Holmes in Everyday Life (1)

Sherlockian Way of Thinking

1. Reasoning is not a detective’s trick but life skill

Sherlock Holmes’s reasoning is not a rarefied talent fit only for the world of detective fiction. His sharp eye and disciplined logic are practical tools for navigating today’s complex society. We judge and decide constantly—about someone’s words and actions, a story in the news, a meeting at work, a conversation with a friend. Every such moment is a “small deduction.”

Holmes did not succeed through cleverness alone. He refused to be swayed by feeling and adhered to a stable architecture of thought: separating observed facts, finding rules, positing hypotheses, pruning away needless possibilities, and arriving at the most natural, persuasive conclusion. This sequence is what we call “Holmes’s methods of reasoning.”

As we have seen, these methods bear a striking resemblance to the operation of today’s generative AI. An AI does not speak because it “knows” the answer; it predicts and composes the most probable result given context and conditions. Well-designed questions—language that encodes a structure of thought—produce more precise and useful outputs. In that sense, a prompt is not only a request to a machine, but also a device for training our own thinking.

Many people, however, do not practice such structure. Before uncertainty, they lean on hunches or memory; they reach for outcomes without forming hypotheses; they notice repeating patterns yet miss the causes. Bias outruns logic; instinct outruns inference. This is less a failure of intelligence than a lack of training.

In this chapter, we examine how Holmes’s six methods—deduction, induction, hypothetico-deductive reasoning, abduction, retroduction, and the method of elimination—apply to everyday scenes. Hear a contradictory claim? Try deduction. Scan recurring items in the news? Organize them inductively. Facing uncertainty? Form a hypothesis and test it. In emotionally tangled conflicts, use abduction to elicit the most natural explanation; when the result is already on the table, use retroduction to reconstruct the path that produced it. And when choices are too many, do as Holmes did: eliminate the impossible until the best remaining option stands.

Finally, we will carry these methods beyond “thinking frameworks” and turn them into a habit of asking ourselves questions—even without a prompt. Those who write precise prompts handle AI better; those who can pose precise questions to themselves think more clearly and decide more deeply.

We will treat Holmes’s reasoning not as play-acting at detection but as a craft for living—practiced daily, one well-designed question at a time. A prompt, in the end, is less about writing than about the habit of thought. Like Holmes, think quietly, ask steadily, and move closer to the truth.

2. How to Use Each Method in Daily Situations

Holmes’s methods are not only for dramatic cases. They are frameworks for arriving at clearer, sounder decisions amid the frictions and choices of ordinary life. Below, we explore how to apply each method to concrete scenes.

A. Deduction: Exposing contradiction in a meeting

1) Definition:

Deduction begins with general principles or stated conditions and draws specific conclusions. We trace the logic of “If A holds, then B must follow,” testing the soundness of claims and decisions.

2) Scene:

In a team meeting, a colleague says: “Customer satisfaction is our top priority, so we can afford to delay the launch this time.” Earlier, the same person insisted: “This project must be finished within the month.”

Connect the two: If customer satisfaction is paramount and customers prize completeness, then a delay can be justified. But if non-negotiable launch this month is also demanded, the two positions collide.

3) Practical cues:

Use deduction to check consistency between claims and the actions they entail.

Continually ask, “If this logic holds, what must follow?”

By following the flow, you expose the gap between rhetorical claims and feasible behavior.

B. Induction: Seeing the “flow” in the news

1) Definition:

Induction gathers particular cases or data and, by spotting repetition, derives general tendencies or patterns.

2) Scene:

Scan a month of headlines:

“Bank X posts a second straight quarter of declining earnings.”

“Twenty-somethings increasingly favor investing over saving.”

“Fintech micro-loans grow 30%.”

Taken together, these fragments sketch a flow: funds squeezed out of traditional finance appear to be shifting into digital micro-investment and alternative lending

3) Practical cues:

Don’t react to isolated facts; track repeating keywords and connecting context.

Ask, “If this pattern persists, where does it lead next?”