reacting to us—they are studying us. If AI can no longer translate their calls… did they change the language on purpose?”

The dirty little secret: was it ever really possible to be totally off the grid? Are members of the animal kingdom not only sentient, but far more aware – and devious – than we ever suspected? And what are we unwittingly teaching them? Consider the raccoon who broke into a liquor store in VA. Of course, he got drunk and passed out, but did anyone really take note of precisely where he passed out? Like extremely inebriated humans, in the loo, not far from the porcelain goddess. Coincidence, or learned behavior?

Speaking of which, and looking back at the systole and diastole of tech, at times when investors submitted to FOMO and seized on a vertical with nary a sustainable business model in sight – the early days of Web 1 come to mind and more lately, certain parts of the Green Energy ecosystem – we can only speculate in this era of outsized funding being poured into AI, as to who the winners will be in the coming year. And which companies will be circling the bowl. Onward and forward.