“The better you understand context, the more likely you will see how easily you can be missing out on it.”

Tyler Cowen, “Context is that which is scarce”

Magnus Neilsson‘s “Nordic Cookbook” is one of my favorite books, primarily for how it opens:

“If you follow the recipes to the dot as printed in the book, sometimes it’s not going to work anyhow…The way ingredients behave in one part of the world might not be the same as how they behave where you are, for natural reasons…Are you getting discouraged? Well don’t…Recipes are there to give you a base to start from, inspiration…and also to explain the technical base on which you can then build….You will have to use common sense.”

Tyler Kord’s “A Super Upsetting Book about Sandwiches” opens similarly,

“Being able to follow a recipe is like being able to read music, and you should feel free to make it your own a little, because nobody will mind if you like your broccoli a little more cooked than I do….”

And from Belinda Ellis’s Biscuits,

“A recipe can’t tell you exactly how much liquid to add because of the fat content of the milk, the amount of protein in the flour, even the weather can affect the moistness of the dough.”

At the beginning of summer, I walked into the neighborhood library and the librarian asked me why I had the recipe for bread on my shirt.

“I’ve committed to entering a loaf of bread into the Minnesota State Fair.”

Yes in fact, a few weeks earlier, I selected a recipe out of Ken Forkish’s Flour Water Salt Yeast to master and have been baking 2 loaves of bread every week since.

No, I haven’t been happy with any of them. Thank you for asking.

In an attempt to get happier, I switched yeast (somewhat better), then I switched flour (much worse), then I introduced a kitchen mixer (much much worse), then I switched flour again (somewhat better).

As much as Forkish’s recipe is far more sophisticated than my t-shirt – or the title of his own book – turns out it’s also a long way from the level of sophistication required for success with this flour, this yeast, in this oven, in my kitchen, in summer, at this altitude.

At beer club, if you’ve a question about anything in your most recent batch the first response you’ll get from the more experience members, “Did you bring your notes?”

So, like anyone screwing around doing science, I’m taking notes. I’m documenting what seems to work in each batch and documenting how I diverge, inadvertently or otherwise, from what the recipes states.

In the end, if I’m successful, I’ll have this one bread recipe adapted/developed, and if written out comprehensively for someone else (even future me), it will likely be >4 pages (it’s already 2 pages). Four pages is quite a bit longer than four words.

This massive discrepancy in length is obvious to anyone having developed a recipe – especially one targeting commercial food equipment at scale. Or anyone having built and refined anything from zero. There are a number of non-obvious details that are only a concern if the goal is: make it repeatable.

The Ninety-Ninety Rule aims to remind us there are always non-obvious details, context, and decisions that are only encountered once we’re in the middle of an effort.

“The first 90% of code accounts for the first 90% of development time, the remaining 10% accounts for the other 90% of development time.”

The Coastline Paradox reminds us of a similar phenomenon, if you were to carefully walk the entirety of any coastline, the distance walked will be longer than any measurement of the coastline. Which is to say, the complexity of a situation is far higher when you’re in the middle of it than when you’re an observer.

Years ago, Merlin Mann recorded (by my assessment) a classic NSFW rant entitled, Make Believe Help. In it, he drags all the internet publications trading in reframing common sense as the latest life hack. For contrast, Merlin evokes an Old Butcher – an expert in the small details gained through hundreds, thousands, of repetitions.

These reps matter.

Making the same cut over and over. Each time doing it wrong in a different way, in a different spot. Then again. And again. And again.

An active practice.

Reps are only thing that will develop skills beyond what fits on a t-shirt.

Everything that’s not real world reps lacks necessary context, the necessary details, the appreciation for how all the factors fit into place. All the factors, not just the obvious ones.

Accelerating skill development requires creating an environment for the reps, for the practice, including a post-rep assessment;

• Was the target achieved?
• What went well?
• What didn’t?
• What was different this time?
• What do we want to deliberately focus on in the next rep?

Any individual instance matters less than the accumulation of all the instances. There will always be another instance.

All of this is well within the Double-Loop model of learning, which is self-aware:

“Double-loop recognises that the way a problem is defined and solved can be a source of the problem.”

Of course, this is why we have coaches, advisors, structured classes, and multi-year specialized educational programs – all to accelerate the acquisition of greater context for a price. To help us get better at defining the problem accurately.

In my work with startups, I’m continually listening for hints of such an environment an real world reps – whether dogfooding or helping a customer solve a problem today. This is usually evident in if, and how casually, they talk about details and problems non-obvious to an external observer. A surprisingly small number have. Some resist even the mere suggestion. I get it. Real world reps can smell like low-value work that doesn’t scale, especially when your end goal is to abstract and automate away the pesky details. But here is where real competitive advantages lay, not to mention early revenue.

Admittedly, as this story of the Vienna Beef company reminds us, we can be successful for a very long time without fully understanding our own non-obvious details.

No, at this moment, I have no evidence this particular recipe would even do well in the Minnesota State Fair. Yet, I’ve committed to this recipe because it looked interesting, delicious, and slightly challenging. All of which could be part of my problem.

How many more reps can I get in before the drop off date?

“…The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood; who strives valiantly; who errs, who comes short again and again, because there is no effort without error and shortcoming; but who does actually strive to do the deeds;…who at the best knows in the end the triumph of high achievement, and who at the worst, if he fails, at least fails while daring greatly, so that his place shall never be with those cold and timid souls…”

– Theodore Roosevelt, “The Man in the Arena“.

Forty years after their creation GWAR played an NPR Tiny Desk Concert.

If you need a reminder to really, intensely, focus on who you are and what you want to contribute to the world, no matter how seemingly weird and tasteless it may seem to others – this is that reminder.

In my work with entrepreneurs, it’s not unusual to spend a substantial amount of time discussing who the customer for the product in question. 

Yes, spending so much time on such a foundational question may seem a bit silly. 

It’s only an indication of how limited our day-to-day transaction experience is relative to the richness of niche business models in existence. 

It’s worth being explicit about who is and, more importantly, who is not a customer. 

Who is not a Customer?

• Likes are not customers
• Follows are not customers
• Users are not customers
• Stars are not customers
• Personas are not customers
• Downloads are not customers
• Awards are not customers
• AI are not customers
• Algorithms are not customers
• Best of Lists are not customers
• Conferences are not customers
• Suppliers are not customers
• Demographics are not customers
• Psychographics are not customers 
• If they say, “I would buy it if…” they are not a customer (thx to CG for this one)

Who is a Customer?

• The individual person paying you to help them

While generative AI (ChatGPT, etc) is red hot right now, and I’ve been rather cool on it. All of my experiments with it have resulted in rather ‘meh’, uninteresting, completely predictable outcomes.

Maybe I’m missing something.

Which takes me to one of my favorite tools for thinking through effects and consequences comprehensively, McLuhan’s Tetrad. While McLuhan developed the Tetrad tool to think through how media changes us, I’ve found it works for anything phenomenon impacting society at large.

The Tetrad asks four questions;

• What does it enhance/amplify/intensify?
• What does it make obsolete?
• What does it retrieve that had been obsolesced earlier?
• What does it flip into when pushed to extremes?

(Note: this list will likely be continually updated as my understanding evolves)

What does Generative AI enhance?

• Distribution of conventional wisdom (including all the implicit biases therein)
• Near real-time machine-generated translation, especially English-to-English translations like BoringReport.org
• In-the-moment individualized learning of well understood concepts, including both programming like GitHub CoPilot or asking ChatGPT to replace Dr. Google in a telehealth context
• Automated customer service / support / repair
• Quality of interactions with Siri/Alexa/Google
• Output velocity of fan fiction authors, self-publishers, vanity publishers, spam farms, content farms, junk texts.
• the minimum level of writing quality expected by the general population
• Out of office replies
• Role playing games with or without the AI as the DM
• Writing that is distinctly, unquestionably human
• the value of fact checkers
• the quality of NPCs

What does Generative AI make obsolete?

• Generative AI
• text-based news outlets, blogs, and social media
• essay writing
• CliffNotes
• Instruction manuels
• Test prep books
• Paying human writers by the word
• Lorem ipsum and other placeholder text
• search engine optimization
• Amazon’s Mechanical Turk
• Press releases
• CorpSpeak
• Memes

What does Generative AI retrieve?

• Handwriting
• Paper towns, canary traps
• ELIZA
• Clippy
• Ask Jeeves
• text-based video games
• oral traditions
• pamphleteering
• Pop Art
• Luddites
• Secretaries / administrative assistants
• The dead (or at least those that have left a sufficient volume of writings behind)
• The unpolished, clunky, sincere, and completely human, amateur web

What does Generative AI flip into when taken to the extremes?

• Personalized doctor in your pocket (for all generally accepted, non-controversial, interventions)
• AI-to-AI interactions – whether both AIs realize it or not. (I refer to this concept as ‘Replicorp‘)
• Active avoidance of text content by humans as it can’t be trusted
• Some people insisting on in-person or face-to-face interactions only, to minimize exposure to “the model”
• All the dystopian sci-fi:
  • Her
  • Rei Toei
  • Marvin the Paranoid Android
  • Blade Runner
  • Master Control Program
  • Young Lady’s Illustrated Primer
  • Idiocracy

After compiling all these, it still seems neutral to net negative. Maybe a net positive on the customer service side. I can see the technology providing a richer experience to those things that currently have an ‘algorithm’ or any kind of robust template, but current applications seems like a way to generate low quality, filler content even faster than we can today.

To that point, for comparison, for full disclosure, and for the smug superiority that the human generated one above is much more satisfying, here’s ChatGPT’s Generative AI media tetrad:

What does it enhance or amplify?
Generative AI enhances our ability to create new and original content using machine learning algorithms. It can generate everything from music to art to text.

What does it obsolesce or push aside?
Generative AI may obsolesce the need for human creativity in some areas, as machines become better and better at creating content that is indistinguishable from that produced by humans. It may also push aside traditional methods of content creation, such as manual design or composition.

What does it retrieve that was previously obsolesced?
Generative AI retrieves the ability to create and innovate at scale, something that was previously limited by the time and resources required for manual content creation. It also retrieves the ability to work with vast amounts of data and patterns that are difficult for humans to perceive.
What does it reverse into if pushed too far?

If generative AI is pushed too far, it may reverse into a situation where human creativity and innovation are devalued, and machines become the sole creators of content. This could have negative implications for society, such as job displacement and loss of cultural diversity. It may also lead to a loss of control over the content produced by these machines, as their decisions become increasingly opaque to humans.

Product is a trailing indicator of demand.  

Marketing is a leading indicator of demand.  

In between is art.