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Use a lot of words

Verbosity is the new brevity.

Google felt like a miracle. We could type just a word or two (“blog“) and it would magically guess what we wanted and take us there.

This shortcut spread from Google to the search built into online shopping as well. How convenient. A few words and done.

AI isn’t like that. In fact, our concision is getting in the way of the insight we’re looking for.

Go to Etsy and search for “white pants” and you’ll get more than 10,000 matches, most of them useless. Instead, type “white pants to wear to a wedding in July in lower michigan for a 30 year old woman” and you’ll get this.

AI systems like Claude and ChatGPT let you attach a PDF or text file to your query. Here’s the useful hack:

Create a document that has pages of background.

Your medical history for example. Include your age and every interaction you’ve had with the medical system, including illnesses and drugs and outcomes. Now, every time you ask a health question, attach the document.

Or, a copy of your resume, work history, letters of recommendation and career goals, all in a PDF. Upload it every time you’re asking for career advice.

It works for business plans, for customer lists and even legal documents. Upload an entire email correspondence, or a fifty page wine list.

AI isn’t impatient, easily bored or distracted.

It’s insatiable.

PS chat GPT knows a shocking amount about you, while Claude starts over every time. Neither promises airtight security, but then again, neither does American Express, Visa or Google…

Hard to predict

The outcome of our work can be easy or difficult to predict.

It’s not hard to determine if a bridge is going to fall down or if code is going to compile. The scientific method and statistics do a great job of helping us foresee some dynamic events.

On the other hand, it’s almost impossible to know in advance if a song is going to be a hit, or if a new project is going to be profitable.

We get to pick which sort of projects we take on.

If you want to do artistic work, you’ll need to give up the certainty that comes with a reliable prediction. Part of the deal.

And when it breaks?

Most of the pitch and the demo is all about how terrific our plans are, and how well our gadget works.

But if we hope for resilience, perhaps it makes sense to show off how gracefully the system breaks.

Because it will break. Because plans won’t work out. Because we’ll be surprised.

And then what happens?

Big scale, big impact

The Beatles changed music. Starbucks changed coffee. Perhaps your project is aiming to reach a large audience.

Consultants call it market share. What percentage of the available market have you reached with your idea? No one hits everyone, but many organizations seek to be a monopoly, or perhaps noticeable in scale.

This flies in the face of embracing the smallest viable market. When we’re seeking scale and market share, we need to think about everyone. We need to aim for the middle, sand off the edges, and become the normal, practical, popular choice.

Along the way, hard-working leaders think, “Hey, if we shoot for 40% market share and end up with just 3%, we’ll still be fine.”

The thing is, you don’t get to 3% of the market by trying for 40% and failing.

You get there by embracing the 1% and doing such a good job that the word spreads.

The smallest viable audience gives you focus, traction and positive direction. The smallest viable audience takes humility, guts and responsibility.

Instead of seeking to fail your way to enough, it makes more sense to commit your way to better.

Perfect

Nothing is perfect…

But everything can get better.

There’s never enough time…

But there’s time enough to make a difference.

Someone will always be opposed to the change we seek to make.

And there’s always someone who wants to help.

Anything can happen…

But something will.

But what do they say at the meeting?

This is the way to understand business-to-business selling.

After you’ve left with the purchase order, what does the buyer tell the boss? What does the boss tell the investors or the press?

This helps decode why giant companies like Google or Facebook buy a company or don’t. It explains why McKinsey can charge 20 times as much for consulting as a former McKinsey consultant can. It explains why TV ads continue to be purchased, and why it’s so difficult for a new entity with a better product to get traction.

“What will I tell my boss?” is the key question.

If you don’t have a good answer, the person you’re calling on will default to, “it’s just like we used to have, but cheaper.”

Confused by signals

Even at a distance, we can sometimes tell if someone is educated, rich, powerful or physically attractive.

But that doesn’t always correlate with smart, kind or honest.

Strong signals might not be the same as useful ones.

Remembering toward better

We don’t get a chance to do yesterday over again.

The best reason to think about the past is because it gives us the opportunity to improve the future.

Because we don’t get tomorrow over again either.

Happy Juneteenth.

Here to please

Please who?

If you’re on a social media network, are you seeking to optimize for the algorithm, the owners of the tech stock or your personal goals?

If you’re publishing a book, are you working for the book or is the book working for you?

You might be able to get the folks in the back row to smile a bit if you play your hit song just like it is on the radio, but perhaps your objective is to please the real fans in the front row–by jamming on something new.

Of course, it’s really difficult to please everyone. Which means that we have to figure out which someone we’re here for.

“I made a mistake”

This sits right next to, “I made a bad decision,” in things that are hard to say. But there are many moments when we’re confused about what actually happened.

You might not have made a bad decision. And it’s also possible you didn’t make a mistake.

It could be that there was simply a bad outcome.

That’s different.

Annie Duke opened my eyes to the distinction, and it’s critically important.

Good decisions are calculations based on what you know right now. If the world turns out differently than the data you had indicated, that’s not a bad decision.

A bad decision is one that isn’t based on available facts. It falls into traps like sunk costs or peer pressure. A bad decision is an error in judgment or skill. Good decision makers, when faced with the same options as you had, would not have done what you did.

But good decisions often can lead to undesired outcomes.

Taking the 8:20 train is a good decision, and if the train breaks down and you’re late, it was still a good decision.

Buying a lottery ticket is never a good decision. Sometimes you win, that’s great, but given the data you had when you bought the ticket, there are clearly more profitable ways to invest your money.

If you start a business and unlikely events cause that business to fail, it’s not at all clear that you made a mistake (or a bad decision). What is clear is that the business failed, and you are involved in cleaning up a bad outcome.

The words matter. Because we should repeat our good decisions and avoid our avoidable errors.

Outcomes happen, every time. But we’re only able to be smart about what we know (including the odds), not about what is about to happen.