30 Execution Lessons Learned
from 100+ Deep Tech Founders and Investors.
✨ This is the Premium Edition of The Scenarionist. Unlock the full experience by becoming a Premium Member!
The Scenarionist Premium is designed to make you a better Deep Tech Founder, Investor, and Operator. Premium members gain exclusive access to unique insights, analysis, and masterclasses with the wisdom of the world’s leading Deep Tech thought leaders. Invest in yourself, and upgrade today!
Dear Friends,
When I co-founded The Scenarionist, the ambition was simple, even if the execution was not: to build the best collective-intelligence layer in Deep Tech — a place where founders, investors, operators, and domain experts could help surface what actually matters across sectors, geographies, and company stages.
And the reason I know it is working is not just because the network keeps growing. It is because I keep learning.
Every week, through public conversations on Deep Tech Catalyst and through many other smart conversation with founders, investors, and operators from around the world, I get exposed to the same thing from different angles: how hard it is to separate what is merely interesting in Deep Tech from what is actually repeatable, useful, and real.
That has become a bit of an obsession of mine.
I spend a lot of time trying to understand what really holds across industrial sectors, across technologies, across markets, and across geographies. What is just local noise. What is sector-specific. What is timing. What is luck. And what keeps showing up often enough that it starts to look less like opinion and more like pattern.
Over time, some of those patterns begin to converge.
A few ideas keep reappearing.
A few mistakes keep repeating.
A few forms of discipline keep separating companies that look impressive from companies that actually endure.
That is what pushed me to write this piece.
These are 30 execution lessons I have been collecting, testing, and refining over time — first of all because I wanted to sharpen my own understanding of Deep Tech, and then because I realized they might be useful to others building in the same reality.
The result is not a definitive map of Deep Tech.
But it is a condensed one.
And, I hope, a useful one.
If you build, back, or study Deep Tech, I think these lessons will sharpen your lens — and maybe save you from learning a few of them the expensive way.
Lesson 1
Strategy is defined by what you decline.
Execution improves when founders say “no” to the wrong opportunities.
Every “yes” has a hidden cost, every refusal preserves focus.
The weak founder confuses movement with progress and calls every opportunity “strategic.” The disciplined founder understands a harsher truth: each distraction steals force from the main campaign. Markets are not won by appetite alone, but by restraint. What you decline determines whether your company remains sharp enough to matter.
Lesson 2
Retrofit can be the best beachhead.
Upgrading existing systems is often a faster way into the market than asking customers to rebuild around you from scratch.
Many industrial customers will not embrace full replacement on day one, even when the long-term case is compelling. But they may adopt an upgrade that fits into existing workflows, equipment, and approval processes. Retrofit strategies often create the first wedge that makes broader adoption possible later.
Lesson 3
Know whether you scale through volume or replication.
Not every industrial company scales by building bigger. Some scale by building more units in more places.
One of the most important scale-up questions is architectural: do you need massive jumps in capacity, or repeated deployment of smaller systems across multiple sites? Those two paths create very different demands on manufacturing, logistics, capital, partnerships, and speed. Scaling looks very different depending on which game you are actually playing.