I want to explore an idea that came to me mid-session recently, somewhere between asking a question and watching the answer arrive faster than I expected it to.
The question was this: is there a point of diminishing returns on imagining outcomes?
I don’t mean daydreaming. I mean the specific kind of forward thinking that happens when you’re planning a move, building a system, or working through a problem — the part where you’re running scenarios in your head before committing to anything real. Is more of that always better? Or does it eventually stop paying off?
I think there’s a law here that nobody has quite named yet. And I think AI changes where it kicks in.
The 60% Threshold
Here’s how I’ve been thinking about it. You don’t need to be right about an outcome to benefit from imagining it. You need to be right enough — maybe 60%, maybe a little more — to generate enough forward motion that the imagining was worth the time.
Below that threshold, you’re not planning. You’re guessing with extra steps.
Above it, something useful happens. You’ve built enough of a map that you can start moving without burning a lot of fuel on orientation. You’re not committed to the map being perfect. You’re just committed to not starting from zero every time you take a step.
We did this recently on a content project. I framed a challenge to my AI system — build me a directory where every table cell is a live link — without speccing it out, without a project plan, without a spreadsheet of URLs. I just had a clear enough picture of what the output should look like that I could describe it in one sentence and trust the execution would follow.
512 posts. 97 verified anchor links. 12 minutes.
The imagining phase was maybe 30 seconds. And it was enough. Because the base was set up. Because I trusted the system. Because I was at 60% and that turned out to be more than sufficient.
Where the Returns Start to Diminish
The problem with imagining is that it feels productive even when it isn’t adding anything anymore.
There’s a specific kind of planning session — you’ve been in one, I’ve been in many — where the first 20 minutes are genuinely generative and the next 40 minutes are just the group getting more comfortable with the plan they already made. The decisions were effectively done early. The rest was comfort-seeking dressed up as diligence.
That’s where the returns go negative. Not zero — negative. Because you’re not just failing to generate new value, you’re consuming time and attention that could be executing. Every extra hour in the imagining phase is an hour not in the feedback loop, and the feedback loop is where you find out what you actually got wrong.
The curve looks something like this in my head: steep positive returns early, flattening fast, crossing into negative somewhere around the point where you stop generating new information and start rehearsing conclusions you’ve already reached.
AI Compresses the Whole Curve
Here’s where it gets interesting for the way I work now.
When execution was expensive — when doing the thing took significant time, money, or coordination — it made sense to stay in the imagining phase longer. You were buying insurance against a costly mistake. The math favored more planning.
When execution gets cheap, that math changes. If I can test an idea in 12 minutes instead of 12 days, the cost of being wrong drops dramatically. Which means the value of being certain before I start also drops. I don’t need to imagine all the way to 90% confidence. 60% and a fast feedback loop beats 90% and a slow one almost every time.
But there’s a second thing AI does that’s subtler. It doesn’t just make execution cheaper. It makes imagination cheaper too. I can think out loud with a system that has real context, real knowledge of my setup, real understanding of what I’m trying to build — and it pushes back, fills gaps, surfaces problems I hadn’t considered. The imagining phase gets faster and more accurate at the same time.
So the whole curve compresses. The point where imagination stops adding value arrives sooner. The cost of testing arrives sooner too. The window between “good enough hypothesis” and “let’s find out” gets very small.
The discipline — and this is the part I’m still working on honestly — is recognizing when you’ve hit 60% and actually moving instead of imagining your way to 61.
The Wink
I’ll leave you with something to sit with.
This article is itself an exercise in imagined outcomes. I had a half-formed thought, I described it out loud, and the piece you’re reading now is what emerged from that description — shaped by something that knows how I think, knows what I care about, knows the vocabulary I use when I’m being honest rather than performative.
I wrote every word of this.
I also had help.
The readers who catch the wink will know exactly what I mean. And they’ll also know that catching it requires being the kind of person who already stepped back far enough to see the whole frame — which is, come to think of it, exactly what this piece is about.
The vantage point rewards the curious.
Frequently Asked Questions
What is the 60% threshold in planning and decision-making?
The 60% threshold is the point at which you have enough of a working hypothesis to generate productive forward motion. Below it, continued planning adds little new information. Above it, you have a sufficient map to start moving without burning excessive energy on orientation. The exact number varies by person and context but the principle is consistent: good enough to move is a real and reachable state.
When does imagining outcomes stop being useful?
Imagining outcomes stops being useful when you are no longer generating new information and have begun rehearsing conclusions you have already reached. The signal is when planning sessions feel like comfort-seeking rather than discovery — when the group is getting more comfortable with the plan rather than making it better. At that point, continued imagining is consuming time that should be spent in the feedback loop.
How does AI change the planning and execution curve?
AI compresses the entire curve in two ways. First, it makes execution cheaper, which reduces the cost of being wrong and therefore the value of extended planning. Second, it makes imagination faster and more accurate because you can think out loud with a system that has real context about your environment. The crossover point between useful planning and diminishing returns arrives sooner, and the window between hypothesis and test narrows dramatically.
What is the relationship between imagined outcomes and real results?
Imagined outcomes are hypotheses, not predictions. Their value is in giving you enough directional confidence to begin, not in being correct. The feedback loop — executing against the hypothesis and observing what actually happens — is where you find the truth. The imagining phase earns its keep by getting you to that feedback loop faster than starting from zero every time.
How do you know when to stop planning and start executing?
You are ready to stop planning when you can describe the desired outcome in a sentence or two, you have a sense of what good looks like, and continued planning is not producing new constraints or considerations. The 60% threshold is a useful mental check: am I materially more confident than I was an hour ago? If the answer is no, you have likely crossed into diminishing returns.
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