Monday Memo

A Byte of Knowledge

You start a new project by opening an AI chat and describing what you want.

The plan feels whole in your head, so the description comes out thinner than you think, light on every detail you assumed was obvious.

Psychologists call that gap the illusion of explanatory depth: we feel we grasp our own idea until we have to spell it out, and the holes only show then.

The model can't see those holes either, so it fills them by guessing and builds in a direction you never meant.

So flip it.

Before the model writes anything, have it interview you, one question at a time.

Each question is easy to answer, and each answer drags one of those hidden pieces into the open.

By the last one you hold a brief you could never have written from a cold prompt, and the model finally builds what you actually meant.

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(Plus… They Don't Get Sick, Miss Deadlines, Or Ask For Raises Either!)

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Something to Ponder

We Asked – AI Answered

Our Question: 

"In the age of AI and seemingly endless opportunity with almost Godlike technology at our fingertips, what is the single best piece of advice you have on avoiding ‘Shiny Object Syndrome.’"

AI's Answer: The One-Constraint Rule - Make Every Shiny Object Earn Its Keep 🔒

The single best advice: Choose one measurable business constraint for each 90-day cycle. Reject every new tool, channel, offer, or AI workflow unless it can materially improve that constraint through a small, time-boxed test.

Shiny Object Syndrome is resource misallocation wearing an innovation costume. AI lets you manufacture options faster than your company can validate, train, implement, and operationalize them. Your scarce assets remain owner attention, cash, customer trust, and follow-through.

🧠 Why Even the Smartest of Us Still Get Seduced

• Unfinished work follows you. Sophie Leroy’s two experiments found that attention remains stuck on a previous task, especially an unfinished one, and performance on the next task suffers. Every half-built automation, abandoned funnel, and “quick” platform migration leaves cognitive residue.
• A committed focal goal suppresses alternatives. Shah, Friedman, and Kruglanski found this “goal shielding” effect across six studies. A precise goal helps your mind ignore competing routes, including attractive routes promising the same broad outcome.
• Exploration consumes the same scarce resources as execution. Stanford scholar James March’s classic model showed that organizations must allocate resources between exploring new possibilities and exploiting proven capabilities; either extreme carries long-term costs.

🧱 Install a Constraint Gate

Write one sentence where the whole team can see it:

For the next 90 days, our binding constraint is ______. We measure it with ______. Success means moving from ______ to ______ by ______.

Good constraints sit close to money: qualified pipeline, sales conversion, fulfillment capacity, or customer retention.

Every shiny object must pass four gates:

1. Directness: It attacks the declared constraint within this cycle.
2. Evidence: Customer behavior, internal data, or a credible test supports the hypothesis.
3. Full cost: You count software, setup, training, migration, maintenance, and executive distraction.
4. Kill rule: You define the budget, deadline, sample size, and failure threshold before starting.

🧮 Use This Heuristic

Priority score = (expected constraint impact × confidence) ÷ total cost and disruption

This formula will never deliver scientific precision. It forces comparable thinking. If the new idea scores below the current plan, place it in an “Opportunity Vault” and review it once per quarter. Stop reopening the decision every morning.

🎯 Turn Discipline Into an Automatic Response

Create an if-then rule:

If a new AI tool or opportunity appears, then I will score it against our current constraint and wait until the scheduled review before committing resources.

A meta-analysis covering 94 independent tests found that these “implementation intentions” improved goal attainment with a medium-to-large effect, d = .65. Specific rules outperform vague promises to “stay focused.”

💼 What This Looks Like in Practice

Suppose your constraint is demo-to-close rate. A personalized AI proposal-video tool earns a test only with a defined hypothesis: “Twenty proposals, six staff hours, $300 maximum, continue if close rate improves by at least five percentage points.” An AI chatbot intended vaguely to “build the brand” waits in the vault.

Reserve a fixed exploration budget, perhaps 10% of available experimentation time, so curiosity gets oxygen without commandeering operations. Review the vault quarterly, promote one contender, and keep executing.

In an age of infinite possibility, your advantage comes from treating attention like capital and forcing every opportunity to earn a return.

Thanks for reading the Monday Memo.

Until next time!

The AI Marketers

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