“It does not make any difference how beautiful your guess is.”
— Richard Feynman, The Character of Physical Law
Welcome to the Laboratory, where curiosity becomes experimentation, assumptions are challenged, and occasionally something explodes.
(Metaphorically, of course. Usually.)
I have a remarkable talent for coming up with ideas. Some are practical, some are unconventional, and some are so wonderfully strange that I can’t stop thinking about them. But I’ve learned a crucial lesson over the years: An interesting idea is not necessarily a good idea—and a good idea isn’t necessarily a useful one.
When a concept from Exploration demonstrates real promise, the question shifts from “I wonder?” to “How could we find out?”
That is when an idea enters the Laboratory. This is where we introduce raw imagination to that wonderfully inconvenient thing called reality. Sometimes they get along beautifully; sometimes reality has other plans. Either way, we learn something.
The WEIRD Methodology for Business Growth
To turn promising ideas into practical solutions without wasting time or money, I use a framework that brings together creative thinking, critical analysis, and rapid experimentation.
Naturally, I called it WEIRD. (Because I am apparently incapable of resisting a good acronym.)
Here is how we put ideas to the test:
- W — Wonder: Everything begins with deep empathy and understanding. Who are we trying to help, what frustrates them, and what assumptions are hiding the real root-cause problem? We resist the temptation to jump straight into solutions.
- E — Expand: We go wide. We generate conventional ideas, unconventional ones, borrowed concepts, and strange combinations. We avoid narrowing our thinking or judging ideas prematurely.
- I — Imagine: We get nonlinear. What if we removed a constraint? What if we combined two ideas that have never met? We connect unlikely concepts and explore what might actually be possible.
- R — Refine: We stop generating and start deciding. We select the most promising idea, identify the riskiest assumptions, and build a quick prototype or design a simple experiment to test our hypothesis.
- D — Distill: We examine the evidence. What worked? What collapsed under the weight of reality? We extract the insights and determine the next steps.
Failure Is Data. Assumptions Are Suspects. Reality Gets a Vote.
I don’t celebrate failure for its own sake, but I deeply appreciate it as an essential mechanism for learning.
When an experiment fails, it tells us that our assumptions were wrong, we misunderstood the problem, or the solution was too complicated. I would much rather discover a fatal flaw during a small, inexpensive experiment than after spending six months building an entire business around it.
In this lab, we test intelligently before we build extensively.
The Laboratory Rules
Every respectable mad scientist needs a few operating principles.
- Question Everything, Including Me: An idea doesn’t become correct simply because I came up with it. Bring evidence, ask difficult questions, and identify the weaknesses in the reasoning.
- Understand the Problem First: A brilliant solution to the wrong problem is still the wrong solution. We investigate before we invent.
- Keep Experiments Small: Identify the riskiest assumptions and find practical ways to test them quickly. Learn without creating unnecessary complexity.
- Evidence Outranks Enthusiasm: I reserve the right to love an idea while acknowledging that it doesn’t actually work. Customer behavior and credible evidence matter more than excitement.
- Be Willing to Change Your Mind: Refusing to adapt in the face of better evidence is a major liability. The objective is improved understanding, not defending yesterday’s conclusions.
- Know When to Stop: If an experiment has taught us everything it can, or if it has morphed into a distraction, we shut it down. No dramatic funeral required.
What’s Happening on the Benches?
The Laboratory isn’t organized around a single industry; it’s organized around the scientific method. As you browse this section, you will find projects categorized by their current status:
- Working Hypotheses: Emerging ideas that have an initial explanation, model, or proposed solution, but require more investigation before testing.
- Active Experiments: Projects undergoing practical, real-world testing. I might be evaluating a prototype, interviewing users, or testing a new framework.
- Under Refinement: The core concept works, but the delivery needs improvement, simplification, or systemization to become reliable.
- Experiments That Didn’t Survive: I don’t hide the failures. There is enormous value in documenting what we tried, why it broke, and what we learned to prevent someone else from making the same expensive mistake.
When a project survives refinement, proves its real-world utility, and demonstrates that it can reliably help other people, it graduates from the Laboratory and moves to the Marketplace.
Until then, grab some safety goggles and explore the active experiments.