Through the keyhole: Where details drive success 

Many leaders have experienced this: a brilliant strategy that delivers disappointing results. The boardroom plan seemed perfect, the team aligned, but in the end, the execution failed. You might have found yourself wondering: "What happened?"

But what if the problem isn't your strategy, but the small details you dismissed?

Strategic alignment cascades through organizations, with details playing a critical role in translating vision into execution. Organizations thrive when "loosely coupled, tightly aligned," where confidence breeds autonomy while shared understanding ensures coordination.

Using Google Sheets' recent Gemini AI integration as an example, we'll see how seemingly minor implementation details can undermine strategic intent. Leaders must view details not as unimportant minutiae but as "keyholes" that reveal crucial insights into how strategy manifests in practice, particularly in the emerging era of LLM-powered products where traditional management approaches may fall short.

This quote from the novel Alice in Wonderland is a powerful analogy: strategy alone is not enough. Just as Alice finds a tiny golden key that initially seems useless, leaders must learn to recognize and value the small, easily overlooked details that unlock strategy in practice. These “tiny golden keys” often hold the difference between a bold vision and a realized outcome.

But in the real world, seeing and communicating those keys can quickly become convoluted. As strategy descends through the layers of the organizational chart, its interpretation naturally diverges. Each level filters the message through its own context, assumptions, and cognitive shortcuts. Some degree of wiggle among non-deterministic actors (each full of their own beliefs) is expected. But if misalignment is high in the hierarchy, the gap on the ground will drift out of tolerance. In other words, the "key" gets misplaced. This creates unproductive friction: heated debates that go nowhere. It’s not necessarily because people disagree—it’s because they’re no longer seeing the same door, or the same key.

To avoid these debates (and missed keys), organizations with high-level misalignment will postpone decisions as long as possible, they will lazy-load alignment. At best, this avoids unnecessary investments in decisions that never surface as urgent. At worst, this is the ostrich effect; execution slows, but we can't see how to fix it because we've taken ourselves out of the habit of seeing things through to their costly conclusions.

In this misaligned mode, we become tightly-coupled, but loosely-aligned. The former leads to lots of meetings due to dependencies, individuals aren't confident without guidance. The latter leads to destructive interference because we pull along different vectors.

We want to be loosely coupled and tightly aligned instead. This creates a state where confidence enables autonomy (fewer meetings), while a conservative interpretation of strategy creates constructive interference, positive contributions without constant direction.

One way for leaders to cultivate this autonomy is to monitor and reduce lossy transfers of knowledge. Rather than treat company communication like a telephone, where the speaker says it once and the listener has one chance to hear correctly, treat it as the two generals' problem, where both speaker and hearer benefit from being in the same room. This requires proactive outreach to ensure messages are received and understood as intended. While more expensive than broadcasts, these back-and-forths are the mental handshakes and checksums of remote communication, necessary to maintain strategy integrity as it gets disseminated across the organization.

As leaders whose words carry authority, we should watch for the words we use when encountering subjects outside our expertise. Because we've been trained to "not micro-manage" and "be strategic," our instinct is to surrender "the details" to "experts on the ground." But the judgments we imply will inevitably be wielded in battles that ensue out of our sight.

T-shaped individuals (generalists) at higher org levels are especially susceptible to this, as they are "good enough to be dangerous" in many areas. For speed, these generalists construct crude mental models of every realm: engineers write code; designers develop interfaces; baseball players swing bats. They're steeped enough to sweep a Jeopardy! category but know they lack understanding to be prescriptive, so they label the rest as "details."

This sounds like healthy delegation. Yet, how "details" get understood by listeners affects execution.

This sounds like a healthy delegation of concerns. And yet, how "details" are understood by listeners will affect how they execute:

• "Details" means these things are unimportant. If all we care about is outcomes, details don't matter as long as operators deliver. As leaders, we imply we don't care. This is problematic if the consequences are poorly understood. Anyone who has hired a contractor knows how ignored details prevent realizing true intent. "Where should this outlet go? Did the homeowner have a preference?" "No, just wherever."
• Details as minor concerns. When time is of the essence, we avoid wasting time on relatively unimportant details. This surfaces as someone interrupting healthy debate with an apple pie position—guaranteed to sound smart and squelch productive conversation. "Let's timebox this to one hour." "We should avoid being philosophical." "Why not both?" may undermine a strategy that hinges on not being both.
• Details as nuance. As we display greater curiosity, we appreciate that certain details matter more than expected. How a golfer shifts weight, how a surgeon washes hands, and choices baked into the data model—in each realm, these are not details but pivotal elements. As leaders, we should celebrate discovering these nuances and stress their importance. Doing them right means doing them in tune with our strategy.
• Details as keyholes. Leaders can treat details as clues that a much larger world lies behind them. Because knowledge is fractal, whatever we see as a small detail becomes large once we step into it. The challenge is to shrink ourselves—our egos, our assumptions—enough to enter through the keyhole. "How does the data get backed up?" "Why did you make this choice?" "What data does this assume the customer has?" We must embrace becoming "curiouser and curiouser."

In organizations that crave alignment, these piercing questions are awkward but catalyzing. They create confidence in leadership competence and provide accountability. They help teams see trade-offs that align with strategy, or don't.

There is one final key: we must follow through on getting answers. Without this, we risk becoming Socrates, up in the clouds, only spurring endless discussions. With this, we neither micro-manage nor abdicate responsibility; we show the way.

The world is full of examples where the details matter more than someone in management or leadership expected. To illustrate, let's look at a recent implementation of AI assistance inside a complex product: Google Sheets.

We start with the sensible strategy of using AI (Gemini) to aid and support a user: "How can I help you today?" We make it convenient, easy to discover, and personalize it: "Hello, Matthew."

Next, we generate a summary of the sheet: magic!

Now I want to use this to do something that's often vexed me as a user: create a chart. Prompt: "Can you create a chart that shows Contracted ARR by Country?"

Gemini finishes and outputs a gray box, which is a surprise. I was expecting a chart? I notice some microscopic text and realize these are country names. A pop-over tooltip tells me I should "Go Wide!" to stretch the Gemini sidebar to display the chart. I do, but the chart doesn't get much better.

As a user, I'm confused. This is not how any intelligent person would display this data. Oh well, at least I can "Insert" the chart into my sheet. It solved the zero-to-one problem; I'll take it from here.

I click, and the chart appears in the sheet! Awesome, I think; back on track. I click the ellipsis at the top-right to modify the chart, and I'm disturbed:

Oh no. This "chart" is an image. I can't use what Gemini did as a launch point after all. I have to start over. Since it's a static image, the AI assistant must create the perfect chart from my prompt, which means my prompt must articulate everything I want, which includes many things I don't normally think of expressing this way.

What started as a sound product strategy delivered a disappointing experience, even with Google's own AI. While impossible to know where things went "wrong," we can imagine "chart format" being relegated to an unimportant detail. "What do you mean, format? It's a chart." Faced with the choice of a difficult technical challenge or simply inserting an image, the team chose the latter.

How the conversation may have gone among well-meaning participants:

Manager: "We want to give the user superpowers with Gemini built into Sheets."

IC: "Great. What kind of superpowers?"

Manager: "Well, for example, we want to make it easier for them to get started."

IC: "Okay. What do we mean by getting started?"

Manager: "You know, automating the tedious, error-prone tasks. Like writing formulas or creating charts. Or summarizing the whole sheet for a co-worker."

IC: "Okay. Do they know what formulas and charts they want?"

Manager: "Sort of. Let's assume they do."

IC: "Great. So they describe those in a prompt, and Gemini makes them. What do they want to do with a chart once Gemini makes one?"

Manager: "Well, once Gemini makes the chart, they probably want to insert the chart, of course."

This is where 98% of timelines split. The IC assumes the manager couldn't mean investing in making Gemini talk to Sheets's Charts API—an idea shot down nine months ago. They settle: "An image will be fine for v1." The manager thinks the IC understood "inserting a chart"—functionality that's existed for years.

Both are confident they're executing strategy as intended. Unfortunately, both stopped shy of clarity on details that matter to customer experience.

Both would have benefited from probing questions: "Is our goal to automate fully, or get users from zero to something?" "Does the user want to take over and finish manually?" "How will users iterate if it's inside the LLM?" "What tools are available?" "Can it create native objects?" "Did we find a way around the API limitations?"

Seen through "details as nuance," chart format matters because it determines editability. Seen "as keyhole," format opens investment decisions on interoperability—whether to limit capabilities to existing widgets or expose new tools to Gemini, even if delaying six months.

One criticism: the strategy "aiding users with AI" is vague. A clearer statement like "aiding users from idea to first draft" would have provided guidance but excluded other AI uses.

With clearer statements, it becomes easier to ask if Gemini's output counts as "first draft"—presumably editable. These clear statements are rare because they require more leadership effort, feel restrictive, don't "leave details to the team," and appear to reduce market opportunities. So we produce broad statements instead. But these lofty ambitions fail to sharpen perspective on ideal customer experience, placing a greater burden on teams to interpret them. This increases overhead, errors, and scope, bogging down well-meaning squads.

Upper-level managers must understand how natural language interfaces attached to LLMs add novel pressure to this age-old need for details to be worked out in advance. Unlike old UIs, LLM capabilities and user expressions aren't constrained to deterministic layouts tied to predictable API calls. Worse, these abilities are essentially invisible, taking place in ephemeral chat that, unlike call trees or chatbots, cannot be scripted. Product management in the LLM era will require new curiosity to see strategy through, and managers must descend deeper than ever down the rabbit hole.