Five New Thinking Styles for Working With Thinking Machines

4. Sculpting vs. gardening

If the raw material for creative work becomes sequences and intuition instead of rules , essences , and processes, how you do your work is going to look significantly different. It will look more like gardening as opposed to sculpting .

In a pre-AI world, creative work was similar to sculpting. Whether you were coding or writ

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3. Process vs. intuition

If you are searching for sequences instead of essences , you are doing that so that you can build up intuition in place of process .

In a pre-AI world, in order to build an application, you needed to reduce your idea to a process—a set of rules by which your software would operate to accomplish the goal you set. Sometimes this w

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1. Essences vs. sequences

In a pre-AI world, whether you were building software or teams, or writing books or marketing plans, you needed to strip the problems you were facing down to their bare elements—their essence—and work your way forward from there. In building software, you need to define your core user and the problem you want to solve; in writ

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2. Rules vs. patterns

Another way to think of essences versus sequences, especially when it comes to intellectual and creative tasks, is as a shift from the search for rules to a search for patterns .

In a pre-AI world, you needed to define the rules of the game you were playing—to think from first principles and apply them to your circumstances. In a p

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5. Explanations vs. predictions

The search for rules and essences, the obsession with process and sculpting, is ultimately a search for explanations . Explanations are the holy grail of the West—they are what we search for in science, business, and life. Consider the questions we tend to ask any successful person: “Can you explain how you got here? Wha

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Or maybe you’re running a creative team. In a pre-AI world, in order to create consistency, you needed to reduce your work down to principles and systems so that writers and designers could consistently capture your brand's voice and style.

In a post-AI world, you don't necessarily need to reduce your work in such a way. Instead, you can find exampl

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In a post-AI world, by contrast, you don’t need to explicitly define what a customer who is about to churn looks like, or which interventions you might use in which circumstances.

All you have to do is identify sequences that lead to churn. For every customer who churns, you can feed their last 100 days of user data into a classifier model that cate

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Instead, we're moving into Software 2.0 (a shift that Michael Taylor recently wrote about), where we describe a goal that we want to achieve and train a model to accomplish it. Rather than having a human write instructions for the computer to follow, training works by searching through a space of possible programs until we find one that works. In S

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In a pre-AI world, in order to build an application, you needed to reduce your idea to a process—a set of rules by which your software would operate to accomplish the goal you set. Sometimes this was easy; for example, a customer relationship manager like Salesforce is naturally reducible to rules.

In a post-AI world, you can build applications for ... See more