Story 1: Two Weeks vs Ten Minutes

Ben is a non-technical colleague that I respect, and I was livid that he was being taken advantage of.

His affordable, ~$30/hour dev was quoting him two weeks to deliver a feature that (I kid you not) was basically a single API query and exporting it into an HTML table.

I sat dumbfounded. I called bullshit.

This was May 2026, 6 months after the “holy shit” moment when Opus 4.5 turned the coding world upside down.

I asked Ben to let me screen-share while I fired up Claude Code. I then verbally brain-dumped a prompt.

“Make a dummy database from industry X. Then create a single HTML page. Then have that page call said database and convert it into an HTML table.”

We went back to talking. And somewhere between two and ten minutes later, the demo loaded on screen.

I turned to Ben. “So you’re telling me your developer with Claude Code is going to take two weeks to do that?”

This lunch meeting was the turning point for how his startup operated. Within days, they hired a new, AI-first developer to upskill the team. Within weeks, a client demo deadline that felt impossible was doable.

It took a technical, Forward Deployed Executive (FDX) to get the Ben over the hump.

Why I Hated the “Forward Deployed Engineer” Title

It’s ok to admit when you were wrong, and I was dead wrong.

The first time I heard about “forward deployed engineers” (FDEs), I thought it was yet another stupid marketing trick.

Isn’t this just software services?

Isn’t this just staff augmentation?

But it was fucking genius, because it solved a problem as old as time.

The Gap

In The Success Principles, mega-author Jack Canfield repeats the mantra of “closing the gap between where you are and where you want to be.”

The self-help, professional consulting, and executive coaching industries are built around this premise of gap closing.

And this gap is MASSIVE in the AI space right now. A few research examples (thank you, Perplexity!):

• 95% of enterprise GenAI pilots produced no measurable return. MIT’s Project NANDA looked at 300+ deployments, 52 case studies, and 153 leadership surveys; only 5% generated real financial value.

• 56% of CEOs saw neither higher revenue nor lower costs from AI in the past 12 months. Only 12% got both. That’s PwC asking 4,454 CEOs across 95 countries.

• 72% of CEOs now call themselves the primary AI decision-maker at their company, roughly double a year ago. Nearly all of them plan to keep funding AI whether or not they can prove it works.

Companies WANT to be at the bleeding edge, and yet most are feeling further and further behind… and their attempts at catching up just aren’t working.

Closing The Gap with FDEs

Palantir recognized the AI gap early. They knew the fastest way to close the gap, get customers to a win, and become indispensable for their clients was to embed the very same elite engineers that built the tech alongside their customers’ teams. Even better, these FDEs would keep identifying more opportunities to expand and grow the accounts, creating a virtuous loop.

So they coined a new job title and went all in on this approach.

I would argue that while the technique wasn’t new (it’s basically staff aug), the mindset was very different.

So how did FDE’s solve this?

Buying is Easy; Actualizing is Hard

Enterprise companies know that change is hard.

This is why sales cycles are typically 18-24 months, and most will not bring on more than 1-2 new tools per cycle.

You have to deal with things like…

• Data migrations

• Tooling integrations

• Code refactors

• Hiring new people

• Training existing people

• Capacity management

• Comms (internal, external)

• Coordination (internal, external)

• Board politics

• C-suite buy-in

• Budgets

• Mercury Retrograde (just checking if you’re still reading)

Oh, and ultimately achieve the goal or ROI you set out to achieve. Otherwise, WTF did you start this in the first place?!?

With this laundry list of challenges and headwinds, it’s no wonder why there’s a >90% failure rate for enterprise AI initiatives.

Add to that that the fact that the world is changing more rapidly than ever, sometimes on a quarterly, monthly, or weekly basis.

But all hope is not lost.

Solutions! Embedding Engineers AND Executives

The goal is to close the gap, but how?

FDEs were a critical FIRST part of that solution. They brought…

• Proximity. They sit inside the customer’s team and see the actual workflow instead of the sanitized version that showed up in the RFP.

• Speed. Something working in weeks (or days… or hours) rather than quarters, which breaks the pilot purgatory that produced that 95% number.

• Ownership of the outcome. They’re measured on whether the customer wins, not on closing the sale or watching usage metrics through a dashboard.

But IMHO, that wasn’t enough. Yes, this addressed the technical gaps. These SEAL Team Six-type engineers can largely address business objectives, but they’re still often too far away from the key decision makers that are critical for decisions and culture.

Two citations that emphasize this.

1. Dan Shipper of Every once said one of the strongest leading indicators of AI adoption is whether a CEO is an avid user of AI (and usually sharing the wins to the team). I’ve witnessed this juxtaposition personally.

2. PwC came at the same idea from the other direction. They found that CEOs whose organizations built strong AI foundations are 3x more likely to report meaningful financial returns. The difference between the 12% who win and the 56% who don’t comes down to foundations and embedding.

The last part is critical. You need an AI foundation, which requires AI champions at the top. And since companies can’t just rapidly hire and replace the entire C-suite in a month, they need outside help… they need a Forward Deployed Executives to help level them all up.

What exactly does an FDX look like? More on that in a minute.

Remember the story of Ben? He didn’t even know he needed an FDE-like resource! He first needed an FDX, an AI-first founder type that could identify the problem and get him over the mental/emotional hurdles that prevented him from making it a priority to hire an AI-first engineer.

The AI Bottleneck is Humans

The smart folks at Anthropic (I’m looking at you, Dario) told us that AI was going to start replacing 50% of white-collar work starting by 2030.

Whoops. It doesn’t look like it’s happening… yet.

We may get their eventually, but right now the bottleneck isn’t the models, the products, the agents, or the token costs.

The gap is how fast humans can successfully absorb AI practices, products, and methods into their companies.

And that’s just the mechanics. There’s also the psychology. Here’s a direct quote from an executive I work with.

“You’re just my security blanket, so I want you here.”

AI is scary and risky. Even if someone hands you a perfect answer, they may not take it unless they trust you.

Why? The rate of change and the potential risks of AI mistakes are so high that they create so much fear, uncertainty, and doubt (FUD). It’s so massive these days that even seasoned executives who have weathered the 2008 market crash and the 2020 COVID lockdowns are affected.

Hell, there’s an executive that I’ve heard about through a friend of a friend. He’s been suffering from regular panic attacks, even throwing up multiple times a week because he’s so afraid of falling behind. I’ve heard others in my direct network say they feel the same pressure.

These execs don’t need another LinkedIn article with 5 new tips. They need a trusted confident to describe their challenges and, most importantly, help them close the gap.

They need someone with both technical AND leadership experience that can help them navigate this chaos and complexity.

What Makes a Good FDX

History doesn’t repeat, but it does rhyme.

A decade ago, one of the hottest hires on the market was a “solutions architect.” This mythical hire had skills and experiences across 3 key areas.

• Technical (i.e. deep understanding of architecture, best practices, etc)

• Management (i.e. costs, timelines, team makeup, etc)

• Entrepreneurial (i.e. business needs, ROI, market opportunities)

You may recognize these factors from the bestselling book The E-Myth.

And rare was the person who could do all three. They were outstanding hires.

Now we’re in an era where the gap requires all three of these plus a few more.

• Adaptable (i.e. able to react rapidly, with high tolerance for change)

• AI-first (i.e. approaching everything from an AI-first mentality)

• DIY, DWY, DFY (i.e. the ability to build, teach, and delegate these skills)

I’ve been doing AI upskilling now for over a year, and you’d be amazed at the number of executives who want and need a coach to sit in the trenches with them (to test, tinker, optimize, vent, etc.). They need someone that’s like them enough to translate into their words and needs as well as technical enough to knock down walls with and for them.

Can I Help?

Ok I didn’t mean to make this a pitch, but why not? Here’s a bit about me:

• MIT BS + PhD.

• 18 years of startup experience (6x co-founder)

• Enterprise, SMB, and security/compliance experience.

• Techstars Mentor x5 cohorts.

• Coached hundreds of people.

• 12 months of AI-first consulting, training, up-skilling.

• Wrote a book, Save Your Startup, to help founders with actionable playbooks.

Enough about me. What matters most is an honest question to. How can I help?

I’d be happy to riff on any ideas. DM me on LinkedIn, X, or Substack.

Now back to the article close…

Story 2: “My CTO is an OpenClaw”

Tyler is a non-technical colleague that I respect, and I was thrilled he trusted me with such an ambitious bet.

I had been sharing AI news with him for weeks/month. Then on Sunday, January 25th, 2026, he asked, “Thoughts on clawdbot?” (later rebranded to OpenClaw). I basically shared that I bought a Mac mini and was about to go all-in. I said it would be as pivotal as Opus 4.5, and the world would understand this in under a month.

Tyler didn’t just say “cool” and move on. Within one week, he had two OpenClaws running his company, one as the CTO. By week two, he was already shipping 3-5x and reduced his team size by half. He’s the CEO of a small, and aggressively AI-first startup.

Similar to Ben, an FDE wasn’t the bottleneck (at first). The first step was another colleague, but an aggressively AI-pilled one, to push him to take a swing. And swing he did. Now, the student became the teacher. Tyler is now so far ahead of me it’s not funny. And that’s awesome. We continue to push each other.

The Billion Dollar Opportunity

I made a bold claim in the title. Is this really a billion-dollar (or more) opportunity?

Absolutely.

But did you catch that I used the word “unblock” vs “unlock” in the title? Why?

First, “unlock” is an overused AI-slop word… abused like my previous favorite punctuation, the em-dash.

It’s also the wrong metaphor. What’s sitting in the way is more like blockage of our own creation. It’s human, it’s emotional, and clearing it is unglamorous work that somebody has to physically show up and do.

US companies are easily spending 100’s of billions of dollars in aggregate to adopt AI as fast as possible.

And again, >90% of these things fail to achieve the ROI… yet.

FDEs were a key part of that solution for forward-thinking companies like Palantir. However, industry-wide, it’s not enough.

If we see enough FDX’s help scope, scale, and deliver better results and move these percentages higher, we’re going to see higher percentages of AI adoption with real, measurable ROIs. This will justify additional investment. This will accelerate a virtuous cycle.

A billion-dollar opportunity is awesome, but that’s just the beginning. The bigger story is the career opportunity for executives worried about AI replacing them (no need to have panic attacks when the amount of inbound demand is rising). Maybe AI will replace us all eventually, but not today in 2026. Today there’s a gold rush of opportunity because there are gaps everywhere, and businesses are just looking for people to help close these gaps.

Maybe that’s you.

I know it’s certainly me.

Which is why I’m so excited about where my career is headed leading into 2027.

I hope you’re feeling more hope than anxiety.

Until next time ✌️

PS. Wrote By Me

There’s a trend these days of Substack articles being 90-100% AI-generated with little to no human editing. That’s a shame. This article is the opposite. I rewrote this draft 4 times by hand before asking AI for assistance, pulling in some stats and research. Then I used Grammarly for spelling, grammar, and brevity suggestions. Then I rewrote sections again because I’m determined to focus and followthrough.

I reject many of Grammarly’s suggestions because I like an occasional cuss word. I also love run-on sentences, ellipses, and other writing no-nos. In the age of AI perfection, I prefer to be proudly imperfect. I hope you’d consider approaching your writing the same way.

So logically, if AI can help us complete tasks 2-100x faster than before, we should be UNDERWORKED and experiencing ZERO burnout, right?

If only it were that simple.

ALL THE THINGS!

You may be too young to recognize this meme, but it’s the feeling most people in tech had when AI started accelerating their efficiency.

Why?

Because for years, all of us had dozens, if not hundreds, of side projects we could have started but had to shelve because there weren’t enough hours in a day.

Then AI came along and teased us with a seductive lie…

Claude: “But, maybe you can do it all now that I’m here!”

For the past decade, I’ve been a repeat startup founder + new dad + always ambitious person. I had over 100 article titles + outlines in draft. I had a someday maybe list full of 50 projects to start “when I had the time.”

I started to dip my toe in the water and YOLO some of these side projects between meetings. Queuing up Claude in 5-minute increments and then letting it rip before jumping to the next call.

The crazy thing is it started to work…

Things I wanted to try, explore, and write about were working, and this only 10X’d my ambition to start more projects! Spin more plates. ALL THE THINGS!

The Crash

You already know how this ends.

Because it always ends this way.

There’s the quote: “You can have anything in life, but not everything.”

Even when AI can 100x your productivity on a single task, we humans still have a finite number of seconds in a day.

And we’re not machines. We’re not meant to operate at 100% speed every waking hour.

What happened was I started to notice I had something like 40 “proof of concept” projects going on, and I was starting to feel that pang of burnout growing inside me. Each project was a new open loop, a new responsibility, and a new thing to tend to.

I used AI to reduce my required work, so I invented an endless amount of make-work.

Make Work: “work assigned or done chiefly to keep one busy”

Don’t get me wrong, I had fun along the way. But this is a failed strategy I had to course correct.

Less, But Better

In his book Essentialism, Greg McKeown beats the drum about doing less, but better.

I think this is critical in an age of AI.

Rather than using AI to expand the number of things you’re doing (horizontal), I have come to realize the best strategy is to go way farther on the things that matter (vertical).

In short, focus and follow through.

Personal Examples

I didn’t intend to write this article this morning, but I had to to stop myself.

I had another one titled “Sesame Street Simple” (coming soon) that I was trying to rush out the door. However, as I kept sitting with that article, I realized I wasn’t giving it my very best. Maybe it was a solid B/B-, but the topic deserves an A+ effort to have the impact I want it to make.

So I stopped.

And I decided to give it at least 2-3 more revisions with focused time and attention.

Partial vs Total Eclipse

Am I being a perfectionist?

An overdramatic artisan?

I don’t think so.

Garry Tan penned an amazing article about the difference between a partial and a total eclipse.

The main thrust? You think the difference between a 99% and a 100% eclipse is a mere 1%, a rounding error. But visually, it’s a 100x difference. A partial eclipse feels like the dimming of a cloud. A full eclipse is like an eerie nighttime befalling the world.

The experiences could not be more different in effect.

Likewise, things that we love (products, books, movies, etc.) pay the price of that last 1% to deliver that 100% experience.

Here’s the hard part. That last 1% may feel like 50-90% of the total time, which is why so many people just say “good enough” and ship.

The Better Way Forward

Now that AI makes things 2-100x more efficient, there’s no reason not to pay the price of that last 1%.

The only way to do that is to be ruthlessly focused and then follow through on the few open projects that matter.

I’m still making lots of mistakes because it’s so hard not to chase the shiny (ALL THE THINGS), but the rewards are worth it.

To that end, I hope to publish fewer articles, but go deeper on each one.

You and I both deserve that.

And no one should be experiencing burnout in the age of AI. The entire point was to offload all the hard labor so we could be save time, focus on what matters, and be more human.

A clear example of this is the utilization vs touch time curve. If your day is scheduled to the minute, a simple 5-minute phone call may take you days or weeks to get to. But if you always have a slack 30-60 minutes in your day, you can get to it in a few hours (if not immediately).

This was beautifully illustrated in this passage of The Phoenix Project.

So my hunch was, the same mechanism would apply to a game I used to play…

What’s Incorrect

Do you remember slider puzzles? If you were a child of the 80s and 90s, you probably saw one.

Anyway! As a kid, these things were frustrating. You had one free space and had to work really hard to get things sorted in the right way. If you don’t know what you’re doing, it can take you hundreds of moves (similar to a newb trying to solve a Rubik’s cube).

My line of thinking went, what if I had two or three spaces open? I bet it could halve the time because you have more degrees of freedom.

10 years ago, I didn’t have the patience or access to someone that could test this. It just felt true.

Enter AI

AI makes it stupid simple to turn ideas into code into demos. So I was like “Hey, I should make a simple web page to show this to drive the point home.”

Problem. The app worked beautifully, but not in the way I had hoped.

I expected it to always be much faster when going from 1 to 2 open spaces, but that wasn’t always true. Depending on the starting position, it could be even or even slower! Check out this screenshot.

Luckily, all hope was not lost. When AI ran 1,200 simulations, I was able to confirm that I was directionally right, even if the jump wasn’t as dramatic as I had hoped.

When you’re an expert and use the fastest path to a solution, the extra space does save some time (up to 2x), but it’s not a 3-5x gain that I expected. Check out the following animated gif of a typical run.

You can run this yourself by visiting the test page here.

A Humbling Experience

Now that the costs of running a simulation are so low, it’s easier to validate AND invalidate claims and beliefs. This is awesome if your ego can take the hit.

And that’s what sucks.

These programs were packed with knowledge I paid hard-earned money for, but it’s difficult or impossible to access the information on demand. At least once a month (and sometimes weekly), I refer people to these resources, but it’s hard to quickly pull up the exact CD, track, and minute/second where the quote is from.

Want to recall Jim Loehr’s 15-second recovery ritual from a Memory Optimizer disc? Your options: re-listen to 7 hours of CDs, or trust a 15-year-old memory.

There’s no search. No way to cite a passage. No way to hand a chapter to an AI assistant and ask, “What was that quote from Caroline Myss about a nation’s collective self-esteem?”

A $2,000 course I own outright is LESS useful to me than a random blog post that shows up in a 5-second Google search.

Again, that sucks.

Finally, I want to go further than search. I want this knowledge to be pluggable in my AI tools. I want it all in markdown files where it can be linked, searched, quoted, and pulled into context when I’m working on something related. Everything stuck in audio just… sits there.

Again, that sucks.

So I fixed this. I used AI to run the following pipeline for courses I bought as CDs or through online portals.

1. Transcribe (verbatim with timestamps)

2. Distill (down to an executive summary per file)

3. Vault (in my Obsidian for easy search/read)

4. Connect (into all my AI tools as needed)

This all happens with a local speech-to-text (free, private, runs on my Mac) and AI agents doing the distillation; the first program took an afternoon, including building the pipeline. Every program after that took one command. 9 programs and 55 hours of audio later, my “dead” course library is roughly 430 searchable notes.

It’s magic. I have another 200-300 hours worth of material to go through, but I can already yank a quote out of thin air in seconds, something that would have taken me 15-30 minutes of digging before.

And if you want a skill file to get started, here’s a generic one to adapt with your AI Agent of choice.

Yes, humans are flawed, and they’ll never meet our idealized expectations.

However, I would argue that it’s more painful to find out that you’ve lost the chance forever.

I know because I just discovered that SIX of my heroes have died in the past 5-10 years.

I was updating my bucket list, and I decided to add a few people I’ve been meaning to connect with since college. Googling led to one obituary after another, and I finally gave up. Too depressing.

The Tail End

Tim Urban wrote an extensive article on this subject. The stat that still shocks me is that by the time a kid turns 18, a parent has already spent 93% of their time together. The remaining 7% happens for holiday gatherings and summer vacations.

The paradox is that you think you have decades of time ahead, but the actual aggregate amount of time left is in the single digits.

Half-Lifes

There’s a term in science called the half-life. It’s defined as the amount of time it takes for half of the radioactive material to decay into something else. Some materials last forever (e.g., uranium), and others decay quickly (e.g., Oxygen-15 and other isotopes used for medical scans).

I’ve been thinking about this ever since finding out many of my heroes were dead, many of them way earlier than expected (early 50s). My assumption is that they were all younger and would live longer. I thought I had 30 years easy. In reality, the half-life was 10 years. And then another half-life of 10 years.

To those who aren’t good with math, I’ll summarize. Life is fucking short.

Do This Now

Now, at age 45 and looking around at those who remain (mostly in their 50s and 60s), I realize I have less time than I think to make it happen. The optimist thinks I have decades. The reality is that if I don’t make it happen by 2030, all bets are off. Too much risk that life happens and another hero becomes an obituary.

I realize this is a bit morbid to think about. However, I lost both my mom and biological dad a month ago. I lost my sister-in-law in her late 30s two years ago. And one of my good friends in Oklahoma has a brother-in-law battling stage 4 cancer at age 38. If anything, it’s just being a realist.

We all have less time than we think! If a person matters, make the time now to avoid regret later.

• The people are REALLY nice.

• Making friends is REALLY hard.

Strange, yes? But stick with me.

Oklahomans are genuinely, reliably nice. Like SUPER nice. It’s one of the things I love most about living here.

On any given day:

• Every stranger will wave and say hello.

• The guy at the coffee shop asks about your weekend (and genuinely waits for the answer).

• Then they go home to hang with friends they’ve had since the third grade.

That last part was what the warning was about. Most people here have been here forever. They’ve got their people, their church, their standing Friday-night plans, and they are not shopping for anyone new. So you get five friendly minutes (and rarely a sixth). And you’re never invited to hang out or join the BBQ. The friendliness is real. There are just no open seats at the table.

For a while, I took it personally. Then I saw the “nice vs. mean” meme.

Nice vs Mean

You’ve probably seen it, and it basically divides the country into 4 quadrants:

• Northwest: “acts nice, is nice”

• Northeast: “acts mean, in mean”

• Southeast: “acts nice, is mean”

• Southwest: “acts mean, is nice”

Yes, it’s a gross over-generalization (to the point where you can find different conflicting versions of this meme!). Still, there is some truth to it.

I lived in Boston from 1999 to 2009, and everyone just felt angry all the time. However, when you actually got through to someone, they were as nice as can be. Then there’s the stereotype of the southern sorority girl, who is as outwardly friendly but secretly judging you.

I personally disliked the particular comparison because I feel “meanness” was the wrong dimension to score, so I made a different grid.

Two New Axes: Approachability & Depth

Approachability. How easy it is to get in the door.

Depth. Whether anything’s on the other side of that door.

The niceness label hid this from me: the two move independently.

• A place can be wide open at the front door, but feel empty inside.

• Or locked at the front, but it’s full of heart and soul inside.

Plot the places I’ve lived (or know people from there), and they each land in a corner.

Oklahoma. Low wall, warm welcome. Nothing behind it to hold onto. You’re through the door before you notice, and the door doesn’t go anywhere.

Argentina. The corner everyone wants. Low wall AND real depth. You meet someone at lunch and you’re actual friends by dinner. Open and lasting in the same breath.

Denver. A higher bar, and not much waiting past it either, because half the city is on its way somewhere else. Friendly enough. But nobody’s putting 20 years into a friendship with someone who might leave by spring.

Denmark. This is the one that gave the whole idea its name. A guy in my men’s group told the story: the Danes are tough to crack. Cold at the gate, slow to let you past it. But once you’re in, you are FAMILY for life. He called it “high wall, warm home.” Apparently, others refer to it as “hard shell, soft core.” Well said.

What the map is actually good for

Two things.

One, it explains the friction. That lonely feeling inside a friendly town stops being a paradox once you separate “easy to meet” from “easy to keep.”

Oklahoma is warm and shallow for a newcomer. Naming that, I quit expecting the warmth to ripen into weeknight dinners on its own. It was never going to, and that’s fine. Oklahoma is just the wrong corner for what I came looking for.

Two, don’t take it personally. You can’t force people to be something they’re not.

When you want depth, and you’ve landed in a warm-but-shallow place, what you’re feeling is the local wiring, the default setting of nearly everyone around you. It says nothing about whether you’re worth knowing. And it runs the other way too. The person who reads as cold may have a warm home behind a high wall, and the wall is just how their world is built. Stick around long enough and you find out.

I’ve been on both sides of that.

People who lit up at me for ninety seconds and evaporated. And people who felt shut until, six months later, they turned into some of the best friends I have.

What you want out of a friendship might not match the norms of the place you’re standing in. Worth knowing early, because it changes where you spend your effort.

In a high-wall-warm-home place, you spend it on patience. The wall is the toll, and the home is real, so you pay it.

In a low-wall, shallow place, you stop waiting for an invitation that was never coming. You go build the depth yourself, with the few people looking for the same thing you are.

The map won’t lower a wall or warm a home. It just tells you which one you’re standing in front of, so you stop blaming yourself for the architecture… and you can make a high-agency decision on what to do about it.

It’s also terrifying and overwhelming. How can we hope to have a chance to stand out from the crowd? Is the bar of exceptionalism too high?

Back to Reality

It’s sobering (and sad) to reflect on our day to day interactions with the people we meet. Aa simple example: in the last 30 days, do you have one memorable moment interacting with a person at a grocery store, on public transportation, or at a coffee shop? If you are like most people, those situations are seen more like a chore than as an opportunity to have a meaningful connection with another human being. I know because I’ve had experiences in my past where I’ve spent 30 minutes getting groceries and never once looked at a person in the eyes. If I were forced to have small talk, I would generally end with a one-word answer and let the conversation die off from there.

I have no data to back this claim, but here are my observations of how conversations with strangers break down. Of course, this will change based on location, age, upbringing, culture, and a variety of other factors. Still, I bet you have at least observed this at some point in your own life.

• Typical: Other people in the immediate vicinity might as well not be there. Most people are not noticed unless they are in the way or making a scene. Actual communication barely acknowledges the other person and is limited to only what is necessary to complete a transaction. This represents almost half of all conversations with strangers public.

• Friendly: Conversation may start with a routine “how you doing?” and ends with a quick exchange of “I’m fine” or “good” by both parties. It’s friendly, but there is no real thought or feeling that went into it.

• Above Average: A person might actually ask a random question, OR a person may respond with a small talk question with a more thoughtful, meaningful answer. This conversation may last for 2-3 more sentences before returning to silence.

• Great: There might even be an exchange of names along with an “it was a pleasure to meet you!” at the end. Already, this experience is in the top 5% of all interactions with strangers.

• Exceptional: Someone watching the interaction might think the two people have known each other for years because it appeared to be an honest to God, meaningful conversation. In these situations, the two people are likely to remember each other the next time they cross paths. These types of interactions happy (in my experience) less than 1% of the time and are, therefore, exceptional.

By the way, let’s compare the two extremes just to show you how little effort it takes to go from a non-event to something much better.

Friendly Interaction

• Store Clerk: Hi, how are you doing?

• Shopper: Good. You?

• Store Clerk: I’m fine. Nice day out, right?

• Shopper: Yes it’s beautiful out.

• Store Clerk: Here’s your change, have a good day!

Exceptional Interaction

• Store Clerk: Hi, how are you doing?

• Shopper: Oh just peachy!

• Store Clerk: Peachy, eh?

• Shopper: Yeah I love that phrase because sometimes life is warm and fuzzy, and sometimes it’s the pits.

• Store Clerk: Ha! That’s clever.

• Shopper: Well, tell that to my wife. The dad jokes can really wear her out because they eventually become too routine.

• Store Clerk: Oh I hear you! We have 3 kids, and my husband always makes terrible puns.

• Shopper: Oh yeah? That’s cool that you have 3 kids. Any fun plans for the weekend to enjoy the summer or do you like to keep it nice and relaxing.

And so on until…

• Shopper: Well I hope you have a good night with the kiddos, Mary!

• Store Clerk: You too Rick! See you next time. Say hi to Evelyn.

Now here’s a question: was there anything that was rocket science here? Yes, it’s helpful to have a few quips or convo variations already on hand. However, the key factors were showing interest in the other person, not responding with stock answers, and bringing in a little vulnerability first to allow the other to loosen up and waken up from their routine. It’s not rocket science, and yet it’s by far the exception.

And Then There’s The Internet

Things get even better (or worse) when you are on the internet, specifically social media. There is a known rule of thumb in Internet Culture called the 1% rule. Basically, only 1% of all users of the system actually contribute new, meaningful content whereas ~10% will share/edit that content, and 90% will just lurk and consume. If you are actively posting new things, congratulations! You are exceptional.

And then there is the darker side when negativity is amplified online and where people (particularly marginalized) are abused and harassed into oblivion. For the individuals dealing with this day in and day out, the bar of an exceptional experience is so low that you don’t even have to be friendly. Frankly, as long as you’re not a dick people are pumped! I’m looking at you Twitter…

And Everywhere Else…

The bar of exceptionalism (loosely defined as being above in the top 1 to 10%) is very achievable in other aspects of life as well. Government statistics show that less than 5% of Americans exercise 30 minutes a day. Given that the average American consumes a combined 7 hours a day of TV and Internet usage, this is not a hard metric to hit.

Yes, some areas of life are much more competitive. Career is one. Salary is one. Sports is another. But many, like just being a decent human being or staying reasonably healthy, are a cake walk if you merely try and commit to it. Hell, even something as simple as having good manners or giving a damn can be a novelty in a world full of apathy.

Is this article my best work? No, not at all. But I had an idea, and I wanted to see it launched in the world versus die (as a result of lack of attention) in my ideas list. Everyone in your life has ideas, and only a few, the exceptions are actually doing something about it. Be that person that tries, commits, and executes and people will take notice. You will be the 1% of people on a social media platform that actually has something to say versus repeat it (10%) or sit on the sidelines (90%). You will be the exception. Be the exception!

Photo by Pedro Kümmel on Unsplash. Even the small (yet important) act of being kind is a remarkable quality to have.

Article originally published Friday, July 6, 2018 on rickmanelius.com

This could not have gone better. It was beautiful, and I’ll have more to share on it another day after I process the stories, pictures, and memories.

2. Banana Water

I think my brother is pulling my leg, but he regaled us at breakfast for a full 15 minutes about several people who had life-changing experiences with… banana water? My bet is it’s more snake oil than the next hot trend, but I’m willing to try anything once. But $5/can?!? Now that’s bananas.

3. 45-year-old tree

My best friend’s mom showed me this giant, 100-foot-tall tree she had planted in her backyard when her son was born. It was a great reminder that while good things take a long, long time to grow, you can still experience the beauty of it all in your lifetime if you’re patient and stick around long enough.

4. Principles

I’m only a chapter into Ray Dalio’s book, and it’s good. I was a huge silver bug (thanks, Uncle Warren!) and didn’t realize the Hunt brothers were the richest people in the world until they almost went bankrupt by mistiming the market. It’s a good reminder that timing is everything, and no one is immune to the booms and busts of life.

5. Reconnection

It’s funny how many times I’ve written off a friendship because 5-10 years went by. And yet I’ve now had more than 5 experiences where we’ve picked up like a day hasn’t gone by. Maybe I’m just lucky, or maybe I should make it a point to keep reconnecting with others from my past.

6. New Connections

Apparently, it’s still harder to make friends than it’s ever been. I admit that it does take some intentionality. However, the reverse is also true… people are craving to find connection. If you provide the means, you’d be surprised how many people show up.

7. Breaking Sleep Cycles

My 70-year-old uncle works 7 consecutive 12-hour overnight shifts as a pharmacist. And somehow he manages to get in 20+ miles of biking a day. He’s my standard for health and longevity.

One thing that surprised me was how sporadic his sleep is. If he wants to nap at 3 PM, no problem. If he wants to get up and start reading at 2 AM, no problem.

So I couldn’t sleep last night, which is why I’m up writing this at 4:19 AM. Might suffer later, but I’m enjoying writing while the world is quiet.

Thanks for Listening

It means the world to know you’re out there, and I appreciate all the comments and feedback.

Until next week! Thank you 🙏

The Captain Class was just such a book.

Several times, I had to pause the Audible version and pull my car over to take notes and consider the ramifications.

Best of all, the material wasn’t just some talking head giving a hot take on a sports talk radio show. Sam Walker had done extensive research across every sport and every era, looking for patterns that explained what made exceptional teams so exceptional.

The big theme of the book was that much of it came down to an elite captain, but not in the way most business books would portray it. Key characteristics that made me rethink leadership at the most elite level:

• They didn’t break the rules, but they often pushed the limits of norms and behaviors.

• They had extreme emotional control.

• They weren’t the prima donnas. They often did the grunt work in the background.

Why Revisit This Book Now?

I have the privilege of speaking with team and company leaders daily.

As you might have guessed from my previous articles, everyone is struggling with AI. More specifically:

• Predicting the future of work, management, and leadership.

• How should they adapt their strategies and tactics to be effective leaders in this new paradigm?

To be fair, I struggle at times too. There are lots of conflicting predictions, advice, etc. However, startup life has always returned me to one key lesson: it’s less important to have the right answer than to have the right algorithm. And in a time of rapid, persistent, and accelerating change, my bet is to widen my search and research over different styles and philosophies to find the best algorithms for adaptability.

I’m betting there are some lessons to revisit in The Captain Class (and other leadership books) because these lessons will be even more applicable in the age of AI.

The number one that comes to mind? Sheer doggedness and grit. I see a lot of leaders throwing up their hands and giving up trying to keep up with it all. I think this is the wrong approach. Staying curious, determined, and gritty… that has been extremely helpful for me over the past few months. While others are quitting, I’m doubling down. The result? More and more people are coming to me for advice because they know I’m actively testing and experimenting every day.

Your mileage may vary with this book. However, if you’re looking for a different angle on leadership, consider adding it to your reading queue.

1. I didn’t plan on reposting my mom’s obituary on my personal website. However, the newspaper we paid $700 to publish it in print edition has decided to place it behind a paywall on the web. This is bullshit, but I’m not going to fight it.

2. The celebration-of-life gathering will take place at FFCS from 2-5 PM on Saturday May 30th. All are welcome to attend. We will provide everyone an opportunity to write a card as a final message to Joddy.

Below is the original obituary, published here.

Kathleen Joddy Rajter

Kathleen “Joddy” Rajter (née Manelius), age 73, of Fultonville, NY, passed away on Thursday, April 30, 2026. She leaves behind three sons, two granddaughters, and a community that she loved and was loved dearly by.

Born June 18, 1952 in Fultonville to Marion and Roy Manelius, Joddy would go on to know the community better than almost anyone. After graduating from Fonda Fultonville Central High School, Joddy became secretary of the Elementary School and remained in that position for nearly 40 years. For Joddy, this was more than a job, it was a calling. She became the linchpin in the community and effectively its welcoming committee, especially for families new to the area. She greeted thousands of students and parents over her career and she remembered all of them. She watched as many of those students grew up to become teachers and colleagues themselves. Joddy lived fully into life’s simple and most beautiful pleasures and taught all around her how to indulge in them too; she’d often leave fresh-picked strawberries on a teacher’s desk, or a handwritten card just because, to offerings of small things she found when she thought of you. She had a gift for noticing other people’s quiet acts of kindness and wouldn’t hesitate to name them out loud. She was always an advocate for the kids who needed one; known to float lunch money out of her own pocket to a child whose parent had forgotten that morning or introducing a child new to the area to other students with similar interests, and sometimes even to her own kids.

Joddy was also relentlessly resourceful and industrious. On top of her day job, she ran community garage sales, cleaned houses, worked the ticket booth at the county fair every year, and operated her own second-hand store. And she did it all with style. Joddy was known across the county for her bold outfits and her unshakable willingness to wear exactly what she wanted, whenever she wanted. She made an entrance and played by her own rules.

Joddy’s three boys were truly her life’s work. Throughout the hardships that life brought forward her determination to give them a stable home was palpable, and she met every storm with the same fierce will and stubborn love she brought to everything else. Pride is too small of a word for how she felt about her boys. She made certain they had every opportunity to play sports, to learn, and to chase the dreams they wanted. Those opportunities led her sons Rick to MIT, Dan to Northeastern, and Ryan to Ohio Tech.

She is survived by her sons, Rick Francis Manelius (Emily Pearson Manelius), Dan Alexander Rajter, and Ryan D. Kelly Rajter; her brother, Warren Kelly Manelius; her granddaughters, Evelyn Noelle Manelius and Laurel Hope Manelius; and her ex husband, Stanley Paul Rajter, whom she kept a lifelong and loving friendship with. She is predeceased by her parents, Roy Alexander Manelius and Marion Lerne Gardner, and her daughter-in-law Elissa Rae Rajter.

A remembrance will take place on May 30th from 2-5PM at the Fonda Fultonville Middle School cafeteria, with Eulogies at 3PM. Bring a story to share about Joddy if you’d like. In lieu of flowers, memorial donations in Joddy’s memory may be made to Recovery.org.

She told the story about how she would walk through graveyards and notice the little dash between the dates.

She then said (paraphrasing) “our lives are summarized by that one little dash between the dates.”

I’ll never forget that.

A few weeks ago, I was walking through the Edmond, OK, cemetery north of Danforth. I noticed dozens of graves that ended within the World War I years. I tried to imagine the years of their birth and the lives they lived. I imagine how many of their lives were abruptly cut short to ensure people like me continued to live in a free country.

But damn… still? An entire life is one dash? It seems almost disrespectful to the dead to not have more to say on each stone.

Joddy

I probably shouldn’t write this while it’s all so raw.

However, I’m not sure it’s wise to wait either.

I promise to write a more thoughtful piece that does her justice.

For those who don’t know, my mom died last Thursday. She was 73.

She was also my hero growing up.

She also had many, many demons. I wrote about this before here and here (thank you, Internet Archive).

However, she was also gritty, stubborn, and determined. She managed to make the best life she could for her three boys.

She also lived a full life, impacting thousands upon thousands of people in the community. She was my mom, sure. However, she was like a mother to so many of the students that she onboarded into the school. 30 years and 3,000 kids (and their parents) later… she continued the legacy that my grandfather started at the school.

Don’t Be a Dash, Be The Asterisk

My mom wasn’t a dash.

She was an asterisk *

She was a person the sat at the intersection and intersected with everyone. She touched so many lives (of those living and dead).

I’m already getting texts and emails. The things she did for people. The way she made them feel. The way she helped out. What she meant to them. I cry with each one.

This is nothing new to me. When she retired, her wall was full of cards and posters. As her son, it was overwhelming and inspiring. Could I imagine a life where I impacted that many people?! It would be a tall order. I’m still nowhere close, but I’m trying.

Time to Heal

There’s more to come, but just know that I may go dark for a little bit. I’ve been expecting this since her first suicide hospitalization a decade ago. Still, despite already grieving for so long, it still hurts… a lot. The more the love, the more the grief. It’s beautifully painful, and now I need to process that for a bit.

Much love and appreciation to you all.

If you can, hug a loved one. Call your mom (and dad) if they are still alive.

And just once… walk around the graveyard… and refuse to accept being a single fucking dash. Be an asterisk.

RIP, Mom

Quick context before the post: I get a fair number of inbound questions from founders and tech leaders (DMs, emails, over coffee, etc). A lot of them have answers that are worth sharing to others.

So I’m starting a new section of this newsletter called (maybe called Inbound?). When a question lands that I think other operators are quietly wrestling with, I’ll sanitize it (no names, no identifying details, no industry details that could give someone away) and post my answer here.

If you want to opt in, great! They’ll come through this same feed. If you’d prefer to receive only my regular weekly content, I’ll send instructions next time on how to manage your settings.

This is the first one. I hope you like it.

The Background

A founder is facing VERY expensive costs from Anthropic while undergoing an SOC 2 audit. I noted that open-weight AI models like Deepseek are showing a similar performance, but at 25x less cost per token.

Unfortunately, it’s a Chinese model hosted on Chinese servers, which led to the question…

The Question

Paraphrased and Sanitized…

“How do you feel about hooking your code to a Chinese-hosted model? I’m going through SOC 2 compliance and multiple enterprise audits, and this scares me.”

The Short Answer

DO NOT USE HOSTED SERVICES FROM CHINA!

Sending your data to China is always a no-no IMHO.

The Real Answer

It’s a great question, and the fear is real. However, there are multiple issues at play. Let’s break it down.

1. The model itself: its weights, its training data, its origin

2. The harness: the IDE plugin or agent that actually runs it

3. The context: what data your tooling is allowed to send

4. Where inference runs: your machine, a Western cloud, or a server in China

Let’s take them one at a time.

Layer 1: The model

When people say “DeepSeek is a Chinese model,” they mean the weights were trained in China. But weights are static artifacts. They’re matrices of numbers. They sit on a disk like a PDF. They can’t phone home. They can’t steal anything (at least directly). You can hash them, audit them, run them air-gapped on a laptop in a Faraday cage if you really want to.

Auditors don’t care that DeepSeek was trained in Hangzhou any more than they care that Llama was trained on Meta’s TPUs. SOC 2 focuses on where customer data flows when it’s used, not on where the model came from.

There are real concerns about Chinese-origin models (e.g. training bias, censorship of certain outputs, license terms, etc), but those are output quality and IP questions, not SOC 2 questions. Different column on the risk matrix.

Now, Chinese-origin models could be trained to secretly inject insecure code in discrete ways. Here is where you might want to be careful and include code reviews by other models.

Concern level for compliance: ~zero.

Concern level for security: ~medium.

Layer 2: The harness

This is where most of the fear should actually be redirected.

The harness is the tool that runs the model and bridges it to your environment (Cursor, Claude Code, etc.). It’s the thing that reads your filesystem, indexes your repo, decides what to forward to the model, and (in agentic modes) potentially executes shell commands on your behalf.

For security purposes, this is your real attack surface. Things to consider

• What permissions does it have on your machine?

• Which 3rd-party MCP servers can it write to?

• How are your team members utilizing it?

• Is this an open-source harness with lots of eyeballs on it?

Given the harness is where the model connects to your machine and performs actions, this is where a permissive configuration OR usage policy can expose risk… particularly if the Chinese model has been trained to inject insecure code.

Concern level for security and compliance: high.

Layer 3: The context

Here’s the underrated one. What data is your tooling allowed to send?

If your IDE plugin sends only the file you’re editing, the risk is contained. If it sends your full repo, your .env file, and your customer data sitting in test fixtures, then that’s the leak vector, regardless of where the model runs or who trained it.

The model could be Gemma 4 hosted by your sweet old grandmother, and you’d still fail audit if you piped customer PII into it without governance.

What auditors want to see:

• Deny lists configured (.cursorignore, .aiderignore, Claude Code settings.local.json)

• Repo segmentation: customer data doesn’t live in the same repo as code your AI tools touch

• Prompt-level redaction where appropriate.

• Audit logs of what got sent.

This is the layer most people don’t think about until an auditor asks. Get it right, and a lot of the model-of-the-week anxiety goes away, because the risk is bounded by what you let leave the boundary in the first place.

Concern level for compliance: high. This is where the audit lives.

Concern level for security: high. This is why you want the right model for the right context

Layer 4: Where inference runs

Now we’re at the layer where the original fear was actually justified, but only for one specific topology.

Three sub-cases:

DeepSeek’s API hosted in China: (e.g., calling deepseek.com directly). Data leaves your boundary and lands on servers under PRC jurisdiction. Chinese data laws require companies to provide data to the government on request. For SOC 2, this is a hard problem; it’s a subprocessor disclosure issue, and most enterprise customers will reject it in their vendor questionnaires. This is what should scare you.

DeepSeek’s weights running on a Western host: AWS Bedrock, Together.ai, Fireworks, Groq, etc. Data leaves your boundary, but goes to a Western SOC 2’d vendor under their controls and DPA. Same posture as using Llama via Bedrock. The model came from China; the inference is governed by a Western provider. Tractable. Routine vendor risk management.

Local inference: the weights run on your own GPU via Ollama, vLLM, llama.cpp. Data never leaves your boundary. The model’s origin becomes irrelevant. Cleanest answer for compliance. Not always the cleanest answer for cost or capability, but compliance-wise, hard to beat.

The principle: a model’s “nationality” only matters when the model is also the host. Decouple the model from the inference provider, and the China question stops being load-bearing.

So what would I actually do?

If you asked me, here’s where I’d land:

Ideally, use non-Chinese open-weight models (Gemma, Mistril)

HOWEVER, if you must use Deepseek, then…

1. Hosting: Use it locally or on AWS Bedrock.

2. Harness: Use best-in-class harnesses like Claude Code or OpenCode

3. Context: Don’t use it everywhere. Use it strategically for certain use cases and flows.

4. Check-it: Always have another model run QA and security reviews on generated code.

The fear in the original question is real, but it’s mis-targeted. The right fear isn’t “Chinese model in IDE”. It’s “ungoverned context flow to any model, anywhere, hosted by anyone.”

Fix that, and the model-of-the-week question stops mattering. You stop relitigating compliance every time a new provider ships a frontier model. You’re not auditing geopolitics; you’re auditing your own data boundary and your vendors’ controls, which is what SOC 2 was always about.

The Reply

I already gave a long answer above. In the future, I may share a sanitized version of the response that I emailed the founder.

If this hit something for you

This is the kind of answer the Inbound section is built for… questions that come up privately, but where the answer benefits a wider room than just one DM thread. If you’ve got something on your mind, reply or send it over. I’ll sanitize and answer here if I think other people are quietly working through the same thing.

Until next question…

• Many people have mile-long TODO lists.

• This results in analysis paralysis, procrastination

• Without a plan, prioritization is difficult.

• Product manager frameworks have already solved this.

• Here’s one I use for myself and teams I coach.

Quickstart

Scoring System

Process:

1. Create a spreadsheet with each TODO item.

2. Rate each item over each dimension (go fast, don’t overthink)

3. Add up the total score.

4. Sort by highest score

5. Pick 1-2 items in the top 5 and go.

Alternative Process:

1. Send the prioritization skill to your AI chatbot.

2. Work through an existing TODO list interactively.

3. Review the ranked results.

4. Pick 1-3 items in the top 5 and go.

When Things Show Up In 3’s

A teacher of mine told me to pay special attention to things that show up in your life in 3’s.

In the last month, how to prioritize has come up 8 times with the following archetypes:

• 2 Startup founders

• 2 SMB CEOs

• 2 coaching clients

• 2 CTO colleagues

So clearly, people are struggling to figure out where to spend their time and energy.

Hell, I’ve had to re-run these exercises for myself on any given day! I have 30+ TODOs and 8-10 hours in my workday. It’s not going to all fit, so I have to be aggressive about sorting my daily targets to make sure the most important things get done.

Sounds Nice, But How?

The fix is simple, but don’t let its simplicity fool you.

Most people (including me) struggle to mentally sort all of this on the fly across multiple issues. By getting it out of your head and quantifying, you can help yourself zero in on the items with the biggest impact.

So get started by doing the following:

• Get a spreadsheet.

• Column 1: TODO label

• Column 2: What is done?

• Columns 3-7: Sorting across the following dimensions.

Effort is inverted on purpose. Cheaper is better, so 5 is cheap, and 1 is expensive. Impact, Reach, and Recurring follow intuition; the higher is better.

You’ll know two key things about scoring.

• Integers only. No 3.5s. The moment you split the difference, you’ve reintroduced the illusion of precision that the coarseness was designed to strip away. You can’t hide behind 4.3 versus 4.4. You have to decide: is this a 4 or a 5? That forced choice is the point.

• Orders of Magnitude. Points matter because they represent big jumps. For something to go from a 4 to a 5 on effort, you have to 10x the speed. For something to go from 4 to 5 on recurring, you have to 10x the frequency you benefit from it.

This makes 5 very hard, and 4s the highly desirable floor.

You can tolerate 3s, but only if the other categories are 4s and 5s.

1s and 2s should be avoided whenever possible. Or you should redefine the task to get a better score. If something of incredible value (5) takes a quarter (1), perhaps you find a way to get great impact (4) but in a week (3). A score of 7 beats a 6, so you should try to find those optimizations.

Don’t Let the Math and Numbers Scare You

This sounds like a lot of work, but it isn’t.

I’ve worked with teams of >10 people, and we’ve been able to rip through and score >20 items in less than an hour.

That’s way better than running with scissors and wasting days or weeks of time on a low-value item.

And if you want, you can use AI to do the scoring for you. Just have it interview on each item, and it’ll assess and spit out the scores.

An AI-era footnote

One axis has been quietly shifting on everyone: Effort.

What was a “1 week build” (score 3) in 2023 is often a “1 day build” (score 4) in 2026. AI tooling has compressed the Effort axis hard, and your rankings will systematically undervalue small, fast, high-leverage work until you recalibrate the legend.

The other three axes are stable. Only Effort drifts. Recalibrate quarterly.

Try It as a Claude Code Skill

I built this as an interactive Claude Code skill. It picks dimensions with you, calibrates the legend against your domain, scores each item, and produces a ranked table you can paste straight into a doc.

Install once:

/plugin marketplace add rickmanelius/skills

/plugin install save-your-startup

Then run it on whatever’s on your desk:

/sys:prioritize 8 features for our Q3 roadmap

It works equally well on startup features, AI experiments, side projects, or life decisions. Pick the hard list you’re avoiding right now and run it through.

I loved working through hard problems with ambitious founders trying to get their startups to the next level.

Unfortunately, life got busy, and I had to start turning down opportunities to join various programs. This was one of the inspirations behind writing my book, Save Your Startup. I wanted to take the best advice and war stories that I had shared over the years and turn them into actionable playbooks.

It’s been super helpful to me. I can now tell people to check out playbook X in chapter Y because it’s exactly what they need for their current problem/opportunity.

Unfortunately, that’s still a lot of work for the founder. And nothing is as powerful as a dialogue with the author.

Enter, AI Skills

I’ve now converted some of the top playbooks from Save Your Startup into Claude Code Skills (available here).

What the heck does that mean?

It means the exercises in my book are now interactive.

Before: you read the section and follow the steps.

Now: you trigger the skill and enter an interactive dialogue (powered by AI).

It’s quite profound. I’ve been using Tim Ferriss’ “Fear Setting” and Brene Brown’s “Painting Done” exercises for years, but it’s sometimes hard to do them without an external sparring partner. Now Claude adopts a clone of me (in my style, tone, etc) and coaches me through it.

This skill pack can do the same for you.

And if you’re an author with a book, you can convert it into interactive content too.

Laurel, my 5-year-old, fits this profile perfectly.

• Why do you need to hold both hands on a steering wheel?

• Why would a policeman pull you over?

• Why do adults pay taxes?

Ok ok. The last one I’m actually quite proud of... my little future libertarian!

But after a while, it’s too much. I wanted a solution that would allow her to endlessly pursue her curiosities with an endlessly patient partner.

And I had one non-negotiable: NO SCREENS.

Enter: Curiosity Claw.

I’ve been using an AI app called Monologue for some time. You hold a button, speak into it, and it transcribes from audio to text. It’s awesome.

What I wanted was something that could dialogue. Hold a button, ask the question, and have the AI respond back (with audio).

Fortunately, OpenClaw is a capable AI platform where I could create a simple prompt, and it built this for me in under 10 minutes. I was able to select a teacher’s voice and tune the answers to be age-appropriate (5-7 years old).

Laurel loved it! She submitted 5 questions in her first session and kept asking follow-up questions. Now she wants me to bring it home so she can use it in the playroom.

Work-in-progress

I may decide to spin this up into an OpenClaw skill that other parents can download, but for now, it’s a fun experiment in using AI for learning, education, and exploration.

And who knows... maybe you’ll be able to buy one on Amazon in the near future!

He would give you the right answer, but it would sting.

Kevin had no formal education (didn’t even graduate high school), yet he had a reputation for solving some of the most complex, gnarly software challenges. It was why he was always bubbling to the top of any organization he joined.

What was his secret? Many things. Tenacity. Curiosity. A willingness to ask dumb questions.

And reading.

I know you’re thinking to yourself. Reading? Isn’t that something everyone learns in elementary school?

Yes, but adults are lazy.

I’m lazy.

Hell, I used to read books from cover to cover. Now? If I see that an article has a 5-minute read time, I bookmark it rather than start it.

I’m proud of you for making it this far!

AI Amplifies The Problem.

We already live in information overload.

AI just makes it 2x to 10x worse.

Now people are generating 5,000-word essays in seconds, and readers are using AI to compress them back down to a few bullet points.

We skim just to survive.

Actual, word-by-word reading is a lost art.

And it’s more important than ever.

Kevin, Meet Steve Yegge

On the Pragmatic Engineer podcast, Steve said exactly what Kevin harped on 10 years ago.

…something that’s contentious, but it’s just the reality of the world. Most people can’t read. I’ve ruined much of my work in my life. I’ve just completely gone down the wrong path by overestimating people’s ability to read. And I think that reading is, if anything, getting harder to come by as a skill these days.
And this is the situation that we’re in right now is that Claude Code makes you read a lot. So I think we’re in a weird limbo for the rest of this year. Until the UIs arrive that are good enough for everybody who can’t read. Everybody who can’t read is going to be a severe disadvantage.”

So there you have it.

The best AI outputs come from well-crafted, accurate prompts and requests.

Unfortunately, most people in AI are trying to move so fast that they don’t even attempt to read.

They just YOLO and respond “Looks good! Do it!”

I mean, I know I have.

Slowing Down to Speed Up

The problem is obvious, but few people will actually fix it.

Therein lies the opportunity to stand out.

If you’re one of the few who actually read and think deeply about what AI outputs, you can learn, refine, and improve much faster than those who just accept and move on.

Learning to read slowly and thoroughly may be the new superpower in an era where most people can’t be bothered.

I’m going to lean into it.

• I played with Apple IIe’s in elementary school.

• I hacked my Packard Bell Pentium 60Mhz in middle school.

• I worked at a computer repairs store in high school.

• I went to MIT twice (undergrad and grad).

• I’ve been building tech startups for the past 18 years.

And yet I’ve seen and felt the pull that many others are feeling... the return to analog.

Here in Oklahoma, a few family friends have returned to the 90s. They ditched their smartphones for a single landline. They have a single, shared family computer. They’ve removed all TVs from their homes. Their lives are almost entirely screen-free, and they don’t appear to have any regrets.

I feel the pull, too.

During my work day, I’m YOLO’ing into the bleeding edge of AI, building multi-agent systems to scaffold software that would have taken me days/weeks before. It’s surreal and addicting.

After hours? I’m with my kid on a bike, cruising around the neighborhood, helping her find friends to play with outside.

My work is digital. My life is analog.

I hear rumors of people leaning hard into this concept. It’s almost like a version 2 of Amish living. But instead of living like it’s the 1700s, they want to build communities that feel like the 1970s, 80s, or 90s. A time-warp, if you will, where you can still visit the world we live in today, but your new normal is all-in on analog.

I’m going to do a little more digging and research on these topics and share if I find anything of interest. I’m intrigued, but it feels infeasible (maybe?). But part of my longing for this type of simplicity, at least after hours.

“Violent Self-discipline.”

Not a wish. Not a hope. But an unwavering attack on keeping your commitments at all costs. No excuses, and no tolerances for even one missed day.

It’s a high-bar, but it reminds me of Jack Canfield’s policy: 100% is a breeze, 99% is a bitch. The second you add even a little wiggle room, it’s a decision every time. If it’s a non-negotiable, zero mental energy is expended because the decision is already.

415 Days of Discipline

In 2024, I shared how I joined a 101 day boot camp called Heroic Elite. The premise was simple. Fill out a daily Carpe Diem page that defines everything from your big goals to your daily targets. Review your results at the middle and end of the day. Never skip a day.

At the end of 101 days, I decided… why stop? The entire point was to build momentum and the daily discipline was helping me stay accountable. So I kept going.

I’m now 415 days in.

I only missed two days. The first missed day was due to illness. The second was because I was so busy I jumped into a day of fire fighting and just never got back to it.

But I never let myself miss two in a row, and I lit a fire under my ass to make it almost impossible to miss another one.

Was I perfect in hitting my daily targets? Hell no! There were some days where work and family life was so chaotic that I only hit 1-2 out of 6-9 targets. That’s hard feedback to stare at, and it only provided more fuel to double down the next day.

To a lot of people, this level of focus seems over the top. However, I’ve had phases in my life where years blinked by without much to show for it, and that led to lots of regret.

Life is short, and I want to fit a lot of life into it. And the only way to make that happen is violent self-discipline.

• Eat nutrient-dense food

• Exercise regularly

• Get consistent sleep

• Limit junk food

It’s not rocket science (and we all know that).

And yet, people will place all kinds of unnecessary dependencies upon themselves before they get started.

• Endless research

• Obsessing about optimal plans

• Buying the right clothes and equipment

• Setting goals and affirmations

Let me be clear! These are helpful in supplementing your results, sustaining motivation, and holding yourself accountable. However, I’ll watch people spend 10-20 hours preparing, and then spend 10 minutes on a treadmill.

They know what to do, but they pretend they don’t. They pretend they need a perfect plan before taking action.

And it’s not just exercise.

The AI Learning Hampster Wheel

If you’re on LinkedIn or X, you’re probably getting buried with AI tutorials, demos, courses, and the like. The FOMO is intense, and some of the smartest people I know are crying uncle because they can’t keep up.

They are also missing the point.

AI is meant to help you get things done. It’s not meant to be an all-consuming 2nd job to keep up with.

My belief? Most people can stop trying to learn new AI tools and techniques. Why? Because they aren’t even applying what they know!

Learning as Procrastination

Look, I have a habit of overlearning.

I have a PhD I’ve never used, because I thought I needed it to be the best at my profession.

In reality, I could have joined a company and gone further faster by learning and applying on the job.

Many people fall into the learning trap. They convince themselves they need just a few more facts.

However, some of the best learning happens through direct experience and feedback. Your code isn’t working? Great! Now you have a real problem with real motivation to fix it.

Forgetting What You Used to Know.

I loved a story that Rich Schefren told on a recent webinar.

He was feeling stuck in his business and decided to look at his bookshelf for guidance. He then noticed a copy of his book he wrote 10+ years prior. When he opened up and started skimming, he realized that the answers he was looking for were right there.

He ended up pulling his book into ChatGPT, asking questions, and got exactly what he was looking for. He was astonished. The answers were already inside of him; it had just been so long that he felt like it was written by another person.

This happens to me all the time.

I’ll go back to my emails or to my blog to write about something, only to find out I already did 10-15 years ago. And after I re-read, I often gain new insights from my past self.

You Know What To Do

We live in a world of infinite intelligence. AI + the open web + your personal experience + people you know. The answers are all out there (or already inside you). You just need to ask, but you also need to get off your ass (I’m saying this for me too).

Stop pretending you have some insurmountable amount of knowledge you need to acquire. Yes, there are certain professions that require it (medical doctor). However, 90% of the time you already know enough to get started in the right direction… and you can make adjustments as you go.

I’m rooting for you.

I’m also rooting for myself.

Because I’m sure I’ll need to re-read this every so often as a reminder.

This is a shout-out to Jake. Beyond being a best friend of 44 years, he’s a perfect example of the archetype of this article. He was the guy who wouldn’t take no for an answer when trying to figure out what do on a Saturday night. Where is everyone? I don’t know… let’s find them. Let’s go cruising.

Mind you, this was in the glorious, tech-free 90s. You couldn’t cheat by checking social media or texting the group chat. Hell, even parents were clueless if you called to ask whether their kids were at.

So, how did you find friends? The old-school way. You drove around until you saw where the cars were in the driveway. And when you saw them, you didn’t chicken out and keep driving. You marched up to the door, knocked, and tried to get in on whatever was going down.

Old School Tactics for Generation Alpha

Kids these days have work harder to make friends.

Everything is a scheduled play date.

Parents move kids from house to house vs. letting them free-range.

It’s better in Oklahoma than in most areas. Parents are negligent, but they also aren’t helicoptering 24×7. The result is that there are safer neighborhoods where kids play in their yard and (gasp) sometimes go 2-5 houses down the road to play with other kids in their yards.

This is what I’m trying to instill in my youngest. She’s still too young for me to at least not be in eye sight for… reasons. However, every weekend I remind her that friends are where the bikes are.

So we go cruising around the neighborhood until we see a few bikes plopped in the front lawn, and then I encourage her to see if she can see or hear them. If we can’t, we knock on the door.

In the past 3-4 months, she’s made 3 new friends this way.

And there’s another pocket of kids across the neighborhood that she’s gaining more confidence with. You know, potential friends material.

Adulting

There are articles and studies on how it’s become more difficult for adults to make and sustain friendships. Add this AI bot apocalypse, and it’s just going to get worse.

But the strategy is the same.

Future friends are where the cars are. Where the bikes are. Where people are already gathering for an event or a recurring activity. You just gotta put down the phone, go cruising, and keep your eyes peeled.

And don’t be afraid to knock.