Nate Sullivan

Now that we're live, Resolution is making some important staffing decisions.

[www.youtube.com/watch](https://www.youtube.com/watch?v=8m761uj_vZ8)

Welcome aboard, Brian. Hope we hear more from you soon.

Big news! The new and improved, public version of Resolution is live and ready to use. It's still missing some stuff (more on that in a sec) but the major improvements are up and running. Those include:

• Account creation
• Model publishing to a public URL
• An onboarding engine / help center / contact widget
• A scratchpad where you can build an (unsaved) model without logging in
• way better ESC/Enter handling (this was making me crazy)
• better error messages
• tons of weird, edge case bug fixes
• prefixes for units (so you can append "inches" or whatever to the end of "length")
• Just general handsomeness and reliability

What's Missing / Immediately Next

Hilariously, our biggest remaining tech holdup isn't tech at all -- it's me getting a bunch of stupid tax and corporate information established with Uncle Sam so I can set up Stripe properly. Actually switching over to real payments shouldn't take long after that, so ideally it'll only be a couple of days. BUT, for now, you can make an account and save/share up to two models as is, and build as much crazy stuff in disposable-Scratchpad-mode as you'd like.

I'm not going to actually blitz people with this thing until payments are running (you know, because money), but I'm more than happy to have you kick the tires if you've found this on your own, or already knew about it. Make sure to check out the Examples page not only for video walkthroughs, but included links to models you can really use and copy into your account.

So be sure to check out what's new, share what you build, and let me know what you think!

I am not a shitposter, I swear. I don't even really have time to construct inflammatory takes, let alone take abuse for them and somehow turn that into engagement or personal brand or whatever it is people do with internet rage.

So when I saw the Top Gun sequel, I kept things to myself. I listened to podcasts I respect, and heard nothing but total praise. I floated some criticism past friends and co-workers, and got the exact same reaction.

"This is one of the best sequels of all time."

"It's better than the original."

"This is one of the best movies of the last decade."

I just can't. I know what I saw, and it... wasn't that good.

Why Top Gun Is Good

My argument -- nay, feelings -- about the Top Gun movies is/are not complicated. This is not some bank shot where I explain to you the history of aviation-based cinema and then at the last second make you realize something subtle but devastating about these movies. It's much simpler than that.

1. The original Top Gun movie created a bunch of awesome, exaggerated characters
2. The setting/premise of the movie means you don't have to unpack a lot of the details about those characters; Maverick and Goose are 20-something badass Navy pilots, Goose does young Dad things, Maverick does young non-Dad things, Iceman is a dick
3. Maverick being awesome at flying is not weird. It might be UNLIKELY that he can do the specific things he can do, but who cares -- someone is the best at flying F-14s, and it is not unreasonable to think that person is a 20-something non-Dad badass who would try to hook up with his attractive military consultant quasi-boss. The specifics of what you can do in an F-14 are not important to me; everything looks kind of real (and even awesome pilots like Maverick and Iceman make mistakes in the movie, validating how difficult all of this is), so a general movie non-expert like me is fine.
4. These awesome exaggerated characters go through "relatable" things. It's not that I can relate to going to fighter pilot school -- I cannot. But I can relate to being good at something I'm good at, going up against other people who are also good, struggling, losing my mojo, and needing to think differently about my awesomeness to regain my confidence and save the day. That's actually... super relatable.
5. The important people grow and change, because people often grow and change under exciting, challenging, dramatic circumstances. Maverick loses his confidence and regains it through a series of trials. Iceman learns to respect what is different about Maverick after they overcome a life-and-death challenge together. Goose dies.

I'm not putting in "Tony Scott creates a magical, sun-kissed nautical playground" in here because obviously he does that. Top Gun is a great looking movie. It also has ridiculous shirtless volleyball scenes and other odd things in it, and all of that is fine. Sometimes it has perfect music, and sometimes it has slightly odd, borderline stupid music. Whatever. You could say doing more or less of those different things would make Top Gun better or worse, but I don't really think any of those things make Top Gun fundamentally "good" or "bad". Top Gun is an okay story -- not great, but crucially, it is an okay story -- attached to great characters, and getting those two essential things right enough makes it a fundamentally good movie to me. Are they great because they are incredibly deep? No, not really, but they are deep enough and vibrant enough that most of the time you are either rooting for them, mad at them, empathizing with them, or feeling bad for them.

Why Top Gun: Maverick Is Bad

When I say this movie is bad, it's important to realize I mean more "it is a bad thing" than "it is a bad movie". I say this because absolutely no one agrees with my "Top Gun: Maverick is bad" take at the highest levels, and I'm starting to think this is (partially) why. This movie does a bunch of things extremely well; it looks incredible, the flight footage is awesome, the sound basically rules, etc., etc., and so forth. Plus, even though it is stupid, movies can be fun and stupid and perfectly fine. Independence Day is a stupid movie that is totally fine. In fact, Independence Day is actually in the upper tier of stupid, totally fine movies for some of the same reasons Top Gun is, even though Top Gun is (while still ridiculous) less shlocky and eye-rolling and "better" for a variety of reasons. But I definitely did not want want Will Smith's character to die, I definitely didn't want Vivica A. Fox's character to die, and I am legitimately happy for the drunk cropdusting veteran guy when he tells his children he loves them. It's still a stupid movie, but I'm not like "this movie is bad for movies and the people who watch it". In fact, I basically think the opposite.

So don't come at me with "bro you are overthinking this". How dare you. How dare you lower the bar for Top Gun like that, a movie that is directly responsible for me saying "talk to me, Goose" to my children when I am trying to get them to open up about their days at school. And I'm not even a Top Gun person! I am just a random general culture-consumer who realizes that Top Gun did a really good job of making me care about/relate to pretend, exaggerated fighter pilots!

Now, for those of you -- and there are many, including film and TV critics/professionals who I really respect and who make me embarrassed to even write this -- who legitimately think Top Gun: Maverick is a great execution of a Top Gun sequel (let alone a good movie on its own), here are my problems.

1. Maverick is not a blank slate. This is the character we met in Top Gun, thirty five years later. He is not "aging out" of fighter pilot age. He has absolutely blasted past the window when you are even allowed to fly these planes at all, and he is clearly still -- at present -- the best pilot who has ever lived.
2. This is... absolutely incredible, and yet it's not really considered that big of a deal. What has Maverick been doing? It says that he is extremely decorated, which seems unsurprising (and is very easy to accept), but lots of people don't really seem that impressed with him?
3. This is even more absurd because Maverick is clearly still vastly better than every single person around him at all times. Wouldn't it be well known by all these hotshot fighter pilots training for this mission that not only is Maverick the best ever, but that he is STILL the best, and is showing zero signs of even slowing down?
4. It would make sense if maybe the young pilots were BETTER at some stuff, but Maverick came in and said hey, you guys don't know how to dogfight, all you do is shoot missiles from 100 miles away, etc., etc., and his old guy tricks became relevant and helped him compensate for being SIXTY YEARS OLD.
5. But that's not what happens! He's already better than everyone at everything! Imagine if Michael Jordan walked into Charlotte Hornets practice, today, except instead of being old and kind of chubby, he was in peak physical condition and actually BETTER than he was in, say, 1993. And then, on top of that, imagine if when an absolute space-alien like that walked into the gym, LaMelo Ball was like "you're old news, grandpa". And then all the other players laughed and high-fived, and the big drama in the room was that, I dunno, Horace Grant's kid was on the team or something and had a problem with MJ. Who cares! 60 year old Michael Jordan just came in after putting up 85 points against the Bucks last night! The only thing that matters is this absolutely incredible space alien who is standing here.

Do you see the problem here? It's not a "the writing is weak" complaint -- although the writing IS weak! It's a "what are we doing here?" complaint. The fundamental canvas of this movie isn't just implausible from a what is happening standpoint (i.e., Tom Cruise keeping a plane flying at record speeds and then surviving a crash of said plane through.... sheer force of will, I guess?), it's that even accepting all the implausibility, the reactions of one implausible thing to another just don't make any sense. The entire plot is just the Navy not understanding that they have peak Michael Jordan sitting there, on the bench, and they are like "MICHAEL, CAN YOU TEACH GORDON HAYWARD SOME MOVES". There isn't even a Lethal Weapon style "I'm getting too old for this shit" vibe. He's very specifically not getting too old for this shit -- it's all he wants to do, it's an apparently desperately needed skill, and he's unquestionably the best at it. There's no actual conflict!

The only time the next generation is relevant at all is when Maverick simply runs out of hands from doing too many awesome, incredible things at the same time. Thanks for the assist, Hangman, I really needed your help after singlehandedly saving Rooster with my plane, somehow not dying, stealing an ancient, abandoned F-14 and almost killing all the bad guys with it.

In the original Top Gun, Maverick thought he was good enough, and the plot proved him wrong. He had demons to overcome, and ultimately the story of him overcoming them is a story of a guy who should be the best figuring out what it took to actually be the best. You can make fun of the details, but the journey holds up.

There is no journey at all in Top Gun: Maverick. Maverick is inexplicably, uniquely incredible the entire time -- no one else, friend or foe, comes close. Not even THE EARTH, which he crashes into at phenomenally high speeds not once, but twice in this movie, both while (of course) being totally badass (saving a fellow pilot from a missile, and breaking some speed barrier). It's just a matter of how big of a problem he can unilaterally solve (quite big, it turns out!), until he requires someone to basically hold his beer for a second until he can catch up with whatever the impossible challenge is.

That's not a journey! Top Gun: Maverick says "let me tell you a story" and then proceeds to do a series of cartwheels while beatboxing. It's 100% humility-free boomer pornography. It's here to tell you not only that the old dogs still have value, but that it's the (accomplished, adult) kids themselves who are completely unnecessary -- they are simply impediments to the best thing doing what it does best, which is whatever it wants to be doing at the moment. 60 year olds were the best when they were 25, they're the best now, and they'll always be the best! You kids will never understand! VRRRRRROOOOM off on my motorcycle!

Top Gun: Maverick is bad.

This is one of those topics that doesn't seem like it needs me to add to it, as most of the smart, correct things have already been said. Still, I've read some odd things from smart people who are missing some of the elephants in the room that make it pretty clear Elon Musk will never succeed with Twitter unless he basically puts it into the equivalent of a blind trust, which he is probably emotionally incapable of doing.

Here are some of the key reasons.

Technology is hard

People at technology companies are often well-paid, and relatively well-treated by the standards of most people who have normal, kind of crappy jobs. I've had regular jobs and tech jobs, and I much prefer the way I've been dealt with at tech jobs even though I certainly haven't enjoyed every day at work. It's still a lot better. 

Here's the thing -- technology is hard. Not every person at a big technology company is important, or even necessary to have around, but a surprising number of them actually are. Sometimes it's because you're dealing with a weird social problem like what Twitter called "Trust and Safety", sometimes it's because selling things like services or advertising, or uptime, or other concepts is complex and weird, and sometimes it's just because software engineering at scale is hard, grinding work that a lot of us literally cannot learn to do. Learning to code is not learning to do CrossFit. Some of us are just not smart in the kind of way you need to be to do it. 

Managers don't like this. Venture capitalists don't like it (actually, they hate it). Hell, sometimes I don't like it because I want to build things I don't know how to build and it costs a fortune and a lot of patience to get them built. But that's the way it is.

There is this bizarre idea that companies like Twitter have these "coddled" employees, but what they really have are the employees necessary to make something like Twitter work like Twitter. The same is true at places like Amazon, Apple, Google, etc. -- there is absolutely bloat and people who aren't necessary, but in general a lot of the work requires really talented people with extremely in-demand professional experience. If you want those people to do what you say, you have to defer to them a lot, or you can try building it yourself. Good luck. 

Being an asshole isn't going to work

This is America, so if you want to reconfigure the term "woke" to mean, I dunno, just being unable to handle adversity or whatever, that's your business. But people don't have to accept your definition, and when they look at this South African billionaire making fun of Twitter's good faith efforts to support its black employees during the legitimately traumatic upheaval of Ferguson, they are going to see -- at best -- a guy being a idiot and a bully for no discernible reason. Again, that's the generous interpretation. 

The people who don't like that -- the people who ultimately won't work for that person -- will come from many backgrounds and places. What they will have in common more than their race or gender will be a tendency to have the skills, education, and experience that you need to run something like Twitter, unless you don't really need it to work very well, handle security issues, etc., etc. 

Musk, Sacks, and all these guys can sort of wish that away and pretend they are all brilliant computer scientists, but it's not going to work with people who have the necessary skills. 

Attention is not revenue

I keep hearing that Musk trolling everyone and dabbling in white nationalism-style tropes and circles is "marketing" because he's "controlling the narrative". I get it -- he's lighting a huge pile of garbage on fire and screaming at the top of his lungs and people are looking. In theory, if people are looking at something, you can slap ads on it and make money. 

But that's only in theory. You don't get money when people look, especially when they don't pay for anything (and as Twitter Blue 2.0 has shown us already, there's no compelling reason to pay for this and Musk can't think of one either). You get money when advertisers give you money. Yes, they need to people to look, but looking is one of those "necessary but not sufficient" conditions. As I once said to a colleague when my marketing department was asked to generate more "buzz", I could get us on CNN whenever we wanted if we just starting throwing televisions and musical instruments off the roof. That attention would be BAD, but it would be attention. 

It's absolutely false that all PR is good PR. Lots of PR is horrendous -- this is why there are PR firms. Twitter looks like a badly run, weirdo tech zombie that is being run by douchebags and is veering into a "basically racist" vibe that advertisers aren't going to touch with a ten foot pole. 

He's not winning, and I don't think he knows how to stop. 

Just like you can spend months rolling out critical back-end improvements to a software application to no reaction whatsoever, only to set off a riot when you change the color of a button, "AI" is having a moment (again) right now because the folks at OpenAI did an awesome job plugging their work into something we can all relate to -- an overconfident, well-spoken, semi-competent reply guy.

I don't need to say it but I will -- as an experience for random internet users, this is an extraordinarily cool, well-implemented experience. I used to use some ancient Mac version of ELIZA as a kid, and I got a huge kick out of it even with its immediately obvious flaws, so comparatively this is like talking to something from the year 3000. That doesn't even take into account the whole "write me a song/poem/bible verse" aspect of this, which will be entertaining us all for some time.

Obviously ChatGPT, as it's known, isn't perfect. In fact, since it's hard to describe exactly what ChatGPT is, or what it's intending to be, I'm not sure it's possible for it to have a definition of "perfect" to begin with. But it does a couple of things that, in theory, you probably wouldn't want something like this to do if you could help it.

1. It's often wrong about objective facts
2. It almost always sounds right

The second thing is more of a good thing by itself ("it's so well spoken!"), but it's also something that makes the first thing much, much more of a problem. Of course, there are people like this, too, and there have been throughout the history of people. But in my experience, they're actually pretty uncommon. The majority of folks I've met who don't know what they're talking about give it away by also sounding like they don't know what they're talking about. This is in important, easily taken for granted component of human-generated bullshit that allows us to sort through it without even trying that hard.

But if machine-generated bullshit can sound right more frequently than the man-made variety, the fact that anyone in the world can crank it out by hitting a button is an absolutely enormous problem. People's "this guy doesn't know what he's talking about" detectors are pretty good, but they're trained to detect the kind of specious nonsense that -- written or not -- comes from people, or at least much more socially awkward robots. We hear/read/see certain cues, and we use those things to filter out a lot of life's junk. This new stuff either doesn't have those factors ("look deep into the eyes of this computer"), or emulates it better than the vast majority of crooks, liars, and major-party presidential candidates ever have. 

There's already plenty of discussion about the social impacts of this kind of thing, and for good reason. Unless we specifically tell them to, robots probably aren't going to rise up and kill us in the immediate future. But it's very possible they'll be used by us to generate enough automated nonsense to destroy the necessary levels of trust and social cohesion that society needs to function. Seems bad. 

Still, I'm not here to focus on the fraud and gaslighting part of this. Instead, consider this much more basic issue: in a world that isn't just dependent on AI-driven insight, but is actually polluted by AI-generated noise posing as either data or analysis, how are you simply supposed to do your job?

Cognitive Automation Cranked to 11

François Chollet wrote a great, high level explanation of what today's real-world artificial intelligence is, and is not. I strongly encourage you give it a read. But for the extreme layperson, basically when regular people (hello!) talk about AI, we talk about a wide variety of tasks and concepts, many of which we've collectively made no progress on at all. But we also talk about things that can be done with what Chollet refers to as Cognitive Automation, and we really have made pretty amazing, practical strides in that over the years. 

In Chollet's words, cognitive automation means "encoding human abstractions in a piece of software, then using that software to automate tasks normally performed by humans". What we've seen in the internet age, and more recently with the work of groups like OpenAI, is a huge leap forward in our ability to encode tons and tons of fairly complex abstractions -- far more than the experiments and "AI" demos I grew up with ever had to work with. 

Abstractions ain't the whole bag, of course. The next level up would enable software to help us make better decisions in the complex real world (not in a closed off system, and not by simply presenting or sorting data for us in a certain way, as many tools do today). Beyond that, you're talking about independent minds and consciousness and a bunch of stuff that we are absolutely nowhere near making a reality -- "science fiction", in Chollet's words.

But the thing about mastering abstractions is that if you master enough of them, you sure do start to look and sound like a real mind, at least to regular dummies like us. And if you really master abstractions, you can sound smarter than a real mind, because we often evaluate the quality of an idea, or the accuracy of an objective fact, based on a bunch of abstractions like the human language used to explain it. 

And while computers might still be dumb, they sure are fast. So we taught them how to figure out a secret social handshake, and then they used their inherent computer-ness to go ahead and learn how to handle another bazillion of them or so. The end result is pretty compelling, even if it's not actually any smarter. 

Bullshit Detection 101

So what do we do? Ben Thompson wrote a fascinating piece on the flaws and implications of ChatGPT and in doing so, introduced to me the awesome concept of "Zero Proof Homework". The idea, in a nutshell, is that the next generation shouldn't try to block out garbage content from AI, but instead be challenged and evaluated on their ability to catch the errors and/or lies that come with it. After all, even in this early version, ChatGPT can spit out incredibly authoritative sounding answers and arguments, complete with references, that are completely and totally wrong. That's because it doesn't actually understand the information itself -- it only understands language. 

This is weird and counterintuitive to a lot of people. Many of us think of numbers as things that computers can work with easily, and language as something qualitative and human. But numbers and language are both simply abstractions of something much more important and complex -- the meaning, logic, and context of the world around us. People aren't always good with those things either, but they can learn, whereas something like ChatGPT (despite its apparent mastery of our abstractions) literally cannot. However, it is so good at using that vast library of well-encoded human language abstractions to generate believable content that it will often appear like it understands the world better than you do.

Remember the Friends episode where Joey tried to make people think he owned a Porsche by wearing a bunch of Porsche merchandise? Did he actually need to own a Porsche? In some ways, he didn't. In some ways, he did. But if you interacted with him from a certain perspective, with a certain set of expectations and information, he effectively did own a Porsche. Maybe even moreso than someone who actually, technically, legally owned one and got to drive it around.

Your Pre-Existing Bullshit

I could now spin you a dystopian tale about your information-economy job, where you're inundated with so much data and analysis, from so many sources that look right, and sometimes are right, but often are not, that you can barely make a decision. A world where people stare at output generated by different algorithms and weakly poke at it, hoping that it will fall apart with basic scrutiny if it says something bad, and if not, ready to push a different button and generate a different result, maybe from a different algorithm. 

Except... this is already what work is like! It's been like this for years! We use business systems every day that have mastered an even less complex set of abstractions ("pipeline revenue", "units sold", "project velocity") and posed as voices of wisdom and authority, like two kids in a trench coat trying to get into an R-rated movie.

So what we do we do at work? Well, for the big stuff -- quarterly reports, managing cash, etc -- we tend to do things by hand, or with systems that are reliable, because they're actually pretty simple. They either just tell us observably true things, or project things with math that at least one person at the company understands, and is capable of challenging and auditing. That's how we keep the lights on. 

But for WAY more things than you'd like to admit, we're total suckers for context-free conclusions that prey on how easy it is to impress us with a mastery of our most trusted abstractions. Over here, this system will calculate how valuable the marketing team is! This other one will tell you how happy everyone is! This one will tell you what your customers want! Turns out they want lower prices! Who knew? THE DATA KNEW, APPARENTLY. We either buy into -- or reject -- these systems and their methodologies for the same reasons we buy or accept a ChatGPT answer. Maybe the system is objectively correct/incorrect, and we have the knowledge to confirm that. Maybe it feels correct, or is at least partially correct in a way that makes us okay trusting the parts that are a mystery to us. 

What Thompson is proposing when he talks about teaching kids to challenge AI generated content makes a lot of sense for kids facing a future of plausible sounding misinformation. But it also sounds like a great idea for people making business decisions right now. 

I did a poll on LinkedIn last year where I asked people about their level of confidence in mapping out how their company makes money.

{editor’s note from the future: Wordpress ate this screenshot at some point, but basically it’s a graph where everyone says they have an extremely accurate sense of how their business makes money)

In the words of many a noted business expert, "C'MON, MAN!" Either your definition of "extremely accurate" is nonsense and you need some perspective, or a whole lot of you are just straight up full of it. Many of you would believe any Salesforce report I waved in front of your face if the numbers sounded familiar-ish and it had normal looking pie charts where most of the slices were of vaguely similar sizes. And for a long time, that's been basically fine.

But it's going to get worse, and if kids really do adapt to machine-generated incompetence, whether it's due to education or simply overexposure and needing to survive, those kids are going to work with you in a couple of years and wonder why you're such a gullible rube. Because for kind of an embarrassingly long time, holding up something you found on the Internet, or some default report the CRM spit out for you, was the easiest way to look smart.

But pretty soon, it's going to be the fastest way to look like you need to retire.

Years ago, I was a new-ish employee at a startup that was both (a) 100% set on becoming a massive enterprise software company, and (b) celebrating closing a $20k annual contract with one of the biggest companies in the world.

“But wait…” I said, nervously. “How many companies out there actually need our product?”

5,000? Maybe 2,000? A lot. And either way, we just closed one of the biggest ones!

“Right, but if one of the biggest companies that will ever need our product is paying $20k a year for it, that’s a maximum of $100m in annual revenue for our business, assuming there are really 5,000 companies that need us.”

Well, it might be more than that. Plus, we’ll upsell them!

“Upsell them to what?”

More users!

“How many more users? What do additional user accounts cost? How many people at this giant company need another user account?”

The conversation broke into a variety of directions – everyone had a different, qualitative take on all of these things – and it became clear to me that we had absolutely no idea what we needed a customer like our recent win to pay in order to actually, logically declare the whole operation a success.

And nobody really felt like that was a reasonable problem to solve.

Math is easy, but context is hard

These were not dumb people, or people who were literally bad at math. In fact, they were very smart, thoughtful people who were quite good at all kinds of math, whereas I barely passed calculus (or trigonometry, let’s be real). But that didn't matter, because the problem wasn't a traditional math problem.

It was a context problem.

None of the individual math questions I had were very difficult. The problem is that there were a lot of them, they were all connected to each other in various ways, and those ways were all in flux. You could assume there were 5000 potential customers, but that might be wrong, and if there were actually only 2000, that would affect a bunch of other math problems needed to figure out how much the average customer needed to pay you to build a $100 million dollar company. Or a $50 million dollar company. Or a billion dollar company! And what if we had two products? Three products? One-off services in addition to recurring subscriptions?

In other words, it wasn’t just that a ton of different numbers might have to change. We could handle that. Instead, it was that the logic connecting those numbers – the context, basically – might have to change, and there was just no good way to keep all of that organized in our heads, or on paper.

We focus on what our tools do, and they don't really do context

"When all you have is a hammer, everything looks like a nail.”

In business, context is often experienced as a source of frustration instead of a problem to be solved because the business tools we’ve been conditioned to think with are all pretty horrible at context. Just like bad, ad-hoc PowerPoint enrages people or puts them to sleep but is still somehow the norm, bad, ad-hoc spreadsheets continue to be how we try to project unknown futures or win arguments.

But… spreadsheets are terrible for this. Instead of making lots of simple calculations easy to manage, change, and understand, they bury them inside a complex formula language and an arbitrary grid of coordinates. Because spreadsheets are fundamentally about cells and values, and not about relationships, you can put anything you want into any field at any time no matter how impossible or nonsensical it is. A spreadsheet can tell you that a value is missing, or outside some range you define, but it’s never going to be able to tell you that something doesn’t make any logical sense.

That logical sense… is context! It’s exactly what we needed when we were trying to figure out whether to celebrate or mourn a $20k contract, as well as exactly what we needed back when we were figuring out what user accounts should do, how much they should cost, and how many people we should hire to sell them.

In business, context is more important than calculations

I've been talking to people about their spreadsheets for a while now. One thing I've noticed is that people talk about them the same way they talk about their driving. Everyone thinks they are above average. But while most people seem to think they're pretty good with spreadsheets, they also had a long, angry list of problems they have with ones made by someone else.

Given my experiences, this isn’t really that surprising. Even if you’re able to represent a massive, complex scenario with your spreadsheet (totally possible!), all of that context and understanding of the situation the spreadsheet represents – it’s in your head! Or at least it’s in your head until things get too big, or you don’t look at it for a while. But the sheet itself is just a horrendous way to discuss, debate, or convey the context of things to/with anyone else. This is fine if you’re looking at the exact same P&L statement you’ve looked at every quarter for five years (i.e., what spreadsheets are for, and where they’re fantastic) and not fine at all if you’re trying to figure out a random, specific business decision you’ve never had to make before.

In fact, when we actually need to figure out context, more often than not I’ve found myself having a conversation over something completely different – a whiteboard. A whiteboard doesn’t do any math at all, but it’s a much easier way to very quickly suss out relationships and logic. People will scribble boxes, draw arrows, violently circle and erase things, and do all sorts of things that reference math, but don’t actually do any of it.

Then we run off and try to bake that context into a spreadsheet, so we can never look at it ever again.

The cost of context-free thinking

I've worked for a lot of different startups at this point, and none of them have been able to completely avoid this kind of context-free thinking. And the costs of that have been pretty enormous, encompassing a variety of dumpster fires like:

• wildly insufficient investment at key points of the business
• lack of accountability for impossible promises or goals (and the resulting credibility loss)
• no shared understanding of costs (in time, money, or morale)
• nonsensical lead-gen expectations for ideas like social media campaigns or cold calling
• unsustainable practices (rate of hiring, discounting, sales without user adoption)

... and a bunch of other terrible things that either weren't in anyone's spreadsheet, or if they were, had too many assumptions buried in too many formulas. And I don't blame the spreadsheet paradigm itself (it's not perfect, but spreadsheets are pretty amazing) as much as the culture that exists from building so much of our strategic thinking around the wrong tool for the job.

Tools matter. They affect our thinking! If we only dug holes with dynamite, we’d have a very different culture across a variety of disciplines. Construction, landscaping, telecommunications and other fields would all have a very different set of expectations, procedures, and required skills. Someone would surely be selling tiny little explosives to my Mom so she could get her garden ready for spring, and they would certainly argue that there was no need for a fundamentally different solution, because “everyone uses dynamite already”. But until we figured out the idea of a shovel – a demonstrably weaker, “less capable” solution for digging holes – we’d never really unlock so much of what we’re able to do today.

Business can be kind of stupid sometimes, and not stupid in a way you necessarily fix with high-powered answers like mass automation and machine learning. Sometimes, it’s just stupid because people – you and I – need to have a better understanding of how things work (and don’t work), and that’s something we’re going to have to figure out on our own… with the right tools, of course.

For what it’s worth, I’m having a blast working on a new generation of tools designed to help people do exactly that.

Without thinking that hard about it (and probably moderating my red hot take as a result), this is one of the best scenes from any movie ever made. (More than a few f-bombs in here, if you’ve got a kid around.)

[www.youtube.com/watch](https://www.youtube.com/watch?v=WlKr-yg-y5I)

I’ve obviously watched this a million times, but I’ve never really felt obligated to use it in an analogy, until today.

It's just a quarter, and look how much more you get

I was just reading this Verge article on some of the concepts behind WeWork fraud kingpin Adam Neumann’s latest, wildly overcapitalized venture. The central thrust of the piece — and the critique of Neumann’s logic, really — is that while he’s talking about doing a lot to increase the tradability of a certain asset, he’s not actually doing anything to deal with the fact that the assets are often garbage.

When we started Efficiency Exchange ten years ago (holy crap), a major inspiration for the company was my wife’s work with auditors, who were tasked with assessing extraordinarily qualitative things (conditions and output quality of a factory) and turning that into data that could be consumed by people halfway around the world, some of whom had never been to a factory in their life. There was a TON of interest from VCs and other tech-world investors in making that data accessible, sortable, and identifying patterns and detecting efficiencies from it using things like (yes, groan) machine learning.

But there was very, very little interest in whether that data was, fundamentally, any good. There were people who worked on that aspect of things, but they were of a very different mindset, and essentially wanted to build better audits, align companies on standards, and do things like that. Basically, while the VC people only thought about scaling things — even if what they were scaling was fundamentally useless — the sustainability people only thought about that real-world applicability, and never about scale. That’s one of the reasons why progress on that front is so slow, whereas ten years later I can ask a web app to draw me a picture of Kermit the Frog eating a toaster and it will give me this in 90 seconds.

Basically, we can fix one piece of shit, or we can scale a big box of shit, but we’re just absolutely terrible at scaling a box of fixed shit.

Over the last decade, the scale people have absolutely, totally won, at least from the perspective of who spends, invests, and talks about what. EVERYTHING is at scale. Content, finance, assets, audiences, it’s all scaled. We make a lot of references to the micro-unit — i.e., some random YouTube influencer being interviewed — but the business of YouTube and all the surrounding services and industries are all about scale. After all, YouTube really is a scaled box of shit — it’s just SO big that it has lots of awesome stuff on it. That’s the answer. So much of everything that eventually something good will happen; the trick is just to expose you to as many things as possible in the quickest amount of time (swipe, swipe, swipe) so that eventually you get the dopamine hit. We never really did figure out curation, and it kinda feels like we’ve given up.

It’s not just consumers. The same piles exist at work — people who are focused on some specific thing without the greater context around it, and people who are focused on nothing BUT context. The former will plug away on their work until layoffs are suddenly and shockingly announced, and the latter is often living in a complete fantasy world because they shout queries at Salesforce and endlessly debate other high-level people about what the answers mean.

Does this look like spit?

Which brings me back to Farva and his liter of cola. Here we have a guy who has absolutely no idea what is behind the counter, or how anything back there works, interacting with a system that is only interested in how things actually work. Farva has to conform to the standards of the system to get anything useful, but he can’t — in fact, he actively refuses to — and since he has no understanding of the standards or the system, he gets crappy answers that frustrate him. Even reassurances from the system that it understands him (“that just means make it extra good”) just antagonize him further, because again, he has no fundamental understanding of how things work behind the counter, and he doesn’t want to acquire it. To be fair, the system doesn’t care either, going so far as to take a query it knows is nonsensical (“Do we make Liter Cola?”) and just throw it over the wall and see what comes back.

The best is when Ramathorn implores Farva to sort of “normalize” his query to the system — “just order a large, Farva”, and Farva responds with the legendary “I don’t want a large Farva, I want a goddamn liter of cola”.

Adam Neumann doesn’t want to talk about auditing, dammit! He wants to talk about the blockchain, and a world of frictionlessly trading assets. Are those assets nonsense? Maybe! Is that a problem? Of course not! We’ll push the "vet assets” button and hire a bunch of college grads in a boiler room to read them or something, I dunno.

Oh good, more thoroughly! Why didn't I think of that? No one would invest in an auditing company who claimed they could solve the problems of auditing by auditing more carefully, because that’s not even an idea, even if it’s pointed at an actual problem. Instead, here’s something that is definitely an idea, but isn’t pointed at the problem at all. Perfect! This increasingly dense layer between reality and strategy is starting to drive me absolutely bananas. Those two concepts are different things, of course, but they’re obviously related, no? It’s like we’ve said “the plural of anecdotes is not data” so many times that we’ve decided data or other high-level concepts don’t need to be traced down to an actual real-world use case at all.

I really do think — and this is not even a warm take — that the internet and cloud computing have made solving a lot of unthinkable problems with brute scale actually feasible, and that really is an awesome, mind-opening achievement for technology. I don’t want to lose sight of that as I age. But this has gotten ridiculous, and now we’ve got a generation of people who are simply scaling things not just before they’ve considered the impact of scale, but before they even really understand the thing they’re scaling. The scaled version of the thing is so different, understanding of the micro-unit is a waste of time, or so I assume because I actually have very little experience looking at a micro-unit in any detail. You people are so petty... and tiny!

[www.youtube.com/watch](https://www.youtube.com/watch?v=x_hqPo97SQc)

Here's the thing. With any fixed amount of time and energy, you can do deeper analysis of fewer things, or more shallow analysis of more things. The cheapest thing to do in the age of communities, connectivity, and cloud computing is to do the latter, and so that’s rapidly becoming the answer, even when it's the answer to a question no one asked.

At some point, though, you’re going to find yourself building a billion dollar asset swapping system with meaningless assets, or leaping over the counter to assault a food service employee, which I think is probably some tortured equivalent of investing $350 million in the WeWork guy.