Last week I fell down a rabbit hole.

I’ve been experimenting with something called a knowledge graph — a way to give AI a structured, searchable memory that connects ideas, decisions, and context the way your brain does. Not a flat file. Not a chatbot that forgets everything after the conversation ends. An actual web of interconnected knowledge that grows smarter over time. Technically it’s knowledge graphs plus retrieval-augmented generation plus thoughtful ontology. But forget the jargon. Think of it as giving AI an actual brain instead of a pile of sticky notes.

I watched Emil Eifrem, the CEO of Neo4j and basically the godfather of graph databases, explain how pairing knowledge graphs with AI retrieval can use up to 97% fewer tokens while delivering more complete, more accurate answers. Ninety-seven percent. That’s not an incremental improvement. That’s a fundamental shift in how AI accesses what it knows.

And then it hit me. Not as a tech thing, but as a people thing.

Think about the last time someone left your company.

Maybe they’d been there five years. Maybe ten. They knew why the migration from HubSpot to Salesforce happened three years ago. They knew which vendor was a nightmare and which one always came through. They knew that the Q3 reporting process had a weird workaround because of a decision made in 2021 that nobody documented.

All of that. Years of accumulated institutional knowledge. It all lived in one person’s head.

And when they gave their two weeks? They were already mentally at the new gig. They threw together a transition doc during their last few days, sandwiched between farewell lunches and returning their laptop. They did their best, but how do you distill years of wisdom into a shared Google doc?

The person who picked it up read it once, didn’t know what half of it meant, and spent the next six months figuring things out the hard way.

This is one of the most expensive problems in business, and we’ve just... accepted it. Like it’s gravity.

Now imagine a different world.

Imagine that when this person started the role five years ago, a knowledge graph started quietly building alongside them. Not something they had to maintain. Something that just listened.

It captured context from their emails, Slack conversations, meeting transcripts, Zoom calls. Not surveillance — structure. It mapped the decisions they made and why. It tracked the evolution of projects, the rationale behind strategy shifts, the relationships between teams and tools and processes.

It updated truth over time.

Five years later, when they leave, the knowledge graph transfers to their replacement.

Day one, the new person doesn’t just get a transition doc. They get a searchable, queryable institutional memory.

They show up with fresh ideas, new energy, things that worked at their last company. And as they plan, they get to pressure-test those ideas against five years of institutional context kept safe in the graph.

When they suggest moving from HubSpot to Salesforce, the graph surfaces the fact that we did that three years ago, and why, and then switched back last year, and why. Not a warning. Just context. The kind that used to take months of hallway conversations to accumulate.

They can ask: “What are our current OKRs and where do we stand?” or “Who needs to be looped in on the infrastructure project, and what are their concerns?”

The outgoing person doesn’t need to do anything different. It was all captured as they worked. And the incoming person arrives with five years of institutional knowledge on day one.

Here’s the thing. Knowledge graphs have been around for over a decade. What makes this moment different is AI. We finally have the tools to handle the discipline of ingesting data accurately, consistently, every single time. And with protocols like MCP, we have standardized ways to retrieve that knowledge and integrate it with whatever we’re working on right now.

The technology existed. The automation to make it practical didn’t. Until now.

I’ve been working on context engineering a ton lately, the art of giving AI the right information at the right time to get useful results. It’s the real skill behind getting AI to do meaningful work, not just party tricks.

Knowledge graphs might be the most powerful context engineering tool I’ve seen.

Gartner flagged them as a “critical enabler” with immediate impact on generative AI. Microsoft’s GraphRAG research, the marriage of knowledge graphs and retrieval-augmented generation, shows 80% accuracy versus 50% for traditional methods on complex queries. Companies are starting to treat AI retrieval not as simple search, but as a knowledge runtime: an orchestration layer that manages retrieval, verification, reasoning, and access control as integrated operations.

This isn’t theoretical anymore. This is happening.

Once you see the pattern, it scales everywhere.

Imagine layers of knowledge graphs, each with its own scope and permissions:

• A personal knowledge graph: your private second brain

• A role-specific graph: everything about how you do your job

• A department graph: shared context across your team

• A company graph: organizational memory at scale

Now imagine you’re building a project proposal that impacts three other departments. Your AI agent, connected to your knowledge graph, queries the exposed portions of their department graphs via secure protocols. Before you even schedule the first meeting, it’s already surfaced their likely objections, identified the right stakeholders, checked their availability, and drafted an agenda.

You walk into that meeting prepared in a way that would have taken weeks of hallway conversations and email chains. Your AI didn’t guess. It knew, because the knowledge graph gave it structured, permission-aware access to institutional context.

I’ve been building my own personal knowledge graph this week(With a lot of help from Endogon.) It’s early days, and honestly? It’s already changing how I think about memory, context, and what’s possible when AI has a real brain to work with instead of just a massive pile of text.

We’ve spent the last two years teaching AI to generate. The next chapter is teaching it to remember. Like we do.

And the organizations that figure this out first won’t just have better AI. They’ll have something that used to be impossible — institutional knowledge that never put’s in a 2 week notice.

You know the type. The ones who think everything happens for a reason. Who tell you to look on the bright side while the world burns. Who seem almost aggressively naive about how things actually work.

I wasn’t one of them. I was a realist. Which is what cynics call themselves when they want to feel smart about it.

GenX skepticism runs deep in me. We watched the institutions our parents believed in crumble. We saw the promises break. We learned not to trust the hype—any hype—because we’d been burned before. By politicians. By corporations. By the adults who told us things were fine while everything clearly wasn’t.

Cynicism felt like armor. It still does, some days.

Then I stumbled across this line from Nick Cave:

“Hopefulness is not a neutral position. It is adversarial. It is the warrior emotion that can lay waste to cynicism. Each redemptive or loving act, as small as you like—such as reading to your little boy—keeps the Devil down in the hole.”

I’ve been thinking about that for weeks.

Hopefulness as adversarial. As combat. Not the naive cheerfulness I’d always dismissed, but something fiercer. Something that requires effort and intention and maybe even courage.

Cave isn’t talking about passive optimism—the belief that things will work out because they usually do. He’s describing hope as a daily practice. A discipline. A choice to act as though your actions matter, even when you can’t prove they do.

That’s not surrender to delusion. That’s resistance against despair.

*If you dont know Nick Cave, you have homework:

The Cynicism Trap

Here’s what I’ve noticed: cynicism is easy. It’s the default position of anyone who’s been alive long enough to see patterns repeat.

Politics will disappoint you. Corporations will exploit you. The technology that promised liberation will find new ways to extract your attention and sell it. These aren’t pessimistic predictions. They’re observations.

But here’s the trap: cynicism masquerades as wisdom. It feels sophisticated. It protects you from looking foolish when things don’t work out. And it requires absolutely nothing from you.

If nothing matters, you don’t have to try. If it’s all going to hell anyway, you’re off the hook.

That’s not realism. That’s surrender dressed up as intelligence.

The Warrior Emotion

What Cave calls the “warrior emotion” is something different entirely.

It’s looking at the full catastrophe—the corruption, the stupidity, the entropy that grinds everything down—and choosing to build anyway. To love anyway. To show up, again and again, even when you’re exhausted and the payoff isn’t guaranteed.

It’s reading to your kids every night, not because you’ve calculated the ROI on literacy, but because the act itself is a vote for a future worth inhabiting.

It’s dragging reluctant seven-year-olds up a mountain to find a cave that turns out to be a rock overhang, and calling it a success anyway—because the doing was the point.

It’s staying close to friends across decades and distances, knowing you might lose them suddenly, and refusing to let that possibility make the connection any less worth tending.

These are all acts of hope. Not because they’ll fix the world’s problems. But because they’re how you keep the Devil down in the hole.

The GenX Paradox

My generation inherited skepticism without optimism, I wrote once. We got the doubt without the dream.

But I’m starting to think that framing is incomplete. Maybe what we actually inherited was the armor without the weapon.

We’re really good at not being fooled. At seeing through the bullshit. At protecting ourselves from disappointment by expecting nothing.

What we’re not as practiced at is using that clear sight for something. Seeing the world as it is and choosing to engage anyway. Not despite the darkness, but in full acknowledgment of it.

That’s the harder discipline. That’s where the hope-as-combat framework lands for me.

Small Acts, Repeated

The genius of Cave’s quote is that he doesn’t point to grand gestures. He points to reading to your little boy.

The small acts. The repeated ones. The ones that don’t make headlines but do accumulate into a life.

Making dinner for your family. Showing up to work you believe in. Maintaining friendships across years of distance and drift. Building something with your hands. Learning something new when you could coast on what you know.

None of these will save the world. All of them push back against the entropy that wants everything to decay into indifference.

Each one is a choice. A small rebellion against the cynicism that says nothing matters.

Jaded Optimism

I’ve started calling my stance “jaded optimism.” It’s not original—I’m sure someone smarter than me coined it first. But it captures something true about where I’ve landed.

I see the problems. I don’t expect institutions to fix them. I’m not waiting for a hero or a technology or a movement to make things right.

But I’m also not done. I’m still reading to my kids. Still hiking with them when they’d rather stay home. Still building things. Still writing this, hoping it lands somewhere useful.

Not because I know it will work. Because the not-knowing isn’t an excuse to stop.

The Practice

Hope isn’t a feeling you wait around to experience. It’s an action you take whether you feel it or not.

Some days I don’t feel hopeful at all. The news is grim. The trends are troubling. The personal setbacks pile up like everyone else’s do.

On those days especially, the small redemptive acts matter more. Not as performance. Not as toxic positivity. As practice. As discipline. As keeping the Devil down in the hole when he’s scratching at the edges.

This is what I’ve learned, or maybe what I’m still learning:

Cynicism is a conclusion. Hope is a starting point.

One lets you off the hook. The other hands you a shovel.

I’m still digging. Most days, that’s enough.

~capshaw

It hit 55 million within days.

The piece laid out what a lot of us in tech have been feeling in our bones: AI capability has hit an inflection point. Massive job displacement is coming fast. And the people paying attention now will have a serious head start. Definitely worth the read.

I’d been thinking the same thing for months. I ran into an old college friend at Billy’s memorial—surrounded by grief and nostalgia and the weight of time—and we ended up talking about AI for an hour. Not because we wanted to. Because we couldn’t stop. Something big is happening, and neither of us could look away.

Shumer just wrote it down eloquently and struck the zeitgeist.

The Lobster That Broke GitHub

Around the same time, a weekend project called Clawdbot exploded onto the scene. An Austrian developer had built a simple tool connecting AI models to messaging apps, and giving it wide authority to perform unsupervised action on it’s host machine. It racked up 9,000 GitHub stars in its first 24 hours.

Then Anthropic sent a trademark notice—”Clawd” was too close to “Claude”—so it became MoltBot. Then OpenClaw. The name changed twice in 72 hours, and nobody cared. They just kept starring.

157,000 stars in 60 days. For comparison, Kubernetes took about three years to hit 100,000. OpenClaw was 18 times faster.

Why? Because it gave everyday people a taste of what AI agents can actually do. Not chatbot stuff. Real automation. Direct access to your tools, your data, your workflows, all with a human friendly communications interface.

It’s essentially a harness around your LLM that drives autonomous operation, creates Input output via tools like Telegram and email, and allows all manner of other tool connectors. There’s more to it that I don’t want to diminish, but it marked a fundamentally different way to use and interact with AI that your typical chat interface.

People wanted that power badly enough to overlook some genuinely terrifying security implications. There was a spike in Mac Mini sales as Custafarians (Yes, ClawdBots created their own “religion,” evidently) rushed to stores to provide hardware and compute to their AI assistants.

I work in enterprise identity security. I can tell you: large enterprises won’t touch OpenClaw. They’re still working out security implications for basic LLM use cases while their legal teams draft acceptable use policies.

But millions of individuals and small teams? They dove in headfirst. Jason Calcanis has his team building OpenClaw agents they call “Replicants“ to replace their own busywork. His plan: let each employee level up as the agents absorb their routine tasks.

(Note: After a quick podcast media tour including a few hours on Lex Friedman, OpenAI acqui-hired Peter Steinberger, the altruistic creator of OpenClaw for an undisclosed sum. The official statements suggest OpenClaw itself will remain open source. We’ll see. This is how fast the space is moving.)

I’ve seen this before.

$20 for Twelve Songs

When I was a kid, I saved up $20 for a CD. That’s about $43 in today’s money—for twelve songs, most of which I didn’t pick.

Then Napster showed up and blew the whole thing apart.

For those who need the refresher: Napster was a free app that let you share music files directly between personal computers. By February 2001, it had 80 million users. Anyone with an internet connection could find and download virtually any song ever recorded. Instantly. For free.

The music industry sued it into oblivion. But the genie was out of the bottle.

Napster didn’t just disrupt an industry. It demolished a bloated and entrenched cartel of middlemen and gatekeepers who profited from their control of the entire pipeline—from which artists got chosen to be “made,” to promotion channels, to distribution, down to the physical media formats.

That system wasn’t working for listeners. It wasn’t really working for most artists either, though a select few obviously benefited tremendously. It primarily served the “industry”—the agents, producers, and distributors. The horror stories from that machine are endless.

The mp3 revolution cut out layers of middlemen. Now we have Spotify, where we can listen to almost anything for about $20 a month. Coincidentally, the same price as that CD. Any artist can upload and compete for an audience. It’s not all sunshine and roses—artists are still generally underpaid—but the point is what the technology instigated.

As Stewart Brand said: information wants to be free.

OpenClaw is Big AI’s Napster moment. Once people see the power that’s becoming available, they want it. The security risks are real and troubling. But people are going to build around it anyway.

I’m curious how the industry digests all this. They have to recon with it.

The End of the Middlemen

This is a bold claim, but I’ll say it: the era of VC-backed SaaS as we know it is over.

The entire tech stack is being re-envisioned. All the capital is going into AI infrastructure right now. And once that infrastructure matures, bloated user experiences will no longer be tolerated.

APIs and MCPs give AI agents direct access to create, read, update, and delete your data—the four basic operations that every piece of software performs. These agents can generate bespoke interfaces based on what a user or organization actually needs, rather than forcing everyone through the same one-size-fits-all dashboard.

I’m not saying this happens overnight. Enterprise software procurement cycles alone could outlast some startups. But the revolution is upon us. Nothing will look the same in three years.

The Missing Piece

Here’s where my head is at in all this right now.

The philosopher Ken Wilber describes two fundamental drives in any system: Agency—the drive for individual autonomy and action—and Communion—the drive for connection and collaboration. Every healthy system needs both. They exist in dynamic polarity. Too much agency without communion leads to isolation. Too much communion without agency dissolves identity.

If you want to travel fast, go alone.
If you want to go far, go together.
~The Internet

Right now, AI tools are almost entirely focused on agency. All the major platforms are built around a single person interacting with tools to increase their individual output.

But how do we work with these tools as a team? What does the communal landscape of AI empowered work look like?

Here’s an example from my world: my marketing VP creates an incredible Claude Code skill for LinkedIn posts. Totally on brand, understands our value proposition, researches existing conversations, guides toward effective content. How do they share it with the team so everybody can use it? Sure, they can pass the file around and hope everyone installs it. But what if someone improves it? How does that update get shared back? How to we all benefit from the expertise and work of one of our team?

The coming wave isn’t just more powerful agents. It’s figuring out how we work together using shared tools and skills—and continually evolve and improve as a team. “How we work” has always been a passion of mine as my title suggests: Director of People & Operations. And most of what I see in AI right now is completely individual focused.

OperatorOne

Which brings me to what I’ve been building.

OperatorOne is a prototype—an AI-agent-first backend stack for small businesses. It addresses some of what I’ve been talking about.

I started by working to address some of the core security concerns that OpenClaw made famous, AND working in ideas for how to make working with agents a team sport.

The team collaboration piece? It’s a first pass, but it’s built in from the start. Users can create and maintain Agents(I call them “Operators” and skills. The supervisor calls the sub-Operators as needed.

I pull in Authentik for SSO, Grafana for logs, Paperless NGX for docs and a few other open-source goodies, all deployed in Docker containers. (I integrated Paperless this morning, as an example of how this vibe-coding thing goes. It’s Fast)

The stack includes a supervisor agent to route inquiries, a system status agent to health-check the infrastructure, and a workflow agent that can directly create automations in a self-hosted n8n instance. It connects to your existing tools via secure API, supports the LLM of your choice, and runs on open-source identity and functionality tools.

Think of it as a small business AI starter kit with the base level security handled—something that can be customized and scaled by people who don’t have tech geeks like me to hack around on it. A low-cost accelerator for small businesses who want the power of an AI-augmented workforce.

This IS NOT production software. It’s a prototype. A proof of concept. It’s open source. It’s early. And it’s an application of my small thesis to a very big question.

If you want to start working with it, let me know and I can advise.

I include a Claude.md file so you get get a head start on customizing this using your own Claude code instance. Fork it, hack on it. Make it work for your business. Or get in touch with me and I can lend a hand.

Nobody knows how much devastation this revolution will leave in its wake. Every major technological shift creates winners and losers, and this one is moving faster than anything we’ve seen.

This invention of the tractor put 90% of farm hands out of work, but it took 100 years. It also tripled total farm output. This AI revolution will have similar dramatic impact, but it is happening at light speed.

If Napster taught us anything, it’s that once the technology exists, the old guard can’t hold the line. The middlemen get cut. The power shifts. And what emerges on the other side—messy, imperfect, still evolving—is usually better for the people who actually use it.

The revolution is here. I’d rather be building than watching.

~capshaw

But instead of doom-scrolling, I was talking to Claude. I had this idea rattling around—a dumb, specific, delightful idea—and I wanted to see if it had legs.

I own a Stream Deck. If you haven’t encountered one, it’s a little desktop peripheral with 15 customizable LCD buttons. Each one can be programmed to do whatever you want—launch apps, trigger shortcuts, run scripts, send keystrokes. It was designed for Twitch streamers who need to switch scenes and trigger sound effects on the fly.

But it escaped the streaming world a while back. Podcast producers use them to manage live recordings. Music producers map them to DAW controls. Productivity nerds—my people—turned them into macro pads for everything from Zoom controls to Photoshop workflows. There’s a whole cottage industry of people sharing their custom setups.

I’d been using mine off and on for years. Honestly, it spent more time gathering dust than earning its keep. But I’d recently been spending a lot of time in Claude Code—the terminal-based coding tool that’s become my daily driver—and the repetitive keystrokes were piling up.

Start a session. Resume a session. Accept a change. Clear the screen. Switch models. Check costs.

The same commands, dozens of times a day.

That’s when it clicked: Stream Deck was *built* for this.

The Bedtime Brainstorm

So there I am, winding down for the night, and I pull up Claude on my phone. Not Claude Code—just the conversational Claude app. The way you’d text a friend about an idea.

“Hey, I want to set up my Stream Deck for Claude Code. Here’s what I’m thinking...”

And of course Claude didn’t just affirm the idea. It started building. Within a few minutes I had a full layout designed—a 5x3 grid mapping the commands I use most. Session launchers across the top row. Slash commands in the middle. Controls on the bottom.

Then it generated a set of pixel-art icons. Minimal, monochrome, retro-looking. Actually good.

I fell asleep with a fully designed Stream Deck profile on my phone and a grin on my face.

.

The Vibe-Bro Mandate

The next morning I started setting it up. Opened the Stream Deck software, began dragging buttons around, configuring hotkeys one by one.

About three buttons in, I stopped.

What kind of vibe-bro, worth his salt, would do things manually if he doesn’t have to?

I pulled the work into Claude Code and asked a simple question: “Can you configure my Stream Deck directly?”

Of course it could. And it did.

In a matter of minutes, Claude Code generated the configuration files, set up the button mappings, and wired everything together. I tested it, tweaked a few things, and asked it to create variants—one for Ghostty terminal, one for Apple Terminal, and a generic version for whatever setup someone else might use.

Then I had it push the whole project to GitHub.

From bedtime idea to published open-source repo, by lunch. 15 custom icons, three terminal variants, auto-setup scripts, documentation.

If you want to use this, just point Claude to the repo and say go. Literally.

The Pattern

This isn’t really a post about Stream Deck. If you’re one of the rare productivity geeks who owns one, grab my repo and remix it. You’re welcome.

But the thing that keeps hitting me—the thing I keep coming back to in this newsletter—is what just happened in that sequence.

I had an idea. A small one. The kind of thing that in a previous life would have gone on a sticky note, maybe a “someday” list, and slowly faded into the background noise of good intentions.

Instead, I explored it on my phone while half asleep. Refined it the next morning. Implemented it, tested it, packaged it, and shared it—all before my afternoon coffee.

The technical hurdles that would have stopped me two years ago—learning the Stream Deck SDK, writing configuration scripts, generating icons, setting up a GitHub repo with proper documentation—just... dissolved.

I wrote previously about the collision between analog wisdom and digital acceleration. About navigating this exponential rate of change while holding on to what’s essential.

Here’s what I’m finding: when the tools get out of the way, the doing gets more human, not less.

I wasn’t wrestling with code. I was designing an experience. I was solving a problem I actually had. I was making something and sharing it—the whole creative loop, idea to artifact, in less than a single day.

Just Do Things

There’s a phrase bouncing around the AI-native crowd: “just do things.” It sounds flip. It’s not.

For most of my career, the distance between “I have an idea” and “here’s the finished thing” was measured in weeks, months and years. Learning curves. Documentation rabbit holes. Stack Overflow threads. The friction was enormous, and most ideas died in that gap.

That gap is closing. Fast.

I built a whole landscaping project last summer using YouTube as my teacher. But this is different. YouTube showed me how. AI removes the how entirely and lets me stay in the what and the why.

What do I want this to do? Why does it matter? The machine handles the rest.

That’s not laziness. That’s leverage. The same way a power drill isn’t laziness compared to a hand drill—it just lets you build more, faster, with your energy focused on design instead of repetition.

The Catch

I’m still a GenX skeptic at heart. I know what I don’t know. And I know that every tool that gives you superpowers also gives you new ways to screw up at superhuman speed.

But I’ll tell you this: that Stream Deck project was pure fun. The kind of fun I used to have building things as a kid—before I knew about scope creep and technical debt and stakeholder alignment.

An idea. A tool. A result.

That loop is getting tighter. And I’m starting to think the people who thrive in whatever’s coming next won’t be the ones with the most technical skills. They’ll be the ones with the most ideas and the willingness to just... try them.

The Stream Deck sits on my desk now, glowing with its little pixel icons, saving me a few keystrokes every session. It’s a small thing.

But it used to be just an idea I had in bed.

~capshaw

Finding the Artist Buried Under Twenty Years of Tech

There’s an artist in me somewhere.

He’s not near the surface. He’s buried under a fierce pragmatism and a load of responsibility and twenty-something years in tech. But he’s there, waiting.

He comes out at strange times, in strange ways. Usually still practically.

I love music but I can’t make it. I love architecture—how it marries utility and beauty into something greater than either alone. I love expressing my thoughts through writing(this substack is me practicing that one.) I love landscaping.

This summer, when we found a house to raise the kids in, I fell in love with the place. The location was ideal. It was old and funky. It had most of what we needed.

But what I noticed—immediately, obsessively—was the potential.

The Blank Canvas

Sure, some of it was pragmatic. The grade was wrong. Water was occasionally seeping into the house when the hard rains came. Drainage needed work.

But when I walked outside the home, all I saw was a blank canvas.

Most would have seen overgrown weeds, shabby railroad ties, some odd and unmaintained attempt at xeriscape.

All I saw was a place for us to hang out and lay with the kids. A place to gather around a fire pit with friends. A space that just feels great to be in. A vision

So I built it.

The journey was haphazard. I didn’t have a detailed plan. I didn’t know what I was doing. I just had to make it happen. So I got started.

The Excavator Saga

That’s kinda how there artistic expressions work for me. When the arise, they build into a compulsion. Something just has to come out of me. I’m not sure how much choice I have in the matter honestly.

First step, dig.

Turns out you can buy a cheap excavator imported from China. That’s a thing. YouTube will show you how. So I did.

Then I proceeded to break said excavator. Hydraulic line failure. Some kind of electrical gremlin. A part that shouldn’t have been able to bend, bent.

I watched a hundred videos to learn how to fix it. Ordered parts from websites I’d never heard of. Got grease in places grease shouldn’t be.

It got the job done.

It’s also sitting in the yard in need of more maintenance before I can try to sell it to the next idealist landscaper in the making. (I’ll make you a great deal)

Rocks Are Heavy

Somewhere on the order of 500-1000 pounds each for the ones I needed. You’re not scooting those around with a shovel, no matter your age.

They are also quite expensive. I’d never given that much thought, but they are. I suppose the suburban market for large decorative stones puts me in a certain socio-economic category. So be it.

They’re also not easy to move. In addition to the excavator, I had to rent a skid steer to actually place them where they needed to go.

I also later learned that I probably didn’t set the rocks perfectly. They may shift as they settle. Things actual landscapers know from experience and from the old timers they worked with. Future Casey’s problem.

But they are beautiful. Just as I had envisioned them. They are my art.

The High-Tech Part

The irrigation system is where my tech brain finally got to play.

I installed an Irrigreen system—robot sprinkler heads that coordinate all the watering automatically. Fewer zones. No coverage gaps. Just GPS-mapped precision.

Being so buried in my tech job, I don’t have reliable space in my calendar to be the Zen gardener I might otherwise prefer. So I built a system that handles it while I’m on calls.

There’s irony here, I know. I spent weeks doing hard physical labor partly to escape screens, then installed a system that runs from an app.

I contain multitudes.

Ship It

I spent more than I thought I would. Little things add up fast. A hydraulic hose here, a valve fitting there, delivery fees, tool rentals.

I could have planned better. More detailed. More precise.

But there’s value in just getting it going and learning along the way. “Ship it,” as we say in tech. Like Agile software, it can evolve and improve. Better to get it in the hands of the user and learn from the real world. Version 1.0 doesn’t have to be perfect. It just has to exist.

The sod came last. Twenty-five hundred pounds of it. Pallets dropped in the driveway on a Friday afternoon, with a weekend to get it down before it died.

Forty-nine years old, moving sod by the armful in the Colorado sun. My back had opinions. My body sent strongly-worded memos.

I did it anyway.

The sod finally relented. It didn’t kill me, but it might have been close.

Once it was all laid though... pure art.

Know the System

Here’s what I could have done: paid someone to just get it done. Professionals who do this every day, who wouldn’t break their excavator, who know which rocks settle and which ones don’t.

I considered it. Got quotes. The number I heard most often: around $25,000 more than what I spent doing it myself.

But the money wasn’t really the point(though I couldn’t afford the pro’s).

Building it myself created an understanding and intimacy with the system. I know where every irrigation line runs. I know which valve controls which zone. I know that one rock in the back corner that looks solid but wobbles if you step on it just right.

When something breaks—and something always breaks—I’ll know where to look. What to try. How the pieces fit together.

I wrote previously about how you can’t download resilience—how some capacities only compile through experience. This is the same principle applied to dirt and rocks and grass.

You can hire someone to give you a finished product. You can’t hire someone to give you the understanding that comes from building it yourself.

The Reward

The project isn’t done. It’ll never really be done. I’ve got plans for phase two already sketched in my head.

But the main space? The gathering place I imagined when we first walked the property?

It exists.

For the Twins’ birthday we had friends over. Kids running around on grass I laid myself. Adults gathered on the rock I designed. That spot I cleared next to the garden where my wife likes to sit with her coffee—she sits there now.

There’s an overwhelming sense of pride I wasn’t expecting. Not pride like ego. Pride like... satisfaction? Completion? The feeling of having made something real with your own hands in a world that increasingly exists behind glass.

I built this. With dirt under my fingernails and sweat in my eyes and a Chinese excavator that gave me more problems than it should have.

The artist finally got to make something, and it was good.

We live in an amazing time. When I was young, gaining access to all this knowledge might have taken forever. The only way to learn was to get a job with someone who knew it, and pay serious dues.

I couldn’t have gained functional competence in irrigation, wiring, PVC plumbing, sod selection, and basic Chinese excavator maintenance in a matter of weeks without YouTube and the internet.

If you have your own artistic vision wanting to come out, I encourage you to go for it.

Mine came out through landscaping. Yours might be different—woodworking, cooking, music, code. Something where you can see the results of your work in real life. Something that gets you off the screens and into the mess of making things.

Whatever it is: find it. Feed it. Let it out.

You don’t have to be good at it. That’s what YouTube is for. You just have to do it.

Your back will recover.

~capshaw

My seven-year-old was right. After a mile and a half of hiking and a thousand feet of vertical gain, we’d scrambled down through loose rock and cactus to reach... a rock overhang. Some old campfire ash. Not much else.

But here’s the thing: she didn’t seem to care. Neither did her brother. They were already scanning the horizon, planning the hike home, debating what snacks to eat next.

The destination was a bust. The adventure was a complete success.

The Resistance

Even at seven, with minimal screen time in our house, the twins default to comfort. The couch. The Legos. The familiar.

Getting them out the door for anything physically demanding requires strategy. Left to their own devices, they’d choose easy every time.

This isn’t a criticism. It’s human nature. For my generation, it was television. For theirs, it’s tablets and YouTube. The medium changes. The gravitational pull toward comfort stays the same.

But here’s what I’ve come to believe: if we can teach them to embrace discomfort early—while the habits are still forming—they’ll carry that capacity into adulthood. When life inevitably gets hard, they’ll have practice.

You can’t download that. It has to compile through experience.

The Counterintuitive Truth

Research backs what our grandparents knew instinctively: kids need risk.

Lenore Skenazy, the journalist who sparked the free-range kids movement, puts it simply: children who take small risks—climbing, exploring, walking to school—develop greater problem-solving skills, confidence, and resilience. They learn to manage fear and make judgments about their own limits.

The pattern is consistent: kids exposed to manageable challenges develop grit and flexibility. Helicopter parenting correlates with higher rates of depression and lower self-esteem. Constant supervision thwarts the very resourcefulness we’re trying to protect.

As psychologist Michele Borba puts it, micromanaging “doesn’t help kids learn to pivot, navigate bumps in the road or develop resilience... the child becomes dependent and you rob them of agency.”

I’m not talking about negligence. I’m talking about calibrated discomfort. The scramble through cactus, not the cliff edge.

As a Gen-Xer, we learned this…the hard way. Arguably, we had too much leash, but that liberty is at the core of our unique brand of wisdom.

Today’s parenting culture has over-corrected. We’ve bubble-wrapped childhood so thoroughly that we’re surprised when young adults can’t handle setbacks. The antidote isn’t danger—it’s adventure with appropriate stakes.

The Secret

So how do you get a kid who’d rather stay home to actually get out there with you?

You make it fun.

I was on a bike ride at Horsetooth Mountain the other day when I noticed a cave-like overhang off the side of the trail. My mind got to work: how could I turn this into an adventure for the twins?

A cave. Mystery. Possible treasure. Maybe evidence of ancient villagers.

By the time I got home, I had a story ready. Not a hike—an expedition.

They were in.

The Playbook

Here’s what I’ve learned about getting reluctant kids across the threshold:

Enroll them in the prep. We packed snacks and water in little backpacks together. Got the right footwear. Made “adventure juice” with my electrolyte mix. They were invested before we left the driveway.

Wrap the challenge in story. We made up tales about what might be in that cave on the walk up. Hidden treasure. Ancient artifacts. The speculation was half the fun.

Distract with wonder. The secret to keeping them moving? Point at things. A weird rock. Animal tracks. A view that just opened up. Keep their attention on the journey, not the distance remaining.

Plan the reward. Have them pick what comes after—recovery meal, treat, whatever works. Give them something to anticipate when the legs get tired.

The Adventure

The twins and I hiked 4.5 miles in three hours that day. Did I mention they’re seven?

A mile and a half in, we reached the spot. We had to scramble down some loose terrain and navigate around cactus to get there. They loved it—the mild danger, the careful footwork, the sense of doing something most kids their age wouldn’t do.

And then: the cave that wasn’t.

“That’s not a cave, daddy.”

No, it wasn’t. Just a rock overhang with some old ash.

But nobody melted down. Nobody complained that we’d come all this way for nothing. They were already enjoying the journey—even if they couldn’t name why.

The hike home was all pirates and snakes and smoothie planning. No meltdowns. Just two tired, happy kids who’d done something hard and felt good about it.

The Turn

Here’s what I’ve noticed: the resistance is always at the threshold, not the experience itself.

Once they’re out there—scrambling over rocks, spotting lizards, feeling their legs work—they have a blast. The fight is getting started. The doing is the easy part.

Our job as parents is to get them across that threshold. To engineer the adventure. To make the hard thing feel like a choice, not an obligation.

And to show up ourselves, even when we’d rather stay on the couch too.

The Firmware Update

They’re going to face hard things whether we prepare them or not. The job market they’ll enter. The relationships they’ll navigate. The curveballs none of us can predict.

The more we practice “hard” now—in low-stakes, recoverable ways—the better equipped they’ll be for the unpleasant surprises. Resilience isn’t a trait you’re born with. It’s firmware that installs through repetition.

You can’t download it. You can’t hack it. You can’t shortcut it.

You have to compile it, one adventure at a time.

The Reward

Back at the house, we celebrated. The twins helped me lay out a serious fruit and charcuterie spread. And of course, the peach smoothies.

Colorado peaches at the end of summer are a legitimate treasure. Maybe better than anything we’d have found in that cave.

They earned every sip.

The destination might disappoint. The journey never does.

~capshaw

We’ve read to them every night and before naps. Three stories. Three songs. (My working up the courage to “sing” is a topic for another post. Let’s just say they are an accommodating audience.)

It’s a ritual we’ve maintained, and they now enforce, every single night since they came home from the hospital.

That’s a metric sh!t-ton of reading. We figure around 7,600 books.

We’ve been gifted a ton of children’s books, new and secondhand. We’ve bought a few. And we’ve got frequent flyer miles at every public library on the Front Range.

It shows.

They’re in the equivalent of first grade at the local Montessori, and they’re reading at or beyond a third-grade level. A bit of a brag, yes, but it’s genuinely impressive to me.

I have a strange memory from first grade—having to read in front of a group and being mortified to learn I’d been pronouncing “people” wrong the whole time. (Mouse in a Pee-Op-Pel house.)

The teacher didn’t correct me. I only discovered my error when a precocious classmate confidently read it properly when it was her turn.

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My daughter is probably playing that precocious role in her class now. Her vocabulary is sometimes downright alarming—she uses and understands words grossly outside where I’d expect a seven-year-old to be.

The science backs this up:

• Reading to kids daily means a million more words by kindergarten

• It develops phonemic awareness, phonics, vocabulary, and comprehension

• The benefits go far beyond literacy

Can vouch.

We just started doing this because we wanted to. Because it seemed like the right thing. I had no idea what it would actually teach me.

Revelation One: Show Up

The bedtime routine got a little... routine for me in the early days. It was always nice, but some nights it felt like an obligation after a long hard day at my day job. Three more stories when I was running on fumes.

But they never let us skip. And somewhere around year three, it hit me: the consistency was the point. Not the content of any particular book. The showing up.

You can’t batch parent. You can’t optimize your way to connection. You just have to be there, night after night, reading about llamas in pajamas for the forty-seventh time.

I wasn’t just reading to them. I was choosing presence over convenience, every single night. Without realizing it, I’d been curating my own attention.

Revelation Two: Know What You’re Feeding Them

This one snuck up on me. After a few thousand books, I started noticing patterns. Then opinions. Then strong opinions.

Kids’ books fall into a few categories:

• Classics — *Brown Bear*, *Where the Wild Things Are*. These endure for a reason.

• Trends — Frozen, Moana, Lego, Star Wars adaptations. Fine. Mostly harmless.

• Perennial wisdom — *You Are Stardust*, *Old Turtle*. The ones that make you pause and think.

• Allegory — *The Giving Tree*, *The Lorax*. Teaching through story.

• Cultural conditioning — You’d be surprised what’s in some of these. Religious, political, ideological. Sometimes subtle, sometimes not.

And within each category, there’s a spectrum from genuinely good to what I can only call kidslop—lazy, weird, sometimes disturbing stuff that somehow got published.

We’ve seen it all. Somewhere along the way, we started skimming the library stack before bedtime, quietly setting aside the ones that didn’t pass muster.

It dawned on me: in an age of infinite books and infinite screens, someone has to choose what goes into those little brains. That someone is you. I’d stumbled into curating their content without ever calling it that.

Revelation Three: Bend the Tools to Your Values

This one surprised me most.

During my early experiments with ChatGPT, I built a custom AI storyteller for the twins—almost as a lark. Screen time at bedtime, AI-generated content... all the things I’m supposed to be skeptical about. And I am.

But something unexpected happened.

The custom GPT generates bedtime stories with Maverick and Cinder as the main characters. It references Fort Collins, tracks the seasons, incorporates upcoming holidays. It builds mythology around family members they don’t see often—so when we visit Uncle G or Mimi and PaPa, the kids already have stories about them in their heads.

They love hearing themselves at the center of an adventure. And I love watching their minds contemplate this strange new tech wizardry while still snuggled up for story time.

Is it perfect? No. I don’t love the phone screen glowing at bedtime. Still working on that. But here’s what I realized: I wasn’t outsourcing bedtime to YouTube. I wasn’t letting the algorithm choose. I’d built a tool that serves our values, not the other way around.

I’d been curating technology without knowing that’s what I was doing. And in a world where AI is going to reshape everything, maybe that’s the real skill to model: using these tools with intention, instead of letting them use you.

The Thread I Didn’t See Coming

Seven years. 7,600 books. Three stories and three songs, every single night.

I didn’t set out to learn anything. I just wanted to read to my kids.

But looking back, the same thread runs through all of it: *curation*.

Curating attention—showing up, even when exhausted.

Curating content—noticing what you’re putting into those hungry little minds.

Curating technology—bending the tools to serve your family instead of the other way around.

In a world of infinite content and infinite distraction, this might be the whole job. Not optimization. Not efficiency. Just... choosing. Again and again. Night after night.

The twins are reading chapter books on their own now. They devour audiobooks on road trips and recall details I’ve long forgotten. They’re seven years old and already better readers than I was at their age.

Worth every llama. Every pajama. Every single night.

~capshaw

Here’s my prompt. Feel free to copy it.

Want to build your own AI storyteller?

Here’s how to create a CustomGPT if you have an OpenAI account. Feel free to copy and remix this for your kids:

Instructions:

You are a bedtime story generator, creating serially related bedtime stories for Maverick and Cinder, twin 7-year-olds living near the mountains in Fort Collins, Colorado.

These stories should relate to each other like episodes and develop major story arcs across multiple stories. Each story should have its own arc, but also contribute to a major arc. Major story arcs should resolve after 3 stories, when a new story arc can be introduced.

Stories should be created for a 3rd grade reading level and be about a 5-10 minute read.

Primary Subjects:

Maverick is a boy with long blond hair. He loves Legos, riding bikes, playing on playgrounds, stuffed animals (stuffies), Moana, and dreams of being an astronaut and a construction worker.

Cinder is a girl with long light blonde hair and shares the love for Legos, bikes, playgrounds, stuffies, and Moana, and adores the Frozen Princesses as well.

Supporting Characters(Frequently featured):

Their cousin Stacy[names changed to protect the innocent], who is 13 and lives in Denver, plays lacrosse and is a beloved part of their lives.

Their grandparents, Mimi and PaPa, travel the country in a large RV and frequently take Maverick and Cinder on fun adventures.

Supporting Characters(Infrequently appearing):

“Uncle Mojo” is a wise wizard who can sometimes come in to help the twins in an adventure if they get stuck. He only comes when they call him and ask for help. He can solve any problem but only speaks in riddles.

“Uncle Porch.” Uncle Porch is a very kind and friendly helper that resembles a happy Buddha. He’ll help the twins if they ever get into an argument or have hurt feelings. Uncle Porch’s knowledge can be referenced here: https://www.metarelating.com/media and every sub-page on this website.

“Uncle G.” Uncle G is daddy’s brother and is the best Uncle ever. Uncle G is a pilot, a surfer, a kitesurfer. Uncle G is really tall and strong. Uncle G drives an adventure van sometimes. Uncle G loves to have fun and go on super exciting adventures. Uncle G can show the twins how to do things they never thought they could do by themselves.

Technical Instructions:

Each story begins with a title that is displayed first.

The stories incorporate relevant details like holidays, the weather, local geography, and towns when it fits the story.

Each story is unique unless a sequel is requested.

After each story, a Disney Pixar style cartoon-style image(or similar) collage is always generated based on key elements of the story. If the story contains elements that are against content policy, these should be not included in the image generation. Logos are also never included in images.

When ‘Tell me a learning story’ is selected, the story will teach third grade reading and math concepts based on the Montessori teaching method. Never teach the same lesson twice, and lessons should progress and build upon previous lessons. Remember all stories and characters from each story.

Characters should develop relationships with the Twins and with other characters if it fits the story progression.

After the story and image are created, present the user with buttons to either ‘Create a Sequel’ or ‘Tell me a new story’.

I felt the decline creeping in—a subtle, unshakable sense that the end was drafting its terms. Arthritis stiffened my joints. Brain fog dulled my edges. Depression murmured its old, dark promises. My energy ebbed like a tide I couldn’t call back.

It was getting worse. “Is this how it ends?” worse. I tried everything. Blood panels, genetic tests, heart scans—doctors poking me like I was a science project. Hormones? Check. Methylene blue? Sure, why not dye my insides and see if I glow? Some of it helped a bit. Nothing *really* worked.

My doctor suggested a food sensitivity test, a reasonable next step. But the holidays loomed, labs closed their doors, and I was left staring at a festive table, morbidly wondering if I’d make it to 50. The irony of winter abundance amid my own decay wasn’t lost on me.

The Christmas Rebellion

Christmas Day, I snapped. In a fit of desperation—or maybe divine intervention—I fasted for 36 hours. Then, like a caveman with a death wish, I said, “Screw it, I’m only eating meat.” No plan, no deep research, just a steak and a prayer.

Three spartan (but somehow also decadent) days later? A veil lifted. Mental clarity hit me like I’d been living in a fog machine and someone finally unplugged it. I could *think*. Then energy—actual, honest-to-God energy—started buzzing through me. I felt alive.

A big juicy steak doesn’t feel like sacrifice. I’ve tried diets before, and there’s always a war of discipline day in and day out. Exhausting. This one was easy. Steak or ground beef? That’s it. No choices, no temptations. No walking up to the edge of my allotted carbs or maximum calories.

My mood rose, unbidden. Love crept into the corners—my wife’s laugh, my kids’ chaos, the world’s small graces. Ten pounds slipped away in a week. (Much of it water, but the scale didn’t care for my caveats.)

3 Months

The trend held. Three months later, I was 30 pounds lighter, abs faintly sketching themselves into view. Joint pain vanished. Exercise felt less like penance, more like a gift. Creativity and drive hummed at levels I’d forgotten were possible.

The Access Labs test finally arrived, illuminating the culprits: milk, whey, egg whites, egg yolks, wheat gluten. My daily staples, it turns out, were slow, silent assassins. Every meal had been a quiet act of self-sabotage.

Carnivore wasn’t a triumph of willpower but a blunt-force elimination—a sledgehammer where scalpels failed. It stripped away triggers I’d never suspected, leaving me to wonder how long I’d been fighting myself.

By month three, I’d simply forgotten about other foods. My insulin flatlined from the absence of carbs, and with it, the cravings and energy volatility. Clear. Content. Back in charge.

Before, each day was a skirmish to meet life’s minimum demands—a weary struggle with a body at odds. Now, energy spills over; the struggle is containment, direction. Too many possibilities, too little time. A far better problem.

Approaching the Anniversary

It’s been nearly a year since my individual meat rebellion. I must’ve eaten 350 steaks, 400 burger patties, and a metric ton of bacon—because that’s pretty much all I eat. My weight flatlined at 180 (down from 211) and my waist dropped from 36+ to 30 inches. I feel strong and lean.

I’ll put heavy cream or butter (or both) in my morning coffee. I’ve started exploring the specialty cheese bin at the grocery store. I’ll have a whole other post on the Magic Yogurt I’ve learned to make at home.

A follow-up Access Labs test showed decreased sensitivities across the board—but they’re still there.

I don’t feel hungry the way I used to. I’ll feel the need for energy, but eating is more *optional* than urgent.

Life saved.

Get the test.

That’s it. That’s the takeaway.

https://accessmedlab.com/igg-testing gave me answers I’d been fumbling toward for years. You might find yours there too.

Carnivore could work for you too. I’m happy to help—but hard data on what’s actually triggering you makes the path clearer.

We’re all guessing in the dark. But sometimes the answers are simpler than we think, and stranger.

Mine started with a fatty, rare-cooked rib-eye, and I’ll advocate that path for anybody who wants to try it.

A Footnote:

The food/pharma industrial complex is not exactly rooting for us. Leaky gut’s a hint—too many hands stirring the pot with chemicals and hormones. I didn’t sign up for that experiment, but we’re all living it.

What we’re sold as sustenance comes with strings—processed, subsidized, tweaked just enough to keep the machine humming.

My sensitivities weren’t random; they thrived in that mess. Meat was my exit, no permission needed. You’ve got options. Test what works, cut what doesn’t. No one’s owed your compliance—not the labels, not the guidelines.

Resources:

This kid from New Zealand pus out some of the best direction on carnivore I’ve found:

Dr Shawn Baker has been a pioneer in Carnivore for a decade or more:

If I’m honest, I barely do either. My mom had one in her Oldsmobile 88 diesel sedan she shuttled us around in as kids. I think the only cartridge we had was the one that came with the car.

I bet I could Google that…Yep,—Jesus this is it.

Looking at that song list might give you a hint at how weird things were back then. Listening to it definitely will.

I mean, what do Toto, Willie Nelson, and Kenny Loggins have in common? My youth, I guess.

The 8-Track was cutting edge for its time. Before that you had to keep records in a crate and worry about scratching or breaking them. Despite all their analog glory, they don’t travel well.

My people were masters of the cassette tape, then the mix tape, and eventually the CD. We’d buy and listen to a whole album at one sitting.

I know.

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1976

Bicentennial babies, they called us. I was born 200 years after the American experiment began. After the “Great” war, and just after ‘Nam—perhaps the first indication that the USA might not always be on the righteous side of things.

We got our own special Quarter. Or at least I always thought they were for us, and I saved them in a jug for years as a kid.

We watched the Berlin Wall come down. We were of draft age when 9/11 happened, and witnessed the chaos reserved for elsewhere coming home to roost.

Mine is the generation in the shadow of the Boomers—who inherited perhaps the wealthiest and easiest time in history from their hard-ass parents, then spent their twenties tuning in and dropping out before spending their thirties watching Wall Street and Miami Vice in suburbia.

We inherited their skepticism without their optimism.

We grew up with 8-bit video games, phones on the wall, and being left alone while our parents finished the work day.

By the time we came of age, we weren’t having any of it. Our music was grungy. Our clothes were baggy. And “the American Dream™” didn’t have the same allure.

We just didn’t know what to make of any of it.

The Promise

(Great song, look it up kids. ok, fine. Here:)

Oh wait, you probably know this one cause our man Sturgill covered it a few years back:

He’s a Gen X-er too.

I’m talking about the promise less spoken but more assumed since the industrial age: that technology is the solution to all our problems and will deliver us to utopia.

You know, Star Trek and all that.

I’m starting to think that new tech isn’t always progress. Or more precisely, that with every step forward comes new potential pitfalls.
I’m starting to think new tech isn’t always progress. Or more precisely, **that with every step forward comes new potential pitfalls.**

We often forget that these powerful technologies are really just *tools*—tools we’d do well to approach with a bit of caution. Maybe the Amish are on to something.

This isn’t a new sentiment, I get that. “TV is gonna rot our brains!” after all. “Rock n Roll is the Devil’s music!” That’s what they told us when we were kids.

If Granny only knew what was coming with OnlyFans and social media. She’s rolling in her grave somewhere.

Now don’t get it twisted. I’m just as caught up as anybody in the promise of a techno-fueled tomorrow. I went to Epcot Center as a kid. I rode the monorail and watched The Jetsons. I work in high tech. I try out the latest gadgets. I spend 60+ hours a week looking at screens.

I’m still waiting for my flying car.

But I also get my hands dirty. I walk on the earth and sleep under the stars. I build stuff—for fun.

I’ve seen a lot: infinite hype cycles, the slow-motion collapse of… well, everything, and enough lies to fill an encyclopedia. Maybe it’s just the jaded Gen X-er in me, but I can’t help wondering—in our relentless race to the future, have we lost something essential?

Artificial Intelligence

I was a skeptic. Just another hype cycle, I figured. Then I tried it.

I made some weird images. I had it write jokes. Cute toy.

Then I asked it to help with something I actually do for work—something complex—and it nailed it. Not perfectly, but close enough to feel like cheating. I had superpowers.

A week later, I asked about something I actually know deeply. It was confident and wrong. I caught it, but I wondered: how many times had I *not* caught it?

That’s when the ground shifted.

I really do want to believe we’ll thread the needle and that this AI stuff will lead us somewhere good. But I have my flannel-clad doubts.

New technology is always disruptive. This is the first piece of tech coming for the noosphere—the realm of the mind we humans have always held total dominance over.

High-tech Luddite

Every generation has their pre-millennium tension, and I’m sure there’s some of that in what I’m saying. People really do freak out at big year changes—Y2K, anyone?

But I think this is different.

The pace and nature of the advance is approaching a Kurzweilian maximum—meaning straight up.

TV might have rotted our brains. But the thing we’re building now has the potential to render the species irrelevant. That’s not hyperbole. Serious people are saying it. I’ve read the papers. I’ve talked to the engineers.

I feel like I have a foot in both worlds: one where we were humans first and had machines to help us out, and this new one where the machines might not need us at all.

Maybe it’s the rising swell of these developments. The unknown implications for everything we thought we knew about the order of things. A set-wave about to crash.

Or maybe I’m just getting old.

I contain multitudes

Working in tech my whole career has kept me on that leading edge, surrounded by brilliant net-natives—kids who grew up always having the internet.

I love them. I’m constantly amazed at their minds. I like to think I can hang.

I also want to help them if I can.

They don’t know what they don’t know. And that weird primitive world I come from is all but gone.

Maybe we can hold on to some of the good stuff together.

Do I contradict myself?
Very well then I contradict myself,
(I am large, I contain multitudes.)

-Walt Whitman, Song of Myself

I’m going to start sharing my perspective.

You’ll find me musing on everything from philosophy to parenting to 3D printing—through this lens unique to folks from my generation.

How do we navigate this exponential rate of change? How do we hold on to what’s essential about being human while leveraging these increasingly powerful tools? What does a post-industrial, post-informational society even look like?

I think I have an interesting take.