Chamber 🏰 of Tech Secrets #32

Some things never change

The Chamber 🏰 of Tech Secrets is open. This is the second post this week, but I have stumbled into so many ideas I want to write about that you may see a few more posts over the remainder of the year. Perhaps you’ll even see a “12 Days of Chambers of Tech Secrets of Christmas” later. 👀

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Snickers and Uncertainty

Sometime during the peak of the Great Recession in 2009, Warren Buffett was driving around Omaha with another CEO and he was asked about his views on the situation. As they drove past closed down shops, Warren was asked how the country would ever recover from this? Would the world ever be the same again?

Warren responded, “Do you know what the best selling candy bar in the world was in 1962?”.

He answered his own question: “Snickers”.

“Do you know what the best selling candy bar in the world is today?”

Again, “Snickers”.

And that ended the conversation.

Photo credit: Wikipedia “Snickers” page

What is the point? There will always be unexpected situations, difficult times, radical shifts, black swan events, unexpected breakthroughs. These things are all unknowable until they fully manifest. Further, there is often nothing we can do about them in the moment. We would be wise to focus our attention not on the things around us that are changing rapidly, but on the the things that won’t change… the things that will still be the same in a year, five years, ten years.

Credit for this story goes to Morgan Housel on the Tim Ferris Podcast #703. Morgan has a new book called “Same as Ever” (available by the time this is published) which is about this very topic. I am looking forward to reading it. I recommend the full Tim Ferris interview as well. (Update: I started the book on publication date and this is the opening story).

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Uncertainty and Generative AI

The Generative AI space is rapidly changing. OpenAI made some significant announcements at DevDay this week (the subject of next week’s post) that are significant to the AI landscape. It is easy for enterprises to get stuck in loops around what they don’t and can’t currently know, leading to analysis paralysis, anxiety, inaction, or too much action (but in the wrong directions). What advice do I have for practitioners or leaders who are trying to figure out what to do? I was asked that question a few weeks ago at the Live recording of “What’s New in Data”, and this is what I said…

Just like Warren was able to focus on the things that would not change during the Great Recession, so too can enterprises focus on the things that won’t change while the Generative AI space develops rapidly around them.

What are some things that won’t change but that will set an organization up for success when the time is right?

• The People: What are the people we need to engage to make progress in AI? Build relationships and collaboration now. This includes legal, privacy, compliance, data and analytics, and technology practitioners.

• Data Foundation: No data, no AI. Are you in a strong position as it relates to your data management practices? Do you have your data cataloged? Do you understand its quality? Do you have metrics to help track freshness and completeness in place?

• API Foundation: How well are your organization’s capabilities as a business covered with functional, enterprise APIs (intended for reuse)? If you want to harness AI for efficiency gains or automation, you will need a way for it to interact with your digital and physical “world”. APIs are the way.

• Experiential Learning: What can you do to learn? Commit to something for a few months and see what you can. Pick an LLM. Pick a Vector Database. Pick a use case. Do some things. The technologies will likely change over time, but the patterns of interaction are likely to remain similar. They are, often, just interactions with yet more APIs anyway. “Hungry? Why wait?” (kudos to John Kutay for this one).

Don’t get too focused on all the stuff you can’t control and/or that is unknowable today. Instead, focus on what won’t change. The things above won’t change: you will need a solid team of people, a strong data management foundation, API’s that enable interaction with your business’ capabilities, and some hands on experience with the types of APIs in the Generative AI ecosystem. If you focus on what you can control, you’ll be well-positioned to take advantage of opportunity when the time and conditions are right. If you already have (had) all these things, kudos. You are ready.