It’s what Copilot was supposed to be. I estimate I save an hour per day on email.

Superhuman has a few things that are fantastic.

Superhuman Split Inboxes & Auto Tagging

It separates important inboxes from newsletters I read to. If I wanted, I could create an inbox that only emails from my team go to, or just client emails.

As emails come in, they’re auto-tagged by Superhuman based on what I’ve either told it in the past or what it thinks. So far, it has gotten very little incorrect and, what it got incorrect, was placed in my “Important” inbox.

Just having my inbox not be a complete disaster is worth it enough. I check “Reading” first thing in the morning and then “Important” the rest of the day except the end of the day, when I check “Other” once.

Smart Auto-Reminders

If you send an email and the person doesn’t respond, a few days later, it’ll not only surface that email to the top of your “Important” folder, but it’ll also write the “bumping this” message. All you need to do is click “Send.”

You can also set your own reminders if you desire. I set reminders every day for things that I don’t have bandwidth for now or need to make sure I don’t forget.

Calendar Management

It intelligently manages my calendar. When I need to schedule a meeting, I click “Select Free Times and Booking Link” and it pops up my calendar. I click the times I’m open, then it also drops the booking link in there, too.

When someone proposes a meeting time, it pops up that time in a small, sidebar view of my calendar for that day and time. When I need to schedule a meeting, it saves me two or three clicks.

If someone proposes a meeting time, a little “Create Event” button pops up in the bottom corner which creates the event, adds the people on the email to it, and pops in a link.

Superhuman has tons of other fun features too, like snippets, which basically are like saved email copy for commonly-written emails and fine-tuning AI to write in your tone of voice.

It has tons of keyboard commands which can be a pain to learn but are amazing once you do.

It can handle multiple inboxes on multiple tenants easily.

It’s beautiful to look at.

It’s got a chatbot integrated right into it for Q&A across your entire inbox.

It’s got fabulous CRM integrations (that actually work) for easily keeping track of deals.

It’s got a public facing trust center so you can verify the data’s security.

People ask me all the time how to use AI with email. The answer is not to hand over your email to Claude. It’s to be in control, but spend less time on it.

I’m not affiliated with Superhuman, I just really, really like it.

If you click the link, you’ll get a free month. Allocate 1-2 hours to getting used to it and learning the commands. By the end of next week, I think you’ll love it, too.

Try Superhuman

I thought it would be a fun exercise to rank my top 25 songs from the first 5 years of the 2020s. Note: these are songs that came out in the first five years of the 2020s. In 2020, I discovered many songs from 2019, but they are not included on the list. Songs that came out in 2025 but I discovered in 2026 are also not on the list. It’s not totally fair, but I get to make the rules.

I definitely bias toward songs released while we were nomading (2022 - 2025). I think all the time on planes and on walks helped me hone my taste in music. I keep my playlists in chronological order to music discovery, and the playlists from 2020 and 2021 were all over the place.

I’m not going to try to make grandiose observations that apply to life, but I noticed two things:

1. I like songs more from periods where life was going really well vs when I was in a rough patch. Cruising around Greece or exploring Morocco or making gnocchi in Italy? Lots of great times. Business is struggling or we’re in an awful Airbnb with a bed two-sizes-too-small? Not many songs from that period.

2. Discovering Italian music really changed things. Plus, I was getting good at speaking Italian, so it was a combination of good times and good music.

My ranking system gets messy after spot 3. Definitely the top 3 are the top 3, though. The two classical songs I stuck at the bottom not because they’re the final two, but because I couldn’t compare them to anything else.

1. As It Was - Harry Styles

2. One of your Girls - Troye Sivan

3. Getting Older - Adam Lambert

4. So Long, London - Taylor Swift

5. Banish the Banshee - Isaac Dunbar

6. Save Myself - Ashe

7. Sweet Cherries - Finneas

8. Bang! - AJR

9. Cinema - Harry Styles

10. Storie Brevi - Annalisa & Tananai

11. Radiohead - Tananai

12. Medieval - Finneas

13. The Ballet Girl - Aden Foyer

14. Guarda Cosa Hai Fatto - Tananai

15. Escapism. - RAYE & 070 Shake

16. Booster - Tananai

17. I Can Do It With a Broken Heart - Taylor Swift

18. Father Figure - Taylor Swift

19. Oldies Station - Twenty One Pilots

20. Fantasmas - Humbe

21. Biale Inolvidle - Bad Bunny

22. The Diner - Billie Eilish

23. Actor - Conan Gray

24. IN A DREAM - Troye Sivan

25. La Perla - Rosalia

26. “Tuscany” Suite for Piano and Orchestra - Nicholas Brittel, Succession: Season 3

27. Succession - Andate Risoluto - Nicholas Brittel, Succession: Season 4

This is too small of a list so I allowed myself 27. Honorable mention to the songs I couldn’t add such as half the songs on Harry’s House, Olivia Rodrigo, Sabrina Carpenter, Isaac Dunbar, and KAROL G.

Then I thought of Moira, from Schitt’s Creek:

This week, Anthropic announced Project Glasswing, “a new initiative that brings together Amazon Web Services, Anthropic, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks in an effort to secure the world’s most critical software.” (emphasis mine).

The best AI use case so far is in writing code. It’s fairly simple to see why: when code is written, it either runs or it doesn’t. There’s an immediate feedback loop. So the AI writes the code, can test it, and, if it doesn’t work, can iterate all near-autonomously.

Claude Code, Anthropic’s app for using AI to write code, is the industry-standard AI coding platform.

Powering Claude Code currently is Claude 4.6 Opus, the current best-in-class AI model for writing code. It’s significantly better than any other AI model on the market.

Anthropic trained a huge new AI model called Mythos that vastly outperforms Claude 4.6 Opus in all coding benchmarks.

Mythos is amazing at coding. There are various objective benchmarks for code quality. In the past, a 2 or 3-point improvement over the current state of the art was enough to get all developers to switch over to the new model.

The current state-of-the-art coding AI model is Claude Opus 4.6. Mythos has outperformed the state of the art by 24%.

Mythos is so advanced that it found, allegedly, “thousands” of major security vulnerabilities across all major technology operating systems (think Mac, Windows, Linux) and web browsers, and core applications. These vulnerabilities are referred to as “zero-day” exploits meaning that the developers of the respective software didn’t know that the vulnerabilities existed.

Anthropic was so surprised at the results that they called industry-leaders and are creating a strike force to identify and resolve these critical technology platforms before AI models like this become widely available. They’ve made Mythos available to select enterprises, but they haven’t made it available to the public and “they may never.”

To summarize:

1. Anthropic trained the most advanced AI model in Claude Mythos.

2. Claude Mythos is 24% better than Claude Opus 4.6, the current state-of-the-art.

3. Anthropic used Claude Mythos to identify thousands of security vulnerabilities in critical software used every day.

4. Anthropic called industry leaders to create a strike force, Project Glasswing, to secure these critical pieces of software.

5. Anthropic decides to publish a huge white paper detailing Mythos, announcing the project, and proclaiming to the world that these vulnerabilities haven’t been solved yet but will.

6. Anthropic also publishes the pricing for Mythos, which is 5X higher than that of Opus 4.6

I, for one, am glad that Anthropic has created this initiative and is taking this seriously. I’m glad that investors gave them the money to do these tests. I’m glad that US administrations over the last 10-15 years have allowed the AI sector to flourish.

It’s not the actions they’re taking that I’m bothered by. It’s the fact that they published all this before fixing the critical vulnerabilities and not after.

Anthropic has a history of this type of sky-is-falling-marketing.

2 quick YouTube searches (“Dario Amodei AI jobs” and “Dario Amodei AI safety”) brought up these and way more examples. 1 ChatGPT search (“Find me videos, tweets, etc where Dario, the CEO of Anthropic, claimed that AI would destroy all jobs or generally had sky-is-falling messaging”) yielded a whopping 82 links to Anthropic’s sky-is-falling messaging (Although it should be noted that I didn’t click them all so there surely is some overlap. You get the point.).

This has been par for the course for a while now. Anthropic was a company started by Open AI employees over fundamental disagreements of how AI should be handled. For example, the Anthropic founding team were at Open AI when they said GPT-2 was too dangerous to be released.

I think it’s incredibly hard to separate the reality (mission-critical technologies should be secured before western adversaries have access to AI models like this) and the marketing.

Am I supposed to thank Anthropic for being team-good-guys? Am I supposed to fear this AI falling into the hands of team-bad-guys? Or is this a really great test of wayyyy higher AI pricing?

And while everyone in Silicon Valley are losing their minds about the implications of Mythos, is it really just because 1 engineer + Claude Code, if Mythos is ever released, may replace 7 or 8 or 9 engineers out of 10?

I’ve stated in the past that I think the best industry to be in is AI and the second best is cybersecurity. That is seemingly more true than ever. But if AI can find the vulnerabilities, and there’s an expectation that it can help in fixing them, and it’s “dangerous” to release it to the public (according to Anthropic), then why publish this white paper before fixing them instead of after?

Much will be made about Mythos in the coming weeks. I hope it’s used to patch the vulnerabilities. It’s unquestionable that the United States will be stronger with 3 or 4 AI models this advanced, all owned by different countries.

But if it’s so dangerous, why make it a marketing campaign?

In 2017, a year earlier, I had tried out a demo for a company called Dreamscape. It was Hollywood-meets-tech. The product was a VR experience unlike any that anyone had ever created. Participants wore an Oculus with a backpack, then they were transported into alternate worlds. An Indiana Jones-style world had me genuinely afraid that I was going to fall off a rock into a black void. When I was throwing a torch, which was a plastic bat retrofitted with tons of sensors, I forgot that I was wearing VR goggles but throwing a real-life object. It was so high-fidelity and spatially accurate that it didn’t matter if I was in a conference room with beige walls or in virtual northern Norway. It was electric.

After the presentation, I bought an HTC Vive for $350 and brought it back home with me where I used it once or twice an then threw it away only after letting it take up valuable closet space in my apartment, moving it out of the apartment, and letting it sit in storage for two years as I nomaded.

I first heard the phrase “Try, Oh My, Goodbye” on the All-In podcast in reference to the same VR experience I had several years prior.

Dreamscape popped up in malls and movie theaters for several years after before shutting down most of their operations. I went once. I remember it being fantastic, but, instead of going back, I always had something better to do.

The parallels between the “Try, Oh My, Goodbye” VR experience and OpenClaw are close. OpenClaw is an open-source software where you plug in a Large Language Model (LLM) like Claude or ChatGPT, and then it can control your computer and do things on your behalf by controlling your screen. Let’s ignore the security risks and mistakes it makes, it took the world by storm a few weeks ago getting millions of downloads and being featured in Wired, Business Insider, and Financial Times.

AI browsers have been around for 6 or 8 months. I first tried one in September of last year. I tried to make one my daily driver in November then gave up on it last month. The problem with the agentic browsers is the same as the problem with OpenClaw: the AI only works sometimes, and its success is largely reliant upon your knowing exactly what you want it to do and taking the time to properly communicate that.

Agentic browsers have a few (solvable) hiccups, but I think of solving the hiccups as winning battles, not as winning the war.

Productivity tools don’t seem to work well

Excel doesn’t work well with AI browsers. They can’t control the cells well. The same is true with Asana. It can’t quite fill out the fields and control Asana the way it needs to. With Excel, it usually outright rejected to work with it. With Asana, I usually needed to fix its mistakes or half-finished work. In fact, I can’t think of a time when the AI browser did the job for me half as fast or even as half well as I would’ve done it.

The second block of issues are solvable, but they severely limit adoption. First is timing and bandwidth. That’s the nice way of saying that the AI browsers are slow and lazy.

AI Browser Agents are Slow and Lazy

We have some pre-release software for which we needed documentation. I recorded a 15 minute video explaining how the software works and how to do everything that the users would need to do, and I gave that transcript to an AI to turn into a user manual. Separately, I set up the AI browser agent to click around and create the SOP. I gave it the same transcript to use as inspiration.

When the agent came back to me, I had about 100 words and 3 or 4 processes outlined. When the normal ChatGPT came back to me, I had 23 pages.

This is true, too, with finding flights. Use an AI browser to find flights and it’s a 5 or 10 minute process as it fumbles through clicking around. Use Gemini and the same task takes about 15 seconds.

I don’t usually know what I want

Combine the slow, lazy browser agents with the fact that it usually takes me two or three tries to fully know what I want and that’s a recipe for irritation. Most times I want to do something, I have to try it at least once more before I get frustrated and give up. This isn’t an issue when using the standard chat interface because it’s fast for me to speak or type, but I’m driven crazy when I need to watch the browser think for 5 seconds before it clicks “submit.”

I want to be clear. Most of my grievances can be solved through innovation and the typical product development lifecycle. Excel can work faster and Asana can work better inside of them. Clicking a button on the screen (and understanding how the screen is laid out) can be done faster. But that doesn’t change that I think it’s a battle.

The war is that the AI’s work should be mostly invisible

What makes the standard chat interface so compelling is that the user uses their natural language, the prompt goes to a server, the server does its thinking, research, or actions, and then, magically, it pops out the answer or solution. APIs have been doing tasks for us for over a decade now. A chat interface that does work by using the APIs is vastly more efficient and more “magical” than watching the AI agent struggle to identify the text field to submit.

If browsers already are the operating systems for the lion’s share of our work, then OpenClaw faces the same issues. It’s using AI to work on an operating system.

I think the solution could be compelling, but I think agentic browsers and OpenClaw are a local maxima, not a global maxima. At best, they’re a niche tool for hobbyists who want to tinker.

In Henry Ford’s day, what people thought they wanted was “a faster horse.” Ultimately, the most compelling vision of the AI future probably isn’t an AI that manipulates the interfaces you’re currently using, it’s an AI that does all the work in the background and gives you the answer or does the task in seconds. That latter technology sounds an awful lot more like a car than a faster horse.

Now that we’re about a month into “normal” life after nearly four years of nomading, I’ve made a few observations. For most people, all this is old news, but Miranda and I have not been really living in America. We’ve stopped by and been in the States off-and-on, but we’ve not had our own place. Since we spent most of the last four years in Europe, I feel like I’m experiencing a wave of novelty all at once.

Below are a non-comprehensive list of things I’ve learned since I stopped being a digital nomad:

• Part of the Boho design style is random rope dangly things, and I don’t like the dangles very much.

• What Japanese Joinery is

• That beautiful antique pitcher you want to buy probably contains lead paint.

• To get Fiber internet, they drill a hole from the outside of your house to connect the cable.

• When they bury the fiber internet cable, if they need to bury it underneath your driveway, they essentially snake the cable under the driveway.

• Below-freezing temperatures are a real problem in Florida because the pipes aren’t insulated.

• A Tesla supercharger takes 25 minutes to charge the car from near-zero to 80% but the AC and car still run so it’s comfortable.

• Tesla self-driving can do u-turns

• Florida drivers are awful, and Florida motorcyclists have a death wish

• Car insurance in Florida is outrageously expensive

• The telephone area code around Cape Canaveral is “321” because of “3-2-1 blastoff”

• 2700 lumens = warm light which is pleasant.

• Costco only accepts debit cards and Visa

• TJ Maxx is a great spot to buy random kitchen stuff like wooden spoons and can openers and peelers.

• Amazon is not a great deal for kitchen stuff because they need to make the numbers work, so they bundle a bunch of stuff you don’t need (15 cooking spoons when you need 3) to get you to spend $15 when you’d spend $5 at TJ Maxx.

• Facebook Marketplace has the best and worst deals. The best deals are the ones I described above. The worst deals are when someone buys something on Amazon and is reselling it for $10 less than what they bought it for.

• Kohl’s has stopped doing Amazon returns for the most part

• Not all stainless steel pans are equivalent. 5-Ply and 3-Ply are good, will be more nonstick, and will distribute heat more consistently.

• How to season a cast iron skillet

• A lamp shade costs $50

• To make a linen duvet cover not wrinkly, pull it out of the dryer just before it’s totally dry and shake it out.

• Most rugs are polyester, and most cheap rugs are polyester plus screen printed. The price difference between wool and polyester is enormous

• If you go to a gym with a bunch of old people then the middle of the workday is as crowded as any other time.

There are a few things that I think are worth more explanation.

North America is so convenient

Amazon same-day and overnight delivery are incredible. At 10:30 at night, I needed a new toothbrush. By 11:00 AM the next morning, I had an electric toothbrush and a Water Pik delivered to me. In Europe, that’s a 90-minute activity. Find the store that carries it, walk to the store (if you’re in Italy or Spain, there’s a 50% chance the store is closed because the owner didn’t want to work that day), find the items, check out, and walk back.

Costco is incredible. The quality is high. It’s all right there for you. You can buy essentially everything you need for your entire life right at a Costco.

Instacart is nice, but we don’t use it, and Europe has its equivalents in Glovo and Deliveroo. That has been the only thing that is not meaningfully more convenient.

We ordered our guest bedroom mattress from Costco. It had springs and coils, and somehow it was shrink-wrapped down into a rectangular box about 3 feet tall and 8 inches wide. When the two delivery guys came to set it up, the total time it took them to walk in the door, open the box, set up the mattress, take a picture of their work, pick up their trash, ask for us to leave a 5-star review, and leave was 4.5 minutes. That service and efficiency is not found everywhere.

Our Major Life Change is Everyone Else’s Normal Life

For us, settling down and building a home is a life change as big as graduating college and entering the workforce. I think it feels like a bigger life change than starting to travel because, with traveling, we sold all our stuff and set off with no expectations. We could stop whenever we wanted. With building a home, we’re acquiring stuff and settling down. With acquiring stuff, we are building attachments. Miranda loves her new, Persian rug for example. I love my new stainless steel pans. We both love our Boll & Branch sheets. As we get more comfortable and develop our own routines, changing the routine will get harder. In fact, the first diary entry I wrote the morning after we moved in was a how-to guide for the nuts and bolts and logistics of how we traveled.

But, while, for us this is a major shift, for everyone else it’s “welcome to the club.” I’m more exhausted now than I was at the end of our traveling. It would’ve been easier to fly to Mexico City (which we’ve lived in for 10 weeks), checked into an Airbnb, connected to the WiFi, and called it a day. Our travel systems were finely-honed.

In this case, we need to build all-new systems. Where we put plates and cups. Signing up for internet and utilities. Determining when we go to the gym.

Signing on and off from work is a huge one. The only time we traveled in Eastern Time was in Colombia. In Mexico City and Costa Rica, we were two hours behind. In Argentina and Chile we were two hours ahead. In Europe and Africa we were +5 - +7 and in Asia we were +12 - +14. When North America is signed off (or asleep), it’s easy to either get focus work down or be signed off. When North America is signed on for your entire work day, it’s much harder to get work done. There are constant distractions. Focus-work gets pushed, and then I am unsure when to stop for the night.

All this and, since we also moved to a new city in a new state, we have all the same work we had when we landed in a new city. Finding restaurants, finding the grocery stores, figuring out how to get places, signing up for a gym.

None of these are unsolvable problems, but they’re problems that need solved, and we’re solving them all at once. It’s exhausting.

We have to buy everything

During our travels, we said that “all we own is what’s in our suitcases, backpacks, and our companies.” We joked, but it’s true.

In our life before travel, Miranda and I were the roommates that didn’t buy much. My roommate’s family had a bunch of extra furniture, and Miranda’s roommates came with lots of stuff. So we lived that part of our life without much. I should be clear, we didn’t contribute nothing, but we didn’t leave our leases with an apartment’s worth of stuff, either. Plus, four years went by since we lived in apartments, so we either outgrew what remained, sold, or donated it before we traveled.

We have had to buy everything. Silverware, dinnerware, pots and pans, a mattress, a bed, sheets, towels, a kettle, a toaster, rugs, a couch, a kitchen table and chairs, a guest bed, guest sheets, guest pillows, a TV, desks, office chairs, curtains, glasses, a car, lightbulbs, lamps, side tables, nightstands, wooden spoons, a paper towel holder, a can opener. Everything.

The sheer quantity of things we have to buy is exhausting. It started out as fun, but now it’s a chore. Starting from zero is no fun. This year will be one of the most expensive years of our lives because of it.

Facebook Marketplace is the current great wealth transfer

The great wealth transfer isn’t in real estate or in stocks, it’s in Facebook Marketplace. Find areas where the greatest service you do to the seller isn’t money, but it’s a takeaway service, and you’re getting the deal of the century.

In Columbus, a family in one of the wealthiest neighborhoods was selling a two-year-old Italian leather couch in excellent condition for $500. It’s easily a $2,500 couch. When we arrived, the couple asked if we wanted a free 8’x10’ rug along with it. Then, they said “we actually redecorated our entire house and have a bunch of stuff in the basement. Want to take a look?” Obviously, we said yes.

The next day, we bought a 9’x12’ handmade, wool, Persian rug for $850 from a different couple that just wanted it gone. It’s like a $3,500 or $4,000 rug. It’s stunning. When we got to Winter Park, we picked up a large mahogany table with six chairs for $250 from a woman who’s an interior designer but redecorated. It’s a $1,000 table. Those are the three biggest-ticket items, but we’ve bought way more on Facebook Marketplace that are a similar stories. A handmade, Mexican jar. A handmade, Indian side table. The best deal on the market right now is whatever’s on Facebook Marketplace in the wealthy area of town.

TVs have become incredible

My standards are low because I’ve spent four years watching TV on an iPad, but TV technology is incredible nowadays. From Costco, we bought a 65” Samsung 4K QLED for $500. The first show we watched was Pluribus. I can’t stop talking about how amazing the colors are. It’s so crisp. Next we started The White Lotus. Again, the colors of the jungle are unbelievable. I can’t believe $500 buys that.

Consistency will be nice once I can enjoy it

As far as I can remember, it’s been since December, 2024 (we were in Cape Town) since I slept three weeks in a row in the same bed. I’m not traveling until I hit 7 weeks, which is the longest I’ll have slept in the same bed since the COVID lock down. In our four years traveling, we went to 35 unique countries but had 122 unique stops not including time spent back in the US with family. We stopped traveling not because we got bored, but because we got tired.

Right now, we’ve got a ton of stuff going on and are, seemingly, in constant motion, so I haven’t settled yet, but sometime I will, and it’ll be nice. I’m both excited for it and concerned. I’m excited because I’m hoping to be more recharged and rejuvenated. If I wasn’t looking for that, I’d still be traveling. I’m nervous, though, because we went so hard for so long that I’m afraid the chickens will come home to roost and I will fall off an energetic cliff. We will see.

It’s nice to have the same kitchen and the same gym. Not needing to re-discover that baking sheets are nowhere to be found is pleasant. We also have pots and pans that are nice and easy to use. Another plus.

Place is vital

We moved to Winter Park, Florida, which is like if the walkability, live oaks, and brick streets of Savannah, Georgia had a baby with the homes and neighborhood of Beverly Hills. We love it here so far. Everyone’s nice, it’s beautiful, the food is incredible, it’s super walkable, we’re pretty close to family, and there’s an intercontinental airport nearby. There’s even train transit. It feels like an American extension of our favorite cities from when we were nomading. Had we moved to Strip Mall USA, we’d be miserable. Having the right off-ramp to combine all the things we loved about being nomads with building a more stable life in the US was paramount. While I’m exhausted now, I’d rather be exhausted and happy about where I live than exhausted and depressed.

The future is here, but it’s unevenly distributed

A 3-year old, used Tesla Model Y with 30,000 miles on it is the best deal on the market. It costs $29,000-$32,000, has a 280-mile range, and, if you pay $99/month, drives itself. For less than the price of a new Toyota SUV, I can get a self-driving car. The self-driving works better than I anticipated. I would say it’s a better driver than I am 90% of the time (and I think I’m a pretty good driver) and, when it does something weird, it errs on the side of caution (driving too slow, stopping too long) than havoc. Around Winter Park, there are tons of Teslas driving by.

Someone who lives nearby has a Tesla solar roof. I didn’t notice it before (besides that it looked like a nice roof), but when I walked by it at night, I saw the green lights of a PowerWall, the battery units that store the energy. That home is probably fully-off-grid.

Waymo and Cybercab are coming to central Florida in 2026. Combined with light rail (the central Florida railway system) and Brightline from Orlando all the way to Miami, we have an abundance of options for transit.

But it’s not just that. 500 mbps fiber internet costs $55/month. A smart doorbell with facial recognition AI that backs up securely to iCloud costs $65. My gym has a (somewhat accurate) body composition scanner sitting next to the check-in desk they encourage your using.

We’re an hour’s drive away from watching the Artemis II launch and future Starship launches.

I know I sound like I’m singing Winter Park’s praises (I am), but there’s something nice about walking down beautiful, brick-lined streets to dinner while having a self-driving car drive me to the beach.

For me, a daily challenge is determining “what is the best thing for me to work on this week?”

A mental model I’ve created to help is to answer the question “Would I still be doing this if we had triple the customers we do now?”

In a hyper-growth stage, systems break down extraordinarily fast.((not tech systems – business systems))

Rickety technology needs better infrastructure. Systems and processes need documented with explicit areas for flexibility for when particular milestones are achieved.

Take “this task.” “This task” is the task in front of me that I could do or could delegate (to a human or an AI). 

Keep in mind: delegation requires finding and paying someone to do it and managing it, which often I feel too lazy (or cheap) to do, so it often “feels easier” to just do the task.

My decision-making criteria is the following:

“Would I still be doing this task if we had triple the customers we do now?”

For the present – achieving triple the customers

• Can I help my team remove blockers? That’s always thing #1. It helps the organization move faster in the present.

• If “this task” helps us achieve triple the customers (and I play a role), I focus on it.

For the future – we’ve achieved triple the customers

• If I wouldn’t have time for “this task,” I start building a system to support triple the customers now.

• If I would be doing “this task” with triple the customers, I do the task.

As I’ve been thinking about it, I think the biggest trap to avoid is the “it’s fun” trap.  The “it’s fun” trap is when a task is fun to do, but you wouldn’t have time for it if you had triple the customers you do now.

“It’s fun” is actually a form of procrastination.  It should be avoided. Just rip the bandaid off. If I really loved it, I would feel like it’s more important with triple the customers.  Instead, it’s just helping me avoid something else.  

“I’m willing to sleep on the ground, I’m willing to be hungry, and I’m willing to be cold, but I only do one at a time.”

This struck me as super, super wise.

Since AI is the hot thing, I get approached several times per month with the idea of a collaboration.  Each idea is essentially the same.

Someone who works in a non-tech industry knows about a process / task in their industry that sucks.  

Then, they ask us “Can we automate it?”

After a review, usually the answer is “Yes.”

And then they say “You know, everyone else in our industry has this same problem.  Could we sell the solution to everyone else in my industry?”

** usually ** “Yes.”

Then, they add something like “Instead of your being a vendor, you become a collaborator with us, so we split the investment but then we share the upside.”

Before recently, I didn’t have a good way of filtering out ideas or knowing which collaborations to pursue and which to not purse outside of a gut reaction.  But, recently, the number of requests has increased sizably, so I needed a way to objectively determine which ideas to take on and which to drop.

Which took me back to Outdoor Boys.

Below is an email I recently sent which outlines Teammate AI’s approach to collaborations from here forward.

The email has been slightly modified for clarity.

I’m totally cool with exploring the collaborations further, but I’m instituting a few requirements for Teammate AI.

1. We will only be in pre-release, active development with one at a time.  I love collaborations, but too many at a time and none will work.
   

2. We start by building a scaled-down version of the solution first where Teammate AI serves as a vendor.  I am totally with you on the idea that collaborators are better than vendors (I agree!), but the version-1 solution needs to be a solution developed as a vendor. The reasoning for this is simple: it focuses us on solving the problem and making a difference for customer #1 (our client).  After that, we can scale it up to work with more than 1 client and, ultimately, generate revenue.
   

3. The total market size for Year 1 revenue is > $1MM / $83k/mo.  It doesn’t mean that we hit it, but it means we know enough people facing the same problem to be able to achieve that metric.  This does, admittedly, slow us down a bit because it means we need to have a financial model in place before starting, but I think it’s worthwhile to keep the process a bit slower up front so that we don’t waste 3-6 months getting a bunch of stuff together before realizing it’s not viable.

As I discuss in How Do You Win with AI?, the first half of the flywheel is using AI to free up your people. The second half of the flywheel are the steps for achieving exponential benefits and differentiation in the marketplace.

At some point, all companies will be on this flywheel, and the differentiation will be commoditized.  Using AI will be table-stakes to compete, just as using the internet is now.

In the internet age, the first companies that could profitably sell their products or services on the internet created exponential differentiation in the marketplace. Then, everyone developed websites.  

It’s similar with mobile websites as smartphones proliferated. The first companies to have mobile-native experiences drew massive benefits in the marketplace.  Then, building mobile sites became table stakes.

In the past, as the tech, and the transformation that followed, became table-stakes, there were technology platforms that effectively demonetized the transformation.

Instead of coding your own website from scratch and buying servers, you could use site templates Wix or WordPress with your own copy and spin up a website in an hour or two. And, it would automatically generate the mobile versions of the sites to boot.  Instead of spending $10,000 on a website, a company could spin one up for $300 per year.

So why invest in AI when it’s early and expensive?

Because by the time it’s table stakes, there will be less and less differentiation.  All the value is in getting the early lead.  The early lead is what customers remember. It’s what builds brand equity.  It’s what creates true differentiation.

When everyone else is playing catch-up to you, you’re focused on value-creation for the customer.  It’s a completely different mindset.  One company is saying “What can I do to not be left behind?”  

The other company is saying “How can I drive even more value for you?”

The difference is where the content originates

When the AI creates the content, the AI is the content creator. It’s making sense of the ideas and nuance.

When the human creates the content and the AI repackages the content, it’s taking your original thoughts and ideas and it’s making the content fit your desired delivery method.

I’ve not met many businesses that love their content marketing spend. Most that I know what to reduce it as much as possible.

I think it’s a worthwhile effort.

But it’s important to know where to reduce that spend.

If you reduce the spend on the creation side, you’ll end up as just another company using AI for marketing.

If you reduce spend on the packaging side, you’ll have better ideas than your competition in more places than your competition.

Which brings me to my most important point.

The purpose of any content creation budget is to create an inventory of content for your customers and prospects to consume.  

AI can take the cost of creating that inventory to zero.  Combined with the fact that it’s virtually free to host the content on the internet, the cost to create and the cost to store this inventory is effectively zero.

For you and for everyone.

In a world where inventory creation and storage costs are zero, it’s no longer inventory that’s scarce.  Inventory is abundant.

It’s creativity.

Imagine you’re running a sales organization, and you want to sell more, but you don’t want to hire more people, so you hire an AI cold calling service.  Hypothetically (definitely – I’ve heard the numbers.) that service costs $25,000 per month, and it’ll double your cold calling output.   The AI even sounds just like a human with perfectly timed “ums” and “uhs” and small chuckles.

Cha Ching! You’re in! 

Now imagine you’re a senior leader receiving this call. You pick up, have a nice conversation, advance through the funnel and you sign up for a product or service only to find out later that the first call you received was a robocall where the AI wasn’t disclosed.  What’s the foundation of your relationship?  Some percentage of those companies will discontinue their contracts, and other portions will most certainly need to hire more humans to build relationships and repair any mistrust.

Now imagine you’re the human sales rep for the AI sales agent companies (at some point, for a service that high-ticket and most certainly requires advanced setup, a human is needed).  You need to hit quota quarter after quarter, so you need to both upsell existing clients on more calls and get new clients to buy your service. Over time, the space gets commodified and instead of charging $25,000 per month you charge $5,000 per month, so 10X or 100x the number of businesses can use your software.  

The total number of calls made per day increases quadratically, because every business exponentially grows their AI calling sales force and the number of businesses using this technology expands exponentially.

Now imagine you’re literally anyone on planet earth, now getting bombarded by cold calls all day by AI sales agents.  What will you do? Simply not answer your phone anymore if it’s an unknown number.

This is the exact reason why AI sales call companies won’t work at the scale they’re being promised. They rely on you, the prospect, answering the phone, which you won’t do as soon as more than like 1000 companies are using this software and your phone never stops ringing.

Calls are way more invasive than emails and banner ads.  They take up your entire phone screen and incessantly buzz your smart watch, and then the caller leaves a voice message or, worse, boldly calls again.

I get the AI-agent cold emailing strategy. I actually think that’s worthwhile, because email inboxes already have spam filters to filter out all the emails it thinks you don’t want to see.  The way they work is you have AI agents that find and qualify prospects, and then the send the prospect a cold email tailored to that prospect’s background and company.  Smart! This is a less robotic process than most humans SDRs do, at least from my experience.

But phone lines don’t filter out spam as well. Or, maybe mine doesn’t, considering I get like 10 spam calls per day.

I think AI agent inbound customer service reps will be huge.  That’ll bring 10X productivity for businesses and it’ll bring a 10X better customer experience. Everyone wins! Apple already does this, and the one time I called them and was greeted by the AI, it was delightful.

That said, on the sales side, my hunch is that people will answer their phones even less than they did before.   

Before Apple released the “Silence unknown callers” feature, I paid for a service called Robokiller which identified spam calls and would answer the call on my phone using a bot specifically programmed to waste the time of the spammer calling me.  Usually, the conversations, which were recorded and I could listen to afterward, would be 3 or 4 minutes. It made me feel good to know that I was playing a small role in saving someone else from having their time wasted.

So my guess is the final step in this saga for AI sales cold calling agents is that our AI spam-blocking-time-waster apps will talk to the AI sales agents and NVIDIA, AWS, Azure, and GCP will get way richer than they already are thanks to insane compute usage those services require.

Thanks to Miranda Wagner for reading a draft of this essay.

Feature Image Credit: ChatGPT 4 with the following prompt: An image of a computer making a sales call on the telephone.

Obviously, a TikTok ban would benefit Meta.  It would increase time on app increasing the ad placement inventory, especially in Reels, increasing lock-in.  That said, there will also be new entrants to the short-form content space, and I think lock in is much more difficult when operating on an interest-graph (you see more content that you like) than a network-graph (you see content from your network).   Other companies can build interest graphs too, get creators on the platform and then spin up ad networks.  This business strategy is obviously oversimplified, but it’s much more difficult for you to convince all your friends and family to switch from the Facebook family of apps to a completely new family of apps.

That said, a ban is not really in Meta’s control, and so I don’t think it’s worth spending much time on. 

The B2C Bull Case – AI drives higher engagement on more modalities

This is a two-stakeholder case.  Stakeholder 1 is for Meta and Stakeholder 2 is for creators.

For Meta, better AI drives deeper engagement on things you care about.  A better Reels algorithm keeps you on Reels longer. A better Instagram algorithm keeps you on Instagram longer.  Also, a better Meta AI assistant that leverages more and more of your data is more useful to you.  A WhatsApp bot that you use as a conversation partner, a thinking partner, or travel agent, or a smart assistant like Alexa is a very useful tool.  “Deep engagement” doesn’t necessarily mean increasing the total-time-spent in the family of apps.  It also means the quality of that time, or, better yet, time-not-regretted-using-Meta’s-services.  AI like LLaMa driving higher-value engagement in the apps leads to your turning to Meta more and more and more.  It’s similar to Prime driving higher-value delivery predictability drove customers to turn to Amazon more and more and more.

For creators, AI tools to create content faster and cheaper will transform Meta’s recommendation algorithms.  Right now, after about an hour on Reels, the content quality falls off a cliff. The limiting factor for Meta’s recommendation algorithms isn’t quantity content, it’s quality content.  These AI tools, especially in multi-modality like LLaMa 3, will drive way higher quality content and, more importantly, raise the benchmark for “average.”

Especially in short-form content, B-roll is valuable.  More than half the time, a Reel is some audio with some text placed on top of B-roll, and that’s okay for many circumstances.  Grade-A storytelling also deserves a place on the Meta platform, as they previously attempted with IGTV (which they then rolled into Instagram), but that’s fundamentally not Reels.  Reels is fundamentally a quick hit. It’s not storytelling; it’s more like improv. 

The other element for Reels creators where generative AI will crush it is in editing.  AI that can intelligently edit the Reel will drastically increase the number of Reels posted to the platform because the barriers will entry will be reduced to near-zero. 

With each improvement, Meta will keep users on the platforms longer, which will increase ad inventory.  Which brings me to the next point: filling that inventory with ads.

Case 2: Incremental Increases Drive New Ad Spend

Imagine you, overnight, doubled your operational capacity and it was completely free.  What’s the next thing you’d do?

You’d spend more on marketing and sales to drive new customers.

Enter: open-source LLaMa.

Meta has every incentive in the world to open source their large language model, just as they did when they open sourced React.

React is a development framework that allows teams to build desktop and mobile web applications as well as cross-platform native mobile applications.  Essentially, one code base can power desktop web, desktop mobile, native iOS, and native Android.

Naturally, the Facebook apps are built on React, but, now, much of the internet is as well.  We build most of our applications on React.  One Click RFP is built with React.  It’s the fastest, easiest, and most scalable way to build an application.

What’s Meta’s incentive to open-source React? 

The easier and cheaper it is to spin up a new software company, then, naturally, the more money will be spent on marketing that company.  Imagine I raise $1,000,000 to build a tech company. If I spend $500,000 to build an app, I have a way smaller marketing budget than if I spend $100,000 to build an app.

Making LLaMa open-source is the exact same thing, except with AI agents. 

All indications are pointing to AI agents, powered by large language models like LLaMa, automating or augmenting many tasks for companies in the not-so-distant future.  If there are no good open-source LLMs to build on top of, then companies must use closed-source LLMs, which will be 10X – 100X more expensive over time.  Instead, if Meta can democratize the LLM technology, then they make the tech table-stakes in your business.

AI agents will probably double many company’s operational capacities, and it’ll have the biggest impact on small businesses which are resource-constrained.  Making the technology free-to-use and free-to-modify is a rising tide, except that, crucially, Meta will see a large percentage of the gains in ads.

Case 3: Open Source LLaMa drives free R&D

By making the best models open-source, the developer community, for free, will tinker with it and will publish their findings. That’s how open source works.

This is the crucial feedback loop for Meta.  They do the heavy lifting. They buy the GPUs. They take the technology from 0 to 1, but they are allowing the developer community to take it from 1 to infinity, but, since it’s theirs, they can use all those gains.

In short, cases 1 and 2 continue to grow thanks to case 3, and, with their scale, their ROI will be measured in tens or hundreds of billions.

Feature image credit: ChatGPT, with the following prompt: “An image representing Meta, the company. The company is on an upward trajectory. The style is friendly and approachable and in one that wins hearts and minds.“

“Where is Apple?” Twitter was asking.  

Open AI is publishing models. Amazon has models. Facebook has models.  Microsoft has models. Google has models.  Where are Apple’s models?

Then, now two months since Vision Pro came out, people are saying they are not using the devices as frequently as they expected.  Uh oh! Vision Pro isn’t the next iPhone! 

Has Apple lost it?

Tech twitter can sort of turn themselves upside down at times.  I don’t own any Apple stock, but I think there are a few reasons to be bullish on Apple.

Reason 1: LLMs

I’ll sing this from the rooftops: Large Language Models ((LLMs) are not competitive advantages. They’re table stakes, and they’ll be open source.((Every business will have their own and it won’t cost a fortune to train.))

The competitive advantage in an LLM is and will be the data that goes into them.  

I do not understand why startups are raising $100M+ to buy GPUs to train LLMs. They’re all being trained on the same data! 

People go to the Common Crawl, download all the data (it’s free and open source), and then they use that to train the LLM.  

Right now, LLMs are scaling based off adding parameters to the model and throwing more hardware at it, but the tech will get more and more refined over the next few years, and we’ll reach the upper limit of what the LLMs can do.  

Then, that tech will be open sourced (probably by Meta).  That’ll be table stakes.

Then, the challenge in LLM output performance will be the proprietary data that you can put through it.

For Apple, it doesn’t serve a single business purpose to begin competing with Open AI and or Amazon or Meta in the large-scale LLM space. They don’t currently have a cloud offering, they don’t really depend much on ads (their ad algorithm in the App Store is rudimentary at best), and they don’t seem committed to building out a developer cloud (although I think it would be great for their stock price).  So why spend the money? Why spend the energy?

Where LLMs will become very useful for Apple will be within Siri and turning Siri into an agent.

Imagine: Apple has access to your email and reads that you are going on a business trip to Nashville in a few weeks.  It knows you usually fly Southwest to Nashville and that you like to stay at the Marriott downtown.  It asks if you want some travel plans prepared.  It finds the hotel in the Marriott app and flights in the Southwest app, of course, corresponding with your calendar.  It pre-orders an Uber to the airport leaving you the desired amount of time at the airport before your flight.  All you do is press “book.”

Developers are building prototype agents for this type of thing now using large language models.  Of course, they’re just prototypes, and making them work would require your giving up all your life’s data, so you probably won’t use just any random company’s service. 

But you might use Apple’s.

Apple wants all this to take place on-device((they’ll market it as private and secure)), which means that they need to make the LLMs small enough and energy-efficient enough that, instead of running on an NVIDIA GPU in the cloud, they run on an iPhone in your pocket. 

Apple’s strategy isn’t to train large models to run on huge GPUs in the cloud.  They need to compress models to run on-device.

These types of updates don’t magically appear. They’re incremental.  Incremental hardware upgrades that will drive new software capabilities.

Did you catch that?

To get incredible advancements like the above, they need hardware upgrades.

My expectation here is that Apple isn’t behind at all.  Quite the opposite: they’re solving their actual problem. 

How to convince people that used to be on 2-year upgrade cycles and are now on 4-year upgrade cycles to go back to 2-year cycles.

For Apple, AI is software that drives consumer purchases and compressed upgrade timelines of hardware. The iPhone isn’t going anywhere.  In fact, I’d argue I’m more bullish about it now than I was 3 years ago.

Which brings us to their new product, Vision Pro.

Reason 2: Vision Pro

Tech twitter wants to think that the Vision Pro hasn’t taken off like the iPhone, and is not on a path to, therefore it’ll be DOA.  This assumes that Vision Pro is the “next iPhone,” which it’s not.  Vision Pro, in its current state, might become the next Mac, but right now it’s being billed as a Mac addition.

People seem to forget that the iPhone wasn’t huge until the 4th gen.  Gen 1 iPhone was slow, only worked on AT&T, and didn’t have an App Store.  It was, however, still better than most phones on the market, albeit radically different.

The other advantage the iPhone had was that everyone already had a cell phone and had gotten used to using it. The iPhone was a huge leap forward in tech that already existed, so it’s easy to get people to switch.

Vision Pro isn’t that.  Nobody outside of gaming is seriously using VR or AR technology.  Outside of Meta’s products, I can’t think of any that have come close to being commercial successes.  Jason Calicanis, an angel investor in Silicon Valley, refers to VR as being “Try, ‘Oh My!’, Goodbye.”  Meaning you try it, are shocked by how cool it is, then put it down and never pick it up again.

This happened to me, too. I had an HTC VR setup which I loved for about 7 days. Then, I put it in my closet and threw it away 3 years later.

Vision Pro as a Mac addition, however, is a different value proposition.  It’s a B2B device.  Tech hobbyists may have purchased it, but its initial use cases are for businesses.

An elevator technician can do training and collaborate with folks at the home office using Vision Pro. A plumber can do the same. 

An expert in London can help troubleshoot a real-world problem in Bali thanks to Vision Pro. 

Recently, a surgeon successfully completed the first surgery done fully within Vision Pro.

An executive can use Vision Pro on an airplane to review company financials without anyone peering over their shoulder.

That use case is enough for right now! That’s all that’s needed. It doesn’t need gaming (which I heard is great) or sports (which is super promising) or movies (which I heard is fantastic), it just needs businesses.

Maybe, someday, Vision Pro will become Vision and will be a B2C device, but, right now, all it needs are enough businesses to buy it to continue to further fund hardware development.  Mac started as a business device, and it still is.  Over time, however, people bought Macs for personal use.  

The other aspect to Vision Pro being different than the iPhone is that it’s being geared toward developers first and consumers second, similar to the Mac. The Mac was a platform meant for pro users and dev users to build on top of first, then for consumers to leverage second. The iPhone, however, shipped locked-down. There were zero developer capabilities.  

These vastly different strategies have vastly different KPIs. In one, you’re looking for business-focused applications and clients. You compromise quantity sold for price per unit (see: $3500 for the device). With B2C products, your assumption is that you’re already leveraging economies of scale in manufacturing and production, so you aim to make up the balance with quantity sold. 

Feature image credit: ChatGPT with the following prompt “An image that’s a clever feature image for a blog titled ‘the bull case for Apple'”

I started by paying around $40 to clone my voice. The audio I sent the company was terrible. Just absolutely terrible. It sounded like I was recording my voice from across a room. 

They cleaned up the audio and really created an amazing narrator. It sounded almost exactly like me (which was beneficial as I listened back, as I don’t like the sound of my own voice).

Then, I copied and pasted my book into the platform, and I pressed “Submit.”

It didn’t go well.   There were all sorts of formatting errors and other elements that needed cleaned up.

So, I went through the whole book, inside the app I used, and I cleaned it up. 

I pressed “Submit” again.

It was better, but it wasn’t perfect. There were logical errors. Emphasis was occasionally placed on the wrong words.

For example, the book uses sub headers.  In print, sub headers are noted as being a different font and weight, then, the paragraphs follow.  In the AI audiobook, the sub header was copied-and-pasted, but it didn’t contain a period, so the AI read it and the first sentence of the first paragraph as a run-on sentence.

Witty remarks I made in the book were awkward.  At one point, in regards to using data, I say “It’s the laziest person on your team. Hopefully it is, anyway.”  A human reads that as a witty remark.  The AI said it in a completely flat tone.  It took 5-10 different attempts to achieve the result I wanted.

Then, the platform, an admittedly very new platform, had a bug. I couldn’t export files. Then another bug. I couldn’t generate new audio. Then another bug.  I couldn’t export files (again). Nothing major, but the bugs stopped me from accomplishing the task at hand.

All-in, I spent about 45 days on the process, on and off.  It was probably 10 hours of work.

Had I recorded the audio in a sound studio and hired someone on Upwork to edit and export the audio, it would’ve cost me upwards of $600, taken 2.5 hours to record, and maybe an hour or two to manage the project with the freelancer.

Instead, I spent only $150 but 10 hours.

The AI voice clone was so magical that I thought “of course it’ll work to record the book.”  From there on, my usage of the AI was like a toddler crawling around and bumping into furniture.   I made progress, but not without frequent and sudden setbacks.

In my use of many new AI tools promising the world, there’s a common thread: the AI is literal magic at doing a task, then it sucks at some other part of the task that’s equally important but seems “basic,” and you’re left picking up the pieces.

It seems like I often spend as much or more time finagling the AI than I would’ve spent simply doing the task the old-fashioned way.  I don’t have a problem working with platform customer support.  Hell, sometimes, our code has bugs! It’s only when they promise you the world, then seemingly underdeliver.

I was in a discussion with a friend recently who had a similar experience with an audiobook but using a different service.  In our discussion, I called it “the 50% of AI.” 

Sometimes, the AI is nothing short of magic, and it’s a 150% improvement on whatever currently exists. Other times, it is a drag, it’s buggy, and it’s irritating, which is a  -100% improvement.

Is it an improvement? Yes.

If I did another audiobook, would I now know what to do and it would be way easier? Yes.

Is it a perfect-fit solution that changes the way everyone operates forever and ever? No.

If you work with ChatGPT frequently, you’ll notice this phenomenon.  Sometimes, it’s easier to just do the work yourself.

Over time, I’m sure the -100% will get resolved, but I think the question is when?

Thanks to Miranda Wagner, Shannon Waller and Terise Ryan for reading drafts of this essay.

Feature image credit: DALL-E accessed through ChatGPT with the following prompt: An image of a computer with headphones on in a sound studio recording an audiobook. The sound studio is an old 70’s studio with lots of smoke and wood panel walls. There’s also the room with the sound booth. The computer is smoking a cigarette. illustrative style. The computer is in front of a microphone. There’s a human working on the sound board.

I couldn’t disagree more.

Feedback, at its most basic nature, is someone else giving you their opinion on a thing with the intention of helping you.

However, framed in the manner of an opinion, no matter the intention, I find the framing of the initial statement to be ludicrous.

“All opinions are a gift.”  How laughable.

Intention, however, does matter. Individuals with positive intentions toward you are valuable, even if their ideas are not, this time around.

Many opinions are misinformed. Many lack knowledge of the full system. Many are shrouded in personal stories and past experiences and battle scars.

Informed, valuable opinions are worth their weight in gold. Someone who routinely has an informed, valuable opinion about a consistent topic is considered a “mentor” or “expert.”

Feedback from mentors, experts, those with relevant past experiences, and those who have been where you are, oftentimes, I find to be invaluable. I’ve never had better shortcuts in the path to get where I am today than brilliant feedback.

On the other hand, I have never wasted more time than when I took someone’s feedback as gospel, and then discovered that the feedback was either misinformed or only applied to that one person, client, or account.

So, not all feedback is a gift, just like not all opinions are a gift. 

Great feedback can be nothing short of life-changing, but that is rare.

Good feedback can lend itself to a marginal improvement.

But not all feedback is a gift. Some is merely a distraction.

Thanks to Miranda Wagner, Shannon Waller, and Terise Ryan for reading drafts of this essay.

Clients for most of the tech industry were people and businesses that worked in other industries.  Tech was a small space, only a few players made the foundational building blocks, commonly referred to today as the “picks and shovels,” to run a tech company, and so growing the market position meant building products and services for everyone else.

As the tech industry grew and became what it is today, more and more companies were built for the sole purpose of helping other tech companies. Amazon, the consumer-facing company, built Amazon Web Services.  Microsoft, the company best-known for Office and Windows, built Azure.   I’m a firm believer that all B2C SaaS companies eventually become B2B, but the magic of AWS and Azure was that it served tech.

Most tech businesses have the best legal economic model in history.   They build something once, the cost of which can be expensive, then they sell that thing lots of times with very low marginal cost.  This is true in both software and hardware.  In software, writing the code and getting the application working costs lots of money, but selling it to a new person costs virtually nothing.  When building a chip, getting the fabs and the manufacturing lines built may take several months and cost hundreds of millions, or billions, of dollars, but the manufacturing cost of each chip is minute.

The high fixed-costs, low marginal-cost nature of tech is the primary reason why tech companies are so investable, they’re so scalable, and they’re so profitable.

Those three reasons are exactly why a new economy emerged: companies that build software for tech companies.  As the total amount of new capital in VC has grown, more companies have gotten funded each year.  As more companies have gotten funded, the total addressable market (TAM) of tech companies has grown.  As the TAM of tech companies has grown, more companies have decided to build software for tech companies.

We’ve entered an era where there are dozens of platforms for to-do apps and note taking apps and blog applications, for example, targeted exclusively at employees of tech companies. There are coding assistants for your coding assistants.  Email apps to decrease your time spent doing email each day.  AI for everything in tech.

Tech, as an industry, continues to grow so much that are now three kinds of tech companies: tech companies that build foundational building blocks (picks and shovels) for other tech companies, tech companies that build products for everyone else, and tech companies that build software for other tech companies.

Due to their being in tech, tech companies are more willing to try new tools, so more software startups serving tech companies stay around longer.  Some solve a real need, get traction, and become a standalone survivor of the startup Olympics.  Many, however, fade off in existence, losing to the next hot app that takes their place.  Worse, yet, some lose not because a new tech company outcompeted them, but, instead, because the “old way” was simply better.  The latest hot tech to-do app that charges $1/day loses out to Apple Notes.  The email app that charges $1/day loses to Outlook.  The paid calendar app which has one cool feature gets copied by an incumbent with better distribution and is rendered, effectively, obsolete overnight.

What’s gotten lost in all this tech hype is building tech for everyone else.  Nobody is building new project management applications for construction companies.  Practice management systems for dentists haven’t been revamped in decades. Manufacturing ERP systems could be so much better, but nobody has taken the time to understand what’s really needed to create a 10X better user experience.

I was recently at a conference with some of the most forward-thinking entrepreneurs in the world. The only caveat is that those entrepreneurs are, largely, nontechnical.  They buy, but don’t build, technology.  They’re terrified of AI because they don’t understand it and because they don’t know where to start.  They don’t even know what to Google to get started.

I was thinking about their fear.  If they’re some of the most advanced, successful entrepreneurs in the world and they’re scared of AI, how are most other nontechnical entrepreneurs feeling? Why are they feeling that way?

Tech, as an industry, has been growing so fast that the industry forgot that a large part of its original client base was everyone who wasn’t in tech. 

There are plenty of big opportunities to be a tech company serving tech companies, but I think there are opportunities just as big, if not bigger, in serving everyone else.

Thanks to Bill Bloom, Shannon Waller, and Terise Ryan for reading drafts of this essay.

I think of myself as the CEO of Evan, Inc.  I am the CEO of my businesses, my health, my time, my relationships, my purpose, and my time.  With that in mind, I think the best way to think about the economics of being a digital nomad is by using financial statements.

The income statement answers the most common question that people in the lives of Miranda and me are asked.

“How can they afford it?”

In my opinion, it’s hardly interesting because anyone can take 30 minutes and easily reverse-engineer our nomad expenses to reasonable accuracy.  That said, let’s review it anyway.

Income Statement

Revenue – Expenses = Net Income

Revenue

We still run our companies and work.  For both of us, our personal income last year was the best it had ever been.

Standard Expenses

In Ohio, we had the following living expenses:

• Rent / Mortgage

• Utilities

• Internet

• Car maintenance

• Car insurance

• Gas

• Food

As a nomad, our expenses are much simpler:

• Airbnb

• Flights / Trains

• Food

Airbnb. Utilities, internet are covered.  We don’t need to buy anything for the kitchen.  We don’t buy cleaning supplies.  We buy food and maybe trash bags and that’s it.  We tried to make the Airbnb cost about as much as rent + utilities + internet would be, although usually we were a bit over. 

Our usual Airbnb nightly expense was about $80 or $90.  Because we did long stays, we often received 15% – 25% discounts, so we were getting $110 – $120/night places for $80 – $90 / night.  In expensive cities, we spent far more. In cheaper cities, we spent far less.  We would almost((almost because sometimes the pictures didn’t match the reality)) always have a newly renovated Airbnb with two bedrooms in an upscale part of town.

We found this was the sweet spot.  A lot of times, the most expensive Airbnb wasn’t the best one; it was the biggest one.  The best locations, amenities, internet, and reviews were oftentimes Airbnbs in the $80 – $125 / night range pre-long-stay-discount.  We found that the most delightful Airbnb we stayed in was one of the least expensive, while one of the most difficult Airbnb experiences we had was also the most expensive. Although cheap Airbnbs are generally low in quality, we often didn’t notice a significant difference between mid-range and expensive ones.

Flights / Trains. Flights in Europe are stupidly cheap. Besides flying from rural Turkey to London, I can’t remember a flight costing more than $110 USD per person. 

No cars. Gas prices dominated the news last year, but we don’t get cars when we nomad.  We walk everywhere or Uber.

Living Like Minimalists. We live like minimalists a bit out of necessity.  We could travel with a bunch of stuff, but we don’t.((Recently, I saw that a few nomads travel with a cast-iron skillet.)) We only keep the items that fit in our luggage, so we didn’t spend lots of money on new clothes or other physical items, simply because we couldn’t carry them. Furthermore, since we are living in Airbnbs, certainly no home goods!

Net Income

I haven’t calculated whether we spent more money or less than we had while we were in the USA, but I know it’s close enough that I think we spent about the same amount in 2022 as we had in 2021 on a cash-on-cash basis.  This takes into account rampant global inflation in 2022.

Sometimes, I think people ask us how we afford it, while comparing their European vacation to our 8 months in Europe. European vacations from the USA are amazing experiences that can also be insanely expensive while being compressed into short timeframes.  Consider the following; during a 10-14 day European vacation, there are:

• Exorbitant, round-trip trans-Atlantic flights.

• Most or all nights are spent in a hotel room in the touristy area of town, which is inherently more expensive.

• All meals are eaten at restaurants.

• Fun experiences! Otherwise, why would you go?

• …and still all expenses from back home.  Rent/Mortgage, utilities, etc.

Nomading through Europe last year, we had:

• 1 exorbitantly-priced flight across the Atlantic.  Flights in Europe were cheaper than my car’s gas bill each week. 

• We stay in Airbnbs, which are much cheaper than hotels, but also we usually stay a 10-15 min walk outside of the touristy area of town.  It’s usually quieter and much more livable.

  • We also ensure they have full kitchens so we can grocery shop and cook our own meals.

• Fun experiences!  We’re still tourists!

We took vacations, but we didn’t have the exorbitant flights across the Atlantic, nor did we have any “living” expenses during our vacations, since we had no permanent residence we were paying for back home.

And, our businesses had their best years ever.

We both came out on top.

Balance Sheet

Assets – Liabilities = Equity

At its simplest, in business, assets are money or things that will put money into your bank account.  Liabilities are things that will take money from your bank account.  The optimization function is to optimize equity: the total value of the business.

On my personal balance sheet, assets are things that enhance my peace, freedom, and sense of adventure, whereas liabilities are things that detract from them.

Assets

Freedom of Location. Remote work allows us move freely without the need to ever show up to the office and without any pause about whether or not our coworkers or boss won’t approve. 

Freedom of Time. I, largely, create my own hours.  In an average week, I have 7-10 hours of meetings.  That means that, within reason, I can work independent of time zone.  Last year, revenue across our various companies, in aggregate, more than doubled, yet I was 5-7 hours ahead of US/NY for most of the year.  I was more effective and efficient than I am in US/NY time.

I was also more peaceful.  I joke that, basically every day, we would go on a walk in the morning and get a coffee, tea, and treat, but those morning walks are things I look forward to now.  Everybody else is working, so the streets are relatively empty.  Usually, I haven’t started my day yet, so I’m not stuck with a cluttered mind.  It’s not the same at 6PM when the streets are crowded from everyone walking home from work and I’m mentally exhausted.

Freedom to be paid in USD, but spend in the local currency.  This is one of the keys.  We are paid in USD.  The dollar, thanks to the ingenuity, entrepreneurship, and structure of the American system, is as strong as it’s ever been.

When we arrived in Great Britain in March, 2022, the GBP/USD exchange rate was $1.35 GBP to $1.00 USD.  By September, 2022, the exchange rate was $1.10GBP to $1.00 USD.

Three years ago, in Italy, the Euro/Dollar exchange rate was $1.35 EU to $1.00 USD.  In July, 2022, it was $1.00 EU to $1.00 USD.  It was briefly $0.97EU to $1.00 USD.

Most places, in general, are also cheaper than the USA.  Switzerland, London, and Edinburgh were the three key exceptions, where prices were, especially in Switzerland, quite a bit higher.  In Colombia in January 2023, a latte in the nice part of town was $1.50.  Dinner for 2 was often less than $20.00 USD.  In Argentina((where I’m editing this post)) in February, 2023, a sirloin steak is about $8.00 USD.

In Portugal and Croatia, prices marginally cheaper than in the USA.  Less than 20% cheaper.  In Romania, they were quite a bit cheaper, less than half the price of the USA.   In Turkey, they were much cheaper.  In France and Spain, they were about equivalent.  

Freedom to Control My Financial Outcomes.  June, 2022, was my worst month in business in history.  Revenue was great, but expenses were insane.  In my organization, I have the authority to go create new revenue and cut expenses, and by the end of August, the ship had been turned.  By the end of October, the income statement had righted itself.  By the end of the year, all was well.

Liabilities

Minimal.  That’s kind of the whole deal.  As a nomad, I have as minimal physical attachments as possible.  In this case, a liability would be something that ties me down to a particular location.  I own the stuff in my backpack, my carry-on suitcase, and a company.  I say this as a joke, but it’s largely true. 

There are some non-physical attachments to list in the liabilities column.  I miss the friends and family that I can’t see on a more regular basis.  

Equity

I optimize my life for inner peace and for freedom.  I’d argue I optimize for inner peace, and the first-most-important dependency in that equation is my freedom.

Being a nomad is the most free that I can be.  I can go where I want, when I want, and, within reason, do what I want.  Miranda and I have both said that if we won the lottery, we would live the same life we are living now.

It has been the most fulfilling experience of my life.  Being a nomad isn’t about optimizing my business (although it’s growing quickly) nor is it about optimizing my health (although I’m healthier than ever before) nor is it about optimizing my relationship with Miranda (although I think it’s better than ever before).

My personal balance sheet’s equity is about optimizing my life on my terms and how I want.

Notice, it’s not how anyone else says I should optimize it.  It’s not how anyone else says I should live it.  How I want to.  My monthly income statement has revenues, expenses, and income.  It’s structured same as anyone else’s, but it has different numbers. 

I designed my balance sheet, however, to be exactly as I want it.  I determined the definition of assets and the definition of liabilities.  Some peoples’ assets may be stability, connection, thrill, or time spent reading.  Mine aren’t objectively better than anyone else’s, but they’re certainly better for me.

You are the CEO of You, Inc.  Your income statement will always be Revenues – Expenses = Income.  Your balance sheet will always be Assets – Liabilities = Equity.   The magic of the balance sheet is that you get to define your assets, your liabilities, and what equity means to you.

Thanks to Miranda Wagner, Bill Bloom, Nina Ryan, and Shannon Waller for reading drafts of this essay.

I experimented with ChatGPT to write sports articles. I gave it the following prompt:

On December 13, Argentina played against Croatia in a World Cup match at Lusail Stadium in Doha. Julian Alvarez scored 2 goals, the first in the 39th minute and the second in the 69th minute. Messi scored one goal at the 34th minute. Argentina won the match 3-0. Write a 300-word brief about the match.

It outputted the following brief:

On December 13, Argentina faced off against Croatia in a World Cup match at Lusail Stadium in Doha. Argentina came into the game with a strong lineup, led by superstar Lionel Messi. The team was looking to bounce back from a tough loss in their previous match, and they started the game with a high level of intensity.

In the 34th minute, Messi scored the first goal of the match, putting Argentina up 1-0. The goal was a thing of beauty, as Messi used his incredible dribbling skills to dance past several Croatian defenders before firing a powerful shot into the back of the net.

Just five minutes later, Julian Alvarez scored the second goal for Argentina, putting the team up 2-0. Alvarez made a great run down the right wing, beating his defender with a series of sharp cuts and quick moves. He then blasted the ball past the Croatian goalkeeper, who had no chance to save it.

The second half saw Croatia try to mount a comeback, but they were unable to break through Argentina’s defense. In the 69th minute, Alvarez scored his second goal of the match, putting Argentina up 3-0. The Croatian players fought hard until the final whistle, but they were unable to find the back of the net.

In the end, Argentina emerged victorious with a 3-0 win over Croatia. The win was a much-needed boost for the Argentine team, and they will now look to carry this momentum into their next match.

This brief is amazing! The only problem is that it’s wrong. Messi didn’t score by dribbling past the defenders, he scored on a penalty kick.  Also, Argentina won their last game.

I updated the prompt I gave ChatGPT to reflect that Messi scored on a penalty kick.  It outputted the following brief:

On a chilly December evening in Doha, Argentina faced off against Croatia in a World Cup match at Lusail Stadium. The Argentine squad, led by captain Lionel Messi, was determined to secure a victory and boost their chances of advancing to the next round.

The match started off evenly, with both teams displaying strong offensive and defensive strategies. However, in the 34th minute, Messi managed to capitalize on a penalty kick, putting Argentina in the lead. Five minutes later, Julian Alvarez added to the score with a powerful shot from outside the box.

The Croatian team fought hard to even the score, but Argentina’s defense held strong. In the second half, Alvarez struck again, scoring his second goal of the match in the 69th minute. The Croatian side continued to press, but were unable to break through Argentina’s defense.

As the final whistle blew, Argentina emerged victorious with a 3-0 win. The Argentine squad celebrated their victory, with Alvarez receiving the Man of the Match award for his impressive performance.

The win was a crucial one for Argentina, putting them in a strong position to advance to the next round of the World Cup. The team will now turn their attention to their next opponent, with hopes of continuing their winning streak.

Overall, the match was a thrilling display of soccer talent, with Argentina showcasing their strong offensive and defensive skills. The victory was a well-deserved one, and the Argentine squad will look to carry this momentum into their future matches.

Again, the brief is spectacular, but it’s factually incorrect.  It wasn’t a chilly night in Doha, and  Alvarez didn’t win man of the match.  Messi did.  Along with his goal, he had a brilliant assist to Alvarez which wasn’t provided in the prompt.

There’s a limitation that explicitly affects anyone using this technology without supervision: ChatGPT knows how to write, but it doesn’t know what it’s writing.

AIs, like humans, are trained to do a task by practicing. Practice requires example data, and that example data comes from past experience.  To learn to write, ChatGPT read all of Wikipedia, among other things. It derived style, nuance, grammar, and colloquialisms.  Then, it modeled how it writes off what it read.

The AI clearly read plenty of articles commenting on Messi’s amazing dribbling ability.  It also surmised that the top scorer in a match is probably the player of the match. 

A human writing an article for accuracy could guess that Messi scored by dribbling past the defenders, but they’d look up a highlight to determine.  They could also think that Argentina lost their last match, but they’d look it up.  Of course, in the World Cup knockout rounds, you lose, and you’re done.

The AI doesn’t check for that information.  The AI doesn’t know any of those errors from anything it got correct, such as the Croatian team playing hard until the final whistle.

The AI knows how to write. It knows how to be interesting in its style, using a phrase like “dance past several Croatian defenders” and “a thing of beauty,” but it doesn’t know if it truly was a thing of beauty.  It doesn’t know that Alvarez actually ran down the middle of the field.  It made that up.

Sometime, probably sooner rather than later, AI will do that sort of fact-checking.  Then, it’ll become a search engine, reporter, blog writer, screen writer, and more.  For now, it’s best as a first draft.  You never know when it’ll be confidently wrong.

Thanks to Miranda Wagner, TJ Ryan, Bill Bloom, and Shannon Waller for reading drafts of this essay.

It discussed strategic and nonstrategic costs.

Explained briefly, a strategic cost is an expense that adds to the bottom line.  Examples would be advertising that works, salespeople, R&D that you can commercialize.

A nonstrategic cost is a cost that is considered “necessary to run the business” but doesn’t add to the bottom line.  Rent, administrative expenses, clerical support, middle management, lawyers, and computers fall into this bucket.

This is hardly the first time a concept similar to this has crossed my desk.  Essentially, if I’m writing a check for something, is it going to make me money very soon or is it going to pay for “other stuff.”

Save management, because a great manager can make you plenty of money, the world has endless opportunities for “other stuff.”  Assistants, project managers, lawyers, SaaS, average managers, “let’s see how it goes” marketing initiatives, coaches, and moonshot ideas are all “other stuff.”

In easy economic times, it’s easy to spend on other stuff.  Time becomes scarce, so you hire an assistant.  Companies are growing faster than yours, so you spend more on marketing or management.  Or, you are marketing and management, so you hire project managers so that you can spend more time on marketing.

In hard economic times, it’s critical to cut that spending.  To quote another book I haven’t read, “What got you here won’t get you there.”  In hard economic times, when the belt needs tightened, “other stuff” needs to be reduced as much as possible.

For entrepreneurs, the good news is that most competition goes away during hard economic times.  The remainder of the competition that doesn’t go away gets scared, they baton-down the hatches, and they enter survival mode.

I’ve already seen this in my world.  As tech enters its third consecutive tough month, companies are starting to shut down, albeit quietly.  Over 150,000 people have been laid off, with many more to come.  While a recession isn’t guaranteed, I’m planning for it to happen.  If it doesn’t, then my feeling is that these measures will be a good exercise in austerity and reprioritizing our customers over all else.

My goal during this recession is to be a cockroach.  My strategy is the following:

1. Identify nonstrategic spend

2. Cut as much of it as I can

3. Repurpose two-thirds of that money for survival

4. Repurpose the remaining third to be strategic spend

My strategic spend falls into two categories:

1. Existing Customers

2. New Customers

I’m about to spend 2.5 weeks traveling to see customers in the US and Canada before I head back out to Colombia to be a digital nomad again.  Then, I’ll be back in March, when plan to see most or all those clients again.  In a world where everyone is conserving costs and headed to Zoom, I’m headed in-person.  This falls into the Existing Customers bucket.

I’m also about to start marketing and telling my story more and not less.  I’ve always hesitated to do that, as I didn’t really want people to know me, but in a world where it’s economically tight and people need a new source of creativity, inspiration, or intrigue, I’ll shoot my shot.

My purpose for this blog post is not to gloat or say “I’m zig-ing while everyone else is zag-ing” but to document my strategy.  I’ve never lived through a recession in my professional life before.  If this works, you’ll certainly know, and if it doesn’t, I’ll do a postmortem.

As I spend more time with my clients over the next few weeks, I’ll probably do this exercise with them as well.  It was a great thinking tool for me, and I think it will be for them as well.

Thankfully, AI, SaaS, and business process automation are tools Teammate AI uses to reduce nonstrategic spend. I am betting they will create the stable foundation for weathering any economic storm.

Thanks to Mom, Dad, and Shannon Waller for reading early drafts of this essay.

Separately, outside of the university environment, I was lucky enough to hear a former C-suite executive of Uber and a co-founder of Airbnb speak.  They both talked about how their companies were changing the world.  The commonly-accepted thought in tech was that taxis and hotels would never recover.  “Uber for X” or “Airbnb for X” became the primary startup idea. 

I specifically remember the Uber C-suite executive say a statement that I echo with my clients:

“There are two things that bring industry disruption.  The first, is a 10X decrease is cost.  The second is a 10X increase in user experience.  We’re doing both.”

Of course, he was right.  Uber was 10X better at both.  In 2013, cabs were hardly a luxurious experience.  Ubers were sleek.  The cars just came to you.  Your payment information was stored in the app.  You could see where you came from, were currently, and were going all inside the app.  They were so cheap.

Airbnb was similar.  You could get a nice place at 25% the cost of a hotel.  Or less. 

Both Airbnb and Uber were promising to change the world.  They were raising money at massive valuations, navigating scandals, and well on their way to being a decacorn or bigger. 

Then several years later, both companies IPO’d.  Lockdowns led to demand-side, supply-side, and sometimes every-side shock.  Venture capitalists were replaced by the public markets.  What was a maniacal focus on top-line growth became a focus on profitability and sustainability.

All of the sudden, when the need for profitability arose, the 11-minute Uber from my apartment to downtown went from $6.00 to $17.00.  A trip from my apartment to the airport went from $15.00 to $22.00-$25.00.  Surge pricing was more common.

Airbnb’s fees rose.  Cleaning fees((not in Airbnb’s control, I know)) were requested with reckless abandon.  The Airbnb fees, themselves, rose.  All of the sudden, prices for a place started to rival, or exceed the price of a hotel.  Some hosts started enforcing that guests pay a cleaning fee while also pre-cleaning the apartment and washing the linens before the cleaners come.

Meanwhile, taxis got their own apps.  They integrated credit card terminals into their cars.  Better yet, you could even watch where you were going on your phone, by plugging in the address into your Maps app.  In many cases, especially at airports, they arrive faster than an Uber would. 

Hotels upgraded their apps, offered more diversified room pricing and amenity offerings, and enhanced the customer experience.((Serendipitously, right after finishing the first draft of this, an Airbnb host was 2 hours late to give us the keys to our place, and had forgotten toilet paper, trash bags, and hand soap.  It was our first such occurrence, but one of note.))

Companies like Booking.com allowed you to order a private taxi service to and from the airport and order a hotel at the same time.

When a new company introduces a groundbreaking new customer experience or radically lower costs, it’s easy to give credit to the technology.  It’s easy to say that the old world is “disrupted” or “dead,” and that company is the “new world.” 

In reality, we don’t know until the dust settles.  The dust settles when investors move from private to public.  It settles when the company needs profitability, not growth, to justify its valuation.  When PR calls become analyst calls.  When price-to-sales becomes price-to-earnings.

Now, I use Uber when I’m feeling lazy or in a new city, but if I’m at a hotel, I have them call a taxi.  If I’m at an airport, I either arrange a taxi ahead of time or use public transit from the airport.((Whichever’s faster.  The City Mapper app tells me.))

I use Airbnb when I’m staying at a location for an extended period, but I use a hotel for any stay fewer than 5 days.  Airbnb is perfect if I’m with a big group, like my whole family.((There is an argument that can be made that Airbnb truly disrupted timeshares, but the stated disruption was hotels.))

Uber and Airbnb are firmly in the category of companies that are not disruptive; they’re transformative.  They forced the old-guard of their industries to modernize and enhance their experience. Private funding allowed them to serve customers at a radically lower cost, gain market share, and push the world forward.

Only then did they truly find their niche.

The free + ads model is pervasive in today’s world.  Facebook and Google took share from news and created a new paradigm.  “We’ll give you more, for free, and in exchange, you’ll see some teeny tiny ads.”

All of social media became supported by the model.  Google, Pinterest, Facebook, Instagram, Twitter, Snap, TikTok, and YouTube are free + ads.  In fact, you can’t pay for these services. They don’t allow you to.((Snap is flirting with a paid program, but the core functionality is free.))

Even in the midst of election controversy (Facebook and Google and Twitter), geopolitical controversy (TikTok), and antitrust threats (Facebook and Google), ad-free models were not abandoned in favor of paid subscriptions.

Why is that?

A new wave of apps became big in the early-to-mid-2010s.  Uber, Calm, Headspace, Netflix, and Hulu.  All consumer software-as-a-service (SaaS).  All receiving tons of hype in the press, venture funding, and unicorn or decacorn status. 

At the time of their IPO, most (if not all, not all have released their financials) were unprofitable. Some still are.

In the late 2010s and early 2020s, Disney+, Mint, and Preply came along as new B2C SaaS platforms. 

All of them now monetize B2B in one form or another. I think there are a few reasons why:

• B2C relies on consumers spending their discretionary money on your service. Because of that, the amount charged per month or per transaction must be relatively low.

• It’s much harder to convince 100,000 people to use your service than it is to find 10 companies to sign up 10,000 users each.

• Assuming you find 100,000 users to use your service, at least 25% will use it once and never again, and a very very small percentage will pay for it.  In B2B world, seats are pre-purchased and users are different than checkwriters.

• In B2C SaaS, different groups of users could have tons of different optimization functions, whereas in B2C, the optimization function can be pre-defined and, oftentimes, simpler.

Social Media (Facebook, Twitter, TikTok, Pinterest, Snap, Instagram) sells ads.  The users are the product, and the advertisers are the clients.((Yes, Snap just launched a subscription service, but it’s < 5% of revenue)).

Netflix, Disney+, Peacock, HBO Max, Paramount+, and Hulu all already have or are launching subscription tiers.  In fact, Hulu makes more money off it’s lower-cost, ad-supported subscription tier than its premium, ad-free tier.((https://www.businessofapps.com/data/hulu-statistics/))  I expect others to be the same.

Spotify, Duolingo, and LinkedIn all have most users free + ads.((I would argue all of LinkedIn is B2B, even for individual users.))

In the fintech world, it’s the same.

Mint, the budgeting app, monetizes through paid subscriptions at the premium tier, but ads and referral deals in the free tier.  There’s minimal difference in functionality between the free tier and the subscription tier, so the subscription tier is clearly doing well.

Calm and Headspace, the meditation apps, have free plans and subscription plans that are available B2C.  They both monetize heavily through corporate sales.

Uber has launched ads inside of the Uber app.

Even Tinder shows ads.

I’ve developed a few core tenants of pure-play, consumer SaaS.  The core idea is that all consumer pure-play SaaS monetizes B2B when it wants to become profitable.

The key words in “pure-play, consumer SaaS” are not “consumer” or “SaaS” but “pure-play.”  The rules change when there’s a proprietary item that exists in the physical world that also has an app or service associated with it. 

These tenants are primarily for people making business to consumer apps or services.  When I was starting out, I thought that you build an app, launch it, market it on social media, and people come.  If you charge $5.00 or $10.00 per month to enough people, then at some point you’ll have a business with near-zero marginal cost.

I tried this strategy and it failed.  I’ve seen others try this strategy dozens of times.  It’s never worked.

These tenants are what I wish I would’ve known.

Core Tenant #1: In B2C SaaS, the lower the cost per use, the stronger its B2B angle

The easiest example is one everyone knows: social media.  Free for users, but businesses pay-to-play with ads.((Yes, you can create a Facebook business account, but talk to any business owner and ask if they get reach.  They’ll tell you they did, but they haven’t since before the pandemic.))

Spotify is a great example. Their ad-free subscription is $10.00 per month.   Every song someone listens to costs Spotify around $0.01.  If someone listens to 20 hours of music per month (in the car, working out, etc), Spotify needs to pay out $3.24 to the music creators.  Then, Spotify has costs to run and maintain the app and its services.  Assume that’s $2.00 per user per month (for argument’s sake).  It’s really hard to build a great business making $5.00 per month in gross profit.

Or, you could treat your listeners as a product, sell ads to businesses, and not have a per-user, per-month revenue cap.  Amazon Music is the same way.

Similar rules that apply to Spotify apply to the big streaming services like HBO Max, Disney+, Netflix, Showtime, etc.  Pay for content (either through licensing or outright-buying the programs), then resell it on a monthly subscription that’s used several times per week.

Mint is similar. People check their balances all the time.  The price of a Mint subscription is less than I spend on one Uber ride to dinner.

As usage decreases, the cost per use goes up, and likelihood of the app being a B2B service goes down.

Uber, for example, which is introducing ads into its app now, isn’t quite B2B yet.  It’s still a B2C, two-sided marketplace app.  I estimate I spend $20 per ride on Uber.  Far more than I spend on any individual service above, but I only use it once or twice per week, max.  The same rules apply for Uber Eats, Doordash, and the like.

The biggest cost-per-use for me is Airbnb.  A pure-play marketplace SaaS, there’s minimal B2B component at all.  It’s almost direct B2C, but for each use, I pay quite a large fee.

Core Tenant #2: B2B is an easier equivalent sell than B2C

It’s easier to sell $100,000 in a B2B setting than it is to do so in a B2C setting.

In B2B, there are essentially 3 optimizations that any business will buy:

1. Help me find and retain my best people

2. Help me find and retain my clients

3. Help my business be more efficient and/or save money

Any business monetizing ads is actually a lead generation business. 

Headspace and Calm are in the business of helping retain the best people.  The unit economics on Calm and Headspace are simple.

Assume it costs $10,000 to hire and train an employee.

Now assume that corporate pricing for a meditation app is $5.00 per month, and a company has 10,000 employees, so a total expense of $50,000 per month for the company.  If that benefit keeps just five people out of ten thousand in the business instead of taking a new job each month, the app pays for itself.  That doesn’t include the productivity gains that come from having employees with better mental health.

The average annual employee turnover rate in the United States is 47.2%.(( https://www.creditdonkey.com/average-turnover-rate.html))  A meditation app subscription doesn’t need to be too successful to be ROI positive for a company.

A meditation app needs to be magical to be ROI positive for those same 10,000 users in the real world.

When individuals are paying out of their own personal money, there aren’t 3 optimizations, there are hundreds or thousands.  It could be to be happier (and each user defines that differently), more peaceful, healthier, help with a relationship with a significant other, help with a breakup, help with a relationship with kids, parents, or siblings.  It could be because the user wants to “be someone who meditates.”  Maybe it’s meditation as a sleep aid.  Meditation to reduce stress or anxiety. Meditation to find their purpose.  The list goes on and on and on.

How do you optimize for that?  The easiest way is to decide to make a very narrow difference, say, only help people who want to use meditation as a sleep aid, and expand into other areas over time.

But then you’re stuck trying to find 10,000 people who only want to use it as a sleep aid.  Customer acquisition cost balloons, and unit economics become challenging.

That’s not even including churn!  Nearly 25% of people use the app for precisely one day.(( Nearly 1 in 4 people abandon mobile apps after only one use | TechCrunch))

In the B2C world, SaaS apps are competing for a very small amount of discretionary income with a great number of optimization functions.   The challenges scale exponentially.

In the B2B world, the client (the company buying the app) doesn’t care if Bill in accounting never uses the app.  They care that a few people in their 10,000 person organization use it, see the value in it, and stay with the company longer, in whole or in part, because of it.

Core Tenant #3: Businesses are better creative partners in your success than consumers

The reason why is in the name of the customer group.  Consumers… consume.

It’s not that they’ve got ill-intent, it’s that they’ve got too many optimization functions.  Being a hero to some means ignoring the needs of others. 

In the B2B world, since there are so few optimizations, it’s much easier to be a hero to a greater percentage of the customer base.

Mint can work with their ad and referral partners on better ways to optimize in the app.  Facebook can release new ad tracking features. Headspace can provide better usage and data analytics to their clients. 

In the B2C SaaS world, the driver of user retention is new features.  In the B2B world, the driver of user retention is investment.  The same feature can be shipped, and it has a wildly different impact on a B2C audience as a B2B audience.

Imagine if a meditation or wellness app shipped a feature that told you, the user, that for the following 2 hours after a 10-minute meditation, your heart rate, on average, was 3 beats per minute less than the same time period but without a meditation.  To a general user, this insight is relatively interesting, but not life changing.  To a business, this is cause for celebration.  They can begin having employees do in-app meditations before important meetings!

Imagine the big streaming providers find a way to deliver one new ad unit that’s proven to have high conversion, that the provider is selling for $20/conversion.  They ship the feature, and, being generous with their users, they even lower the cost of the subscription by $1 per month in exchange for that ad unit (this would never happen, but for the sake of the thought exercise).  B2C customers think “Cool, my subscription got cheaper.”  B2B customers rejoice because their cost of getting a customer was only $20.00.

While these examples are extreme, they point to the fact that the same feature but directed at the wrong audience doesn’t move the needle.  Directed at the right audience, and it’s a game-changing innovation.

Core Tenant #4: Early-stage consumer-facing SaaS categories need 5-10 years to mature

Rideshare, grocery delivery, food delivery, fitness subscriptions, ed-tech, health tech.  The list goes on and on.  Thank goodness for venture capital, which is the primary engine that allows for this to happen.

When the category is being created, there is no B2B play yet.  It’s not that the ROI hasn’t been proven out, it’s that the category hasn’t been proven out.  Oftentimes, new consumer-facing categories need 5 or 10 years before they can navigate the hurdles that come with enterprise sales.   If someone doesn’t understand it, they won’t buy it.

Duolingo is a great example of this.  They’ve already branched into the B2B marketplace with ads, but they had 2.5MM((https://www.statista.com/statistics/1248043/duolingo-annual-paid-subscribers/)) subscribers in (not through, some people churned).  They’ve already started getting into official language testing. 

The space is still being proven out, but I expect school systems will assign homework through Duolingo, businesses will buy subscriptions for their employees, and businesses may even buy subscriptions to it for their employees’ kids.

Core Tenant #5: Loss-leaders and churn-reducers play by different rules

But what about Apple Music?  Apple TV+?  Prime?

They don’t have ads.((In the case of Prime, the Prime Originals don’t have ads.)) They don’t have any real B2B monetization (businesses can buy a prime membership, but it’s essentially the same as a personal membership).

I’d argue they’re B2B as well, even though they’re not explicitly the profit driver (although, in the case of Amazon, Prime is).  They’re services built to reduce customer churn and increase usage of the companies’ other products and services, so they give a ton of value away, possibly at a loss, but make it up on the back end with additional, high-margin sales.

The “customer” of those services is another department inside their own company.

If I have subscriptions to Apple Music and TV+, I’m very likely to buy another iPhone or AirPods.  In that case, Apple Music and Apple TV+ are customer retention tools for iPhone and AirPods.

If I have Prime, I’m very likely to buy more stuff on Amazon.

Prime Video and Prime Photos are examples of B2C subscriptions whose purpose is to reduce churn in the number of Prime subscribers.  If you’ve got thousands of photos in Prime Photos or your favorite show is Marvelous Mrs. Maisel, there’s a low likelihood that you’ll churn and cancel Prime.  If you don’t cancel Prime, there’s a low likelihood you’ll stop buying stuff off Amazon.  If you don’t stop buying stuff on Amazon, then Amazon can continue to charge a 35% seller-fee on almost every item sold.

Apple Music and Apple TV+ operate as a “loss-leader.”((We don’t know if they’re truly loss-leaders or not, but we know they aren’t huge profit drivers for the company.  Services revenue is at all-time highs, but lots of the high-margin revenue comes from the in-app payment fees, ads, and Google’s placement of Search.))  If I really love Apple TV+, then I’m more likely to continue buying an iPhone, iPad, or Mac.  If I really love Apple Music, I’m more likely to buy AirPods for the best listening experience.

Loss leaders and churn-reducers have very different incentives than pure-play, make-a-high-profit-margin-business SaaS companies.  Loss leaders and churn-reducers are in the business of being “good enough.”

If my competitor’s product is a loss-leader for a different business, I’ve got to have a product that’s at least 10X better because of the concept of “enough.” 

If my competitor’s product is “good enough,” then the consumers will always flock to free.  In a competition for discretionary income, having a paid product that’s 10% or even 50% better isn’t good enough. 

In the case of Prime Video, is it “good enough?” Yes, it is.  As a consumer, might it stop you from churning on Prime?  Yes, it absolutely might.  If you’re a huge Lord of the Rings fan, you’re not likely to cancel Prime as Amazon builds out that universe.   If you’re considering building a new streaming platform, you’ve got to have 10X better content than Prime Video to win on merit, because you’re competing with “free.”

What do you do if you’re only B2C?

Start looking for the B2B angle.  How are you one of the three big optimizations?  How can you be that way?

The truth is, the big money is in B2B.  Businesses pay more for less because they need one problem solved to see a 10X return on investment.   Consumers pay less for more.  It’s of no fault of their own, they each have a different optimization function.

This doesn’t mean don’t build B2C consumer SaaS.  It does mean think about the monetization angle differently.  It’s easy, as a consumer, to think that the vast majority of apps are B2C (hell, I’m using it, aren’t I?) and the ones I use at work are B2B. 

That’s not the case.

Addendum 1:

There are a few notable exceptions to the tenants above.  First, non-subscription micropayments.  Roblox, Fortnite, and other game-type companies that take small payments in exchange for additional functionality defy these core tenants.  Crypto / Web 3 is trying to introduce more micropayments and less of this type of B2B monetization, but the space won’t be proven out to be successful or unsuccessful for another 5-10 years, minimum.   

I originally thought YouTube TV and Xbox Game Pass defied the tenants, but, now, I don’t think they do.  YouTube TV, a rebundling of cable and also includes ads, so there’s clearly a B2B angle that’s being exploited.  The business still isn’t quite mature enough.  Over time, my estimation is that the B2B offering will be where the profit lies.  Secondly, Xbox Game Pass is not a pure-play SaaS company.  It’s easy to forget that you can’t really use the service unless you own an Xbox, which retails, for the lowest-tier hardware, at $297 USD, or $24.99 USD per month. While it’s certainly a SaaS product, it’s not pure-play.

Lastly, sports betting and gambling.  They’re B2C-only from what I can tell.  One could make the argument they aren’t pure-play, as they’re an extension of sitting in a casino and betting, but I think they fit the qualifications and break the rule.  I’ve been flipping back and forth between these apps being SaaS and being entertainment, but I can’t find a B2B angle.

Addendum 2: A non-exhaustive list of seemingly consumer-facing, pure-play SaaS companies that are beefing up their B2B offering.

• Coinbase -> Institutional holdings, AWS for web3.

• Gemini -> Institutional holdings

• Robinhood -> payment for order flow

• DoorDash / GrubHub / Uber Eats, etc -> ads

• Social media companies -> ads

• WhatsApp -> reduce churn for Facebook family of apps

• Venmo -> charges stores fees, invests the money you keep in your account

• Uber -> ads in the Uber app, lead-gen tool (both supply-side with drivers and demand-side with customers) for the higher-margin Uber Eats

• Apple App Store -> ads, 30% fee of all in-app payments

• Google Play Store -> ads, 15% fee of all in-app payments

• Streaming providers -> all are either monetizing off ads or tools to reduce churn or a loss-leader

• Spotify -> ads

• Duolingo -> ads, certification tests.  Still too early to tell.

• Tinder, Bumble -> ads

• Mint -> ads, referral fees