The Internet Belonged to Everyone Once. It Could Again.

I’ve been online long enough to remember Myspace. Like, actually remember it... the custom layouts, the top eight drama, spending forty-five minutes (at least) clicking through your favorite bands' pages while picking your profile song. Nobody was “building a personal brand.” We were just out here with our feelings and a dial-up connection, and somehow it felt like the internet belonged to us.

That feeling didn’t last, obviously. But I’ve been thinking about it a lot lately because - and I want to be careful about how I say this - I haven’t felt this excited about being online since then. Maybe more excited.

And the reason is AI.

I know. I know how that sounds.

So before I get into why I’m genuinely lit up about this moment in our lives, I want to talk about the part that’s harder, because I think it actually deserves more than a disclaimer.

AI data centers use a significant amount of water to keep their systems cool. That’s not speculation - it’s documented. And in some regions, that water draw is happening in communities that are already dealing with drought, already watching their aquifers drop. The people absorbing the biggest impact are often not the people seeing the biggest benefit. That’s a real harm. The displacement of creative workers through AI-generated content is also real. These aren’t things I’m interested in tucking into a footnote.

So where does that leave someone like me - someone who works in AI strategy and genuinely believes in what these tools can do?

It's a difficult question to debate with myself, but here’s where I keep landing: it leaves me with a responsibility, not a contradiction.

The solution to AI’s environmental footprint isn’t individual opt-out. Honestly, my personal decision to stop using (insert your own favorite LLM here) tomorrow would have essentially zero impact on a data center’s water consumption. That’s just the math. What actually moves the needle is policy, corporate accountability, pressure on the companies building this infrastructure, and real investment in better cooling technology. Those are the levers. Collective use doesn’t have to mean collective guilt, but it does mean we have to stay in the conversation, not check out of it.

What I can do - and what I think any of us operating in this space can do - is use these tools with enough intention that they actually earn their footprint. Not treating AI like a novelty. Not generating content just to generate content. Using it in ways that close gaps rather than widen them, especially for people who don’t have teams of consultants or agencies behind them.

And okay, here comes the part I get genuinely excited about.

What I’m watching happen right now reminds me of those early internet days, except the stakes are higher and (I really do believe this) the potential reach is bigger. The gap between what a well-resourced business can do and what a solo operator or small team can do is narrowing in ways that I did not even dream of seeing in my career. A blue-collar contractor who’s excellent at their trade but has never had a marketing team can now get real support building their proposals, their follow-ups, their whole client communication process. A first-generation entrepreneur who’s always had the ideas but never had the infrastructure can now actually build something that works.

Most people I talk to don’t realize yet what’s actually available to them. That genuinely surprises me every time.

I’m not naive about who captures these tools first - we’ve seen how tech rollouts go, and it’s not usually the people who need them most. But I’m not willing to hand the whole conversation over to the cynics, or to the people who’ve already figured out how to consolidate the gains for themselves. There’s real work to be done helping everyday people understand what’s available and how to use it in ways that serve their actual lives.

That’s the work I’m in.

That’s why I’m paying attention to the ethics - not because I want to perform accountability, but because the tools only live up to their potential if we’re honest about what they cost and intentional about how we use them. I’m excited about this moment. I also think it asks something of us. Honestly? I think that’s part of what makes it worth showing up for.

What An AI Consultant Got Right About Strategy on Big Brother (Even If the Twist Got Him)

This one’s for an audience that’s probably about three people wide, but here we are. I feel very moved to talk about how seeing an AI Consultant on Big Brother hit me in a specific way.

I’ve watched the show for more than a decade. I once threw myself a full Big Brother birthday weekend: competitions, secret meetings, a makeshift memory wall (fine, that was this year, when the premiere landed on my birthday, but whatever). I have a BB tattoo. I met one of my closest friends after bringing up a BB podcast at a music festival. I once sat next to Cory Wurtenberger’s brother in an Uber and spent the entire ride pretending to be so chill.

Ten years ago I watched Da’Vonne Rogers and Jason Roy on the live feeds. Their friendship was so easy it made me feel like I was in the room. I haven’t had that kind of parasocial hit since.

Every summer my schedule tilts around the show - episodes, podcasts, feeds. I’ll talk for hours about the reality of the season versus the edit. I’ll spend the warmer months debating best and worst moments like it’s an actual sport. I have strong opinions about production choices, season themes, and casting “flops” who deserve a second chance.

All of that to say, I really love Big Brother. But let’s get to the point.

Last year I added AI consulting to my work. The tools help, sure, but most of it’s just paying attention. You hear what people say they want, you watch what they actually do, and you notice the gap between the two. Then you figure out how to close it without breaking the rest of the system.

So when Jimmy introduced himself in the BB27 preseason as an AI Consultant, I flinched. Not because I doubted him, but it’s weird seeing your relatively new job title on TV. Hearing my favorite podcasters speculate what it actually means, knowing in the back of my mind that day-to-day his job is basically training for this game. Read the room, track patterns, act at the right time. I wanted to cheer but mostly I just sank lower into the couch cushions.

Then I watched him play.

Week two the house went dark - literally. Jimmy won the Black Box HOH, a pitch-black maze where most players stayed locked on their own puzzle task. He not only navigated it cleanly, he clocked Kelley pocketing a power in the dark. That’s high-level awareness: catching the quiet move while you’re still in motion.

With power in hand he targeted the solid early threat in Keanu. Spotting comp potential and momentum was a good read, even as the week was swallowed by extra powers. When Keanu and Kelley both saved themselves, the week turned into a minefield. Twist powers forced two renoms, meaning Jimmy ultimately put five different people up for eviction during his HOH reign. He pivoted to a safer choice of nominating Amy and Will - a decision that frustrated some of his alliance but kept him in line with broader house consensus. It wasn’t the biggest move, but it was one that kept his threat level low in a week where overreach could have blown up his game.

Good consultants read the flow of information before acting on it. From the start, Jimmy positioned himself where those currents moved. In week one, he linked up with Mickey and Morgan to form Triple Threat - the first named alliance of the season - and built lines into a larger voting group. He also built a genuine connection with Rachel, giving him a personal link outside the core that could feed intel and offer cover if the main alliance fractured. That’s network design, not noise, and it’s the kind of foundation that can carry you deep.

By week three, the house was still wobbling from the early-game chaos. Triple Threat was showing cracks: Mickey wasn’t fully looping Jimmy in, Morgan was exploring side channels, and the larger voting bloc he’d tapped in week one hadn’t solidified. Bonds like his with Rachel were genuine but untested under real vote pressure. And players were already floating aggressive moves before jury, chasing short-term momentum in ways that risked alienating multiple factions. In that climate it was easy for the wrong read to take hold.

Mickey gained control via the last twist on the board, mistook Jimmy’s visibility for disloyalty, and cut him - the kind of misread that tanks a strategy before it has a chance to pay off. He was evicted this past Thursday. The irony: he was one of her most loyal allies, and removing him was a short-term win for her but likely a long-term loss.

Jimmy left with the right reads, the right allies, and the ability to spot a hidden power in the dark. You can make the right read and still lose to timing, twists, and feelings. That’s not an excuse; it’s the job. Strategy lives in the gap between what should happen and what people actually do.

Seeing “AI Consultant” in a house built on chaos didn’t make the work feel loud. It made it feel accurate. The edge isn’t the tools; it’s knowing when to speak, when to wait, and spotting the one thing no one else in the dark is paying attention to.

I started the preseason wary, but from his intro package on night one I was in Jimmy’s corner. He had the reads, the measured play, and the network instincts that could have carried him deep. It’s such a loss to see him cut so early. Not because of bad reads but because of timing, paranoia, and a twist-heavy board. The season is a little less sharp (and a lot less fun) without him in it. I’ll be watching for the next time an AI Consultant ends up on a social strategy reality show. I don’t think I’ll have to wait long.

Jimmy didn’t get the ending he wanted. But the way he played - steady, directional, and early to structure - looked a lot like real life to me.

Maybe we’re all just trying to read the room a little better.

What No One Tells You About Building Systems Mid-Crisis

Why the best systems get built in a mess.

It’s easy to imagine what building strong systems looks like: a clear runway, a calm team, the luxury of time to map and iterate. That’s the fantasy. And for most founders? That’s never how it starts. Instead systems get built in motion. Processes mapped out mid-launch. Team check-ins scheduled post-burnout. Everything on the heels of a cash flow panic or a team shakeup. Not because it’s ideal, but because it’s necessary.

And here’s the part that doesn’t get said often enough: that kind of systems work - the duct-taped, decision-fatigued, just-in-time kind - is still deeply valid. Strategic, even. Not just a placeholder until something better comes along.

The Fantasy vs. The Reality

The idealized version of operations work is clean and color-coded. SOPs built before the first client. Airtable bases that anticipate everything. But most small businesses don’t build that way.

Only 49% of U.S. companies report having a formal crisis plan. And among those fewer than a quarter actively practice it. That gap between theory and readiness? It shows up fast when pressure hits.

And under pressure perfectionism doesn’t help you or your team. Research shows self-oriented perfectionism has risen significantly over the last few decades - and so has burnout. Perfectionist expectations might look like high standards, but in a crisis, they stall momentum.

How to Build Systems in Business (When You’re in a Crisis)

Real systems built mid-crisis aren’t polished. They’re functional. Often held together by Google Sheets, Slack threads, and institutional memory. They prioritize what matters now, not someday.

Frameworks like triage models (red/yellow/green) or the Incident Command System come from emergency response, and they work. In a small business that might mean shifting launches based on cash flow realities or tagging team updates by urgency. It’s not glamorous, but it keeps things moving forward.

Minimum viable systems follow the same logic. Start with the core functionality. Deliver stability fast. Iterate when things calm down.

The Weight of Building While Holding Everything

Crisis mode doesn’t just drain capacity - it messes with clarity. Decision fatigue creeps in. Strategic thinking narrows. You start reacting, not building.

Research backs this up: under high cognitive load, decision quality drops. People default to what’s easiest, not what’s best. That’s not a personal failing. It’s a brain thing.

This is where light structure helps. Tools like OKRs or even simple “Go/No-Go/Wait” choices reduce load and preserve capacity for the decisions that actually matter.

Trade-offs Are the Strategy

In a perfect world you’d fix everything, but mid-crisis, trade-offs are the strategy. You choose what to stabilize first. You let nonessentials slide.

This isn’t about settling. It’s about sequencing. MVP thinking applies to backend systems too: what’s the smallest version of this process that can work right now?

And more importantly: what’s draining you that doesn’t need to?

Building Adaptive (Not Perfect) Systems

The goal isn’t to finish. It’s to keep evolving. Adaptive systems respond to pressure. They shift with you. That’s resilience.

Chaos engineering (used by companies like Netflix) tests systems by breaking them on purpose to see where they hold and where they don’t. Not to punish, but to learn. In a small team this might look like stress-testing your client onboarding by having someone new follow the steps without help. You’ll learn a lot, fast.

You don’t need to simulate failure. You’re living it. But you can treat this phase as data. Every workaround, every breakdown is information you can build from.

A Simple Framework for Crisis System Building

Red (Critical) - What breaks the business if left unresolved? Fix it now.

Yellow (Urgent) - What’s causing friction but still functioning? Triage this next.

Green (Supportive) - What can wait? Schedule or shelve it until capacity opens up.

Pair that with a few mental load reducers:

• Daily decisions? Standardize what you can.

• Priorities? Name the top three and let the rest be background noise.

• Tools? Use what’s already working. Skip the shiny new system for now.

  
  

If you’re building systems mid-crisis, you’re not behind. You’re just building in real life, with real constraints. And what you build now might not be pretty. But it will be lived in. Yours. Strong in ways that polished systems rarely are.

Let it be messy. Let it hold. You can refine later. For now you’re doing the real work.

Sources:

• Wu, Q., Kong, Q., Duan, H., & Wang, Y. Complex Adaptive Systems Theory and Crisis Management: A Review of the Literature. National Library of Medicine, 2023.

• PR News. 49% of Companies Have a Crisis Plan—But Is It Enough to Save a Reputation?

• Curran, T., & Hill, A. P. Perfectionism Is Increasing Over Time: A Meta-Analysis of Birth Cohort Differences From 1989 to 2016. American Psychological Association, 2018.

• Park, A. How Perfectionism Fuels Burnout, and What You Can Do About It. Time Magazine, 2023.

• USDA. Introduction to the Incident Command System (ICS 100). U.S. Department of Agriculture.