When companies mandate AI adoption without a use case, without a strategy, and without a business outcome in mind, they don't get transformation. They get jazz hands and nightmare token bills.

This month's System Update pulls apart what's actually happening beneath the headlines: Oracle's 21,000 layoffs attributed to "AI adoption," Amazon arming junior developers to replace senior engineers, and enterprises burning through AI budgets they cannot predict or control.

The deeper argument George K. and George A. make is harder to dismiss than the headlines. You cannot drive deterministic business outcomes with probabilistic means of production. The CEOs and CTOs who greenlit LLM adoption at scale are now facing a math problem that no earnings call language can paper over.

The free water is now a metered utility. Will the bill ever be worth paying?

The episode also turns to labor theater and what we’re giving our attention to: what we lose when institutions optimize for engagement over depth, and what it costs when an entire generation learns to consume rather than think.

Mentioned:

 * NYT on Schneider Electric’s AI adoption without layoffs [https://www.nytimes.com/2026/05/29/business/economy/ai-jobs-productivity.html?unlocked_article_code=1.tlA.-9w7.nlA_45hQK9Fn&smid=url-share]
 * Amazon tokenmaxxing mandate goes sideways [https://finance.yahoo.com/sectors/technology/articles/amazon-says-shut-down-token-161016125.html]
 * Oracle sheds 13% of its workforce amid so-called AI adoption [https://www.reuters.com/business/world-at-work/oracle-workforce-shrinks-by-about-13-2026-06-22/]
 * Amazon still hiring junior employees while also doing layoffs…? [https://youtu.be/0ii_Fl9R6bw?si=LKJ6198N6UvDgtvU]
 * The Intellectual Life of the British Working Classes [https://en.wikipedia.org/wiki/The_Intellectual_Life_of_the_British_Working_Classes], by Jonathan Rose
 * Snap’s intentional targeting of teens' attention [https://www.nytimes.com/2026/06/04/us/social-media-schools.html]
 * Denmark invests in de-screening its schools [https://www.yahoo.com/news/articles/denmark-bans-smartphones-schools-invests-182150396.html]

Token math, YOLO business strategies, and the true cost of your attention

When an institution says it's changing, how do you tell the difference between real reform and a vocabulary update?

Charlotte Duval-Lantoine has spent years studying organizations that adopt the language of culture change while leaving intact the structures that made change necessary in the first place.

The tells are subtler than most leaders want to believe, and they show up earlier than most are willing to look.

In this episode, Charlotte joins the show to talk about what organizational failure actually looks like from the inside, why decentralizing blame onto individual character is one of the most reliable signs an institution isn't serious about change, and why the absence of a feedback loop is the red flag most executives mistake for resistance.

The conversation moves from military culture into the executive boardroom quickly. We explore why the same pattern runs through both.

Mentioned:

 * Operation Honour [https://globalnews.ca/news/7614063/jonathan-vance-sexual-misconduct-operation-honour/]
 * Female representation in Canadian Armed Forces [https://ici.radio-canada.ca/rci/en/news/2247942/why-canadas-military-is-nowhere-near-meeting-its-decade-old-female-recruitment-target]
 * Cyberstarts scandal [https://www.calcalistech.com/ctechnews/article/b1a1jn00hc]
 * Big Man in Melanesian cultures [https://anthroholic.com/big-man]

Who is served & who gets protected when leaders only look up?

What if the problem with American democracy isn't that the system is broken, but that it's working exactly as intended, just not for you?

Travis Misurell, founder of FiNC (Future is Now Coalition), has spent years watching civic tech efforts try to fix democracy by building better tools. Every one of them failed. His argument: they got the sequence wrong. You don't build the technology and hope a movement follows. You build the movement first and let the technology follow.

In this episode, Travis walks us through the FiNC framework — the Digital Politics Hub, the Up/Down lens, the citizen survey, and the long-term vision of a citizen-owned civic internet where no billionaire, party, or corporation can ever take control. One share per person. No exceptions.

But we also push on the harder questions. If the system is rigged by design, what does building inside it actually accomplish? When AI aggregates open-ended citizen responses into actionable insights for candidates, what gets lost in that translation? When you surface every candidate with equal presentation, are you being neutral or are you making a choice about what equivalence means?

Travis comes back to the same place: intention. Not left or right. Not the policy. The intention. Whether a candidate is in it for you, or in it for the people writing the biggest checks.

FiNC is betting that if citizens can actually see that distinction clearly enough, the rest follows.

It's an ambitious bet. This is the conversation around it.

Learn more about the Future is Now Coalition:

 * https://futureis.org/
 * Discord community [https://discord.com/invite/yFNB2XqWtA]
 * Digital Politics Hub [https://hub.futureis.org/]

Mentioned:

•  • OpenAI donating to stop Alex Bores’s campaign for NY congressional seat [https://www.theverge.com/policy/937650/ai-alex-bores-openai-anthropic-ny12]

If US politics is rigged, can we build a new civic internet?

The travel schedules and time zone tango is real. This week, revisit one of the most downloaded episodes this season, with Rachelle Tanguay. 

What if your biggest career obstacle isn't external—it's the “broken code” running in your own head?

Rachelle Tanguay joins the show to unpack the difference between consuming self-help content and actually doing the uncomfortable work of rewiring your internal programming.

From advising deputy ministers to coaching professionals across sectors, she's seen what happens when high-performers hit the wall between knowing what to do and actually being able to execute.

This conversation cuts through the dopamine-hit culture of five-minute reels and quick fixes. Rachelle breaks down why most people confuse consuming content with doing the work, how imposter syndrome is not your own voice “chirping in your ear," and why even the most senior leaders need help to see the forest through the trees.

If you've ever wondered why smart people with all the right information still can't break through their own barriers, this episode is for you. No buzzwords, no corporate speak—just an honest look at what it takes to level up when the real bottleneck is you.

Mentioned

https://www.kornferry.com/about-us/press/71percent-of-us-ceos-experience-imposter-syndrome-new-korn-ferry-research-finds

https://www.mogawdat.com/solve-for-happy

https://jamesclear.com/atomic-habits

Leveling Up is about fixing your own broken code (REPLAY)

The hype machine spent two years telling us AI was coming for your job. Now it's quietly walking that back. Why now? Follow the money.

On this week's system update, George K. and George A. pull apart the vibe shift happening at the top of the AI economy: from Uber's COO admitting he can't draw a line between token spend and shipped features, to the broader reckoning hitting every CFO who signed a three-year AI contract without modeling what agentic workflows actually cost.

The subsidized era is over. The bill is due. And nobody has a clean answer.

But the harder question underneath all of it isn't economic. It's human.

What happens when an industry skips straight from "how big can we make it" to "what are humans even for" without stopping to answer either?

The two Georges reckon with soft skills being repackaged as vital skills, the neoliberal bargain sold to a generation of college graduates, and what Pope Leo's 42,000+word encyclical on human dignity in the age of AI gets right that most boards and governments haven't.

A tech podcast about humans. This week, more than ever.

Mentioned:

 * Jensen Huang on irresponsible proclamations [https://futurism.com/artificial-intelligence/nvidia-ceo-begs-execs-stop-fired-ai]
 * Uber COO on lack of ROI from tokenmaxxing [https://www.businessinsider.com/uber-coo-andrew-macdonald-ai-token-spending-harder-justify-2026-5]
 * Ed Zitron on OpenAI and potential collapse of Oracle [https://www.youtube.com/watch?v=NHtGXCWXyZs]
 * Daniela Amodei on the importance of the humanities [https://fortune.com/2026/02/07/anthropic-cofounder-daniela-amodei-humanities-majors-soft-skills-hiring-ai-stem/]
 * Jamie Dimon on future job skills [https://www.cnbc.com/2025/12/11/jamie-dimon-ai-will-eliminate-jobs-but-these-skills-will-get-you-opportunities.html]
 * What 2026 hiring managers are looking for [https://www.msn.com/en-us/news/insight/experts-urge-shift-to-human-skills-as-job-market-tightens/gm-GMF1A41634]
 * Pope Leo XIV’s encyclical, Magnifica Humanitas [https://www.vatican.va/content/leo-xiv/en/encyclicals/documents/20260515-magnifica-humanitas.html]
 * Marissa Alert on business outcomes planning first [https://open.spotify.com/episode/7ABtVkMeFEFVkJ0YVXjRXV?si=a10dec23e96f450a]
 * David Homan on how to build real human networks [https://open.spotify.com/episode/4iPxqxL69EKDCox6FuSK0X?si=b564db6ac39e4d35]
 * Sharon Goldman on the small town impact of the datacenter buildout [https://open.spotify.com/episode/3oiUrqViDUNpRtWTPgfLN3?si=w5XsbmbSQ--CbxhtdjLR-Q]

The token math ain’t mathin’, so time to get back to what makes us human

What if the reason most people struggle to build meaningful professional relationships isn't effort — it's that they've mistaken a transaction for a foundation?

David Homan [https://orchestratedconnecting.com/about/] has spent thirteen years building the largest private network of super connectors on the planet. Not by being the most impressive person in the room, but by being the most useful one — long before anyone asked. His thesis is that trust operates on a time horizon most people aren't patient enough to respect. That the introductions that change lives rarely pay off in weeks. They pay off in years, through chains of three to five people that no existing technology has ever been able to track — until now.

In this episode, David walks us through the architecture of real community: why action is the only currency that matters, what it actually means to honor a chain of connections, and how a moment of genuine vulnerability can outperform a hundred polished elevator pitches. He also makes a case that most of us have at least two phone calls we should have made by now — and haven't.

Learn more about David's work:

 * Orchestrating Connection [https://orchestratingconnection.com/]
 * SOAR Connect [https://soarconnect.ai/]

Why your network is shallower than you think, and how to change it

What happens when a community votes no…but the #AI datacenter construction starts anyway?

That is not a hypothetical. It’s what happened in Saline Township, Michigan, when a $16 billion OpenAI-Oracle data center was rejected by the local planning commission, rejected again by the township board, and broke ground weeks later anyway. The developer sued. The town settled. They had no real choice.

Sharon Goldman [https://fortune.com/author/sharon-goldman/]has been covering the AI data center buildout for Fortune — not from boardrooms, but from township halls, planning commission meetings, and rural communities that had never imagined something like this landing in their midst. What she’s found is a story that the technology press largely isn't telling: the buildout is a bottom-up crisis dressed up as a top-down triumph.

The numbers tell part of it. Saline Township received $14 million in community benefits from a $16 billion project, against an annual budget of $1 million. In Richland Parish, Louisiana, the land where Meta's Hyperion facility now sits was once pitched for an auto plant that would have created two to three thousand permanent jobs. The data center is promising 500. The construction workers are mostly from out of state.

And the justifying ideologies — the race with China, the national security imperative — has no finish line. This race has a vague one-upsmanship and a $700 billion spend with no clear end in sight.

What Sharon sees coming, and what she thinks the press is missing, is the backlash that is quietly becoming a political force — showing up in recall elections, in governor's races, and in the kind of conspiratorial thinking that emerges when people have lost trust and no longer believe that democracy is working for them.

You can read more of Sharon's reporting here:

 * A Michigan farm town voted down plans for a giant OpenAI-Oracle data center. Weeks later, construction began | Fortune [https://fortune.com/2026/05/06/ai-data-center-michigan-saline-politics-farmland/?sge456]
 * Meta's $27 billion AI data center is causing chaos in small town Louisiana | Fortune [https://fortune.com/2026/03/26/meta-ai-data-center-hyperion-louisiana/?sge456]
 * At the edges of the AI data center boom, rural America is up against Silicon Valley billions [https://fortune.com/2025/12/27/ai-data-centers-arizona-hassayampa-ranch/?sge456]
 * Huge AI data centers are turning local elections into fights over the future of energy [https://fortune.com/2025/10/22/ai-data-centers-politics-elections-energy/?sge456]
 * Elon Musk is pushing to build data centers in space. But they won’t solve AI’s power problems anytime soon [https://fortune.com/2026/02/19/ai-data-centers-in-space-elon-musk-power-problems/?sge456]
 * Big Tech will spend nearly $700 billion on AI this year. No one knows where the buildout ends [https://fortune.com/2026/04/30/big-tech-hyperscalers-will-spend-700-billion-on-ai-infrastructure-this-year-with-no-clear-end-in-sight-eye-on-ai/?sge456]
 * Inside a multibillion dollar AI data center powering the future of the American economy [https://fortune.com/2026/01/27/data-centers-ai-meta-microsoft-google-amazon-openai-gpu/?sge456]

What the AI datacenter build out looks like from the ground up

In the wake of more layoffs attributed to "AI," we thought it worthwhile to revisit this conversation from earlier in the year. Increasingly, AI is being used as a catch-all excuse to justify layoffs without clear return on business value, other than the stock price...so it's time to dig deeper.

What if your AI rollout isn't failing because of the technology, but because no one asked your employees how they feel about it?

Dr. Marissa Alert is a clinical psychologist who works with organizations scaling AI. Her argument is deceptively simple: the resistance leaders keep running into isn't a change management problem. It's a diagnostic failure. And until you treat it like one, AI rollouts turn into guesswork.

High usage doesn't mean successful adoption. It might just mean fear-driven compliance.

In this episode, we get into what business leaders and organizations consistently get wrong: the assumptions made about how employees will respond, the gap between leadership alignment at the top and the confusion that trickles down, and why layering an AI mandate onto a workforce already running on empty is a very different problem than a training rollout.

We also got into something harder: what it means when employees are being asked to integrate tools that might replace them, and why most leaders don't have a good answer for that question.

If your organization is tracking adoption rates and still seeing 20%, this episode is worth your time.

Mentioned

 * Jack Dorsey’s Block cuts nearly half of its staff in AI gamble [https://www.theverge.com/tech/885710/jack-dorsey-block-layoffs-job-cuts-ai]

Best of: What leaders get wrong about AI rollouts and employee adoption

What if the story we're being told about AI's inevitability is hiding something underneath?

That's the question Jessica Parker and Kimberly Becker put to George K. on their podcast, Women Talking ‘Bout AI [https://www.womentalkinboutai.com/].

This conversation is a replay from their feed. It followed the money: the special purpose vehicles, the obfuscatory financing, the concentration of risk in a handful of companies and a single island in the Taiwan Strait. But what they kept arriving at wasn't really a financial question. It was a human one.

Who has skin in the game? And what happens to the rest of us when the people building this technology can't answer what outcome they're actually trying to produce?

The conversation covers why the dot-com analogy is the wrong frame for the current investment craze, why an AI crash could starve the narrow applications that actually work, and why the "everything machine" promise was probably never going to pay for itself.

It also gets into what chatbot tutors get wrong about teaching, why we keep analogizing ourselves to whatever technology we just built, and what it might mean that generalists could be the ones who come out of this ahead.

The kind of conversation where you leave with more questions than you came in with. Which is exactly what we're after.

The Everything Machine and the Trillion-Dollar Bet [Replay]

The AI hype machine is taking up all the oxygen we need to actually stop the harm happening today.

This month we heard from three guests who didn't compare notes. Didn't coordinate. And all three circled the same thing: the #AI hype machine isn't just wrong, it's actively making things worse.

Capital flows going to “everything machines” instead applications that actually accomplish tasks. Gas turbines burning methane next to communities already carrying four times the national cancer rate. AI chatbots mathematically, not metaphorically, mathematically, engineered to reinforce delusional thinking in vulnerable users. Deepfake abuse still expanding, still mostly targeting women and minors, still unsolved. This is the real harm inventory.

This month. Right now.

Meanwhile the discourse is about whether a model might hypothetically stage a coup in five years.

We're not doing doomer porn. We're saying watch the industry’s hands, not the mouth. The boring risks are already here. The extraordinary stuff — the farmer in Morocco beating generalist models with expert-annotated field data, the researcher finding antibiotics with true wet lab work — that's also already here! It's just not getting same headlines and the funding.

System Check. This month's episodes, broken down against current events and whatever's rattling around our brainboxes.

Mentioned:

 * Smaller models find the same bugs as Mythos [https://the-decoder.com/the-myth-of-claude-mythos-crumbles-as-small-open-models-hunt-the-same-cybersecurity-bugs-anthropic-showcased/]
 * Stanford HAI 2026 AI Index [https://hai.stanford.edu/assets/files/ai_index_report_2026.pdf]
 * Discovering a new class of antibiotics [https://news.mit.edu/2023/using-ai-mit-researchers-identify-antibiotic-candidates-1220]
 * Dmitri Alperovitch's testimony on compute [https://chinaselectcommittee.house.gov/committee-activity/hearings/china-s-campaign-to-steal-america-s-ai-edge]
 * Baidu robotaxi outage [https://www.wired.com/story/robotaxi-outage-in-china-leaves-passengers-stuck-in-cars-on-highways/]
 * MIT CSAIL study on AI psychosis [https://the-decoder.com/sycophantic-ai-chatbots-can-break-even-ideal-rational-thinkers-researchers-formally-prove/]
 * NAACP lawsuit against xAI [https://naacp.org/articles/naacp-sues-xai-illegal-pollution-data-center-power-plant]
 * XAI gas turbines polluting rural communities [https://www.nbcnews.com/news/us-news/musks-ai-power-plant-generates-sound-fury-mississippi-rcna258594]
 * Northern Virginia datacenter health impacts [https://www.nbcwashington.com/news/local/northern-virginia/amid-constant-data-center-noise-sterling-residents-also-worry-about-health-impact/4091393/]
 * Human Line Project [https://pulitzercenter.org/stories/ai-psychosis-mental-health-crisis-21st-century]

AI is doing real good and real harm, but the hype is hiding both

Bare Knuckles and Brass Tacks is the tech podcast about humans. Hosted by George K and George A, this podcast examines AI, infrastructure, technology adoption, and the broader implications of tech developments through both guest interviews and news commentary.

Our guests bring honest perspectives on what's working, what's broken, and new ways to examine the roles and impacts of technology in our lives.

We challenge conventional tech industry narratives and dig into real-world consequences over hype. Whether you're deeply technical or just trying to understand how technology shapes society, this show will make you think critically about where we're headed and who's getting left behind.

George Kamide

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