When Technology Investment Loses Contact With Reality
Technology has never attracted more capital, nor carried more promise.
At the same time, many investors quietly share a similar experience. Investments that looked clear, coherent, and convincing at decision time often become slower, more expensive, and more fragile once execution begins.
This is not anecdotal. It is structural.
And it has less to do with bad ideas or bad actors than with how technology investment decisions are commonly made.
The rise of symbolic decision-making
Most early and growth-stage technology investments are decided through representations: pitch decks, narratives, road-maps, demos, and projections.
These tools are useful. They help align vision, explain opportunity, and compare options.
But they are, by nature, symbolic. They describe intent, not behavior. They communicate possibility, not constraint.
As long as technology is relatively simple, this abstraction works reasonably well. With High Performance Computing, AI systems, deep-tech stacks, hardware–software integration, and data-heavy platforms, the gap between description and reality widens significantly.
What looks coherent in slides can conceal:
- unresolved technical dependencies
- unrealistic performance assumptions
- execution bottlenecks
- hidden cost and time drivers
None of this is visible in a pitch.
Why this is not simply risk taking
It is often said that early technology investing is a “bet”. That framing is convenient, but incomplete.
Serious investing is not about eliminating uncertainty. It is about understanding which uncertainties are being taken, and which are avoidable.
Market risk is discussed extensively. Team risk is discussed extensively. Financial risk is modeled carefully.
Technical risk, however, is frequently deferred.
Not denied. Deferred.
The consequence is that some of the most expensive surprises appear only after capital has been committed, when correction becomes slow, political, and costly.
Industry analyses from organizations such as CB Insights and McKinsey consistently show that execution and technical realities are among the leading causes of technology investment under performance and failure [1] [2].
This points to a mismatch between how decisions are made and how products are actually built.
The missing layer in many investment processes
In most capital intensive industries such as infrastructure, energy, or manufacturing, capital is never deployed without early technical assessment by experienced practitioners.
Technology investing has largely escaped this discipline, despite becoming more complex and more capital intensive.
The result is not recklessness, but an over reliance on presentation quality and confidence as substitutes for feasibility.
This is not a call to abandon vision, speed, or conviction. It is a argument to re-balance them with earlier contact with technical reality.
Fields Notes on Investing in Technology
The Field Notes on Investing in Technology series is a practical attempt to document recurring patterns that appear once capital meets execution.
Each note focuses on a concrete aspect of this gap. Timelines that slip. Costs that rise. Products that drift away from their original promise. Strong teams struggling with hidden complexity.
Better questions asked earlier lead to better decisions later, for investors and founders alike.
A closing thought
Technology investing will always involve uncertainty.
The objective is not to remove it, but to understand where it comes from and which parts of it are avoidable.
Many of the most costly surprises are not random. They come from complexity that simply had not surfaced yet.
Recognizing that early is not pessimism. It is part of taking technology and capital seriously.
From NEXTWave Technologies SRL, providing independent technical insight for investors at the intersection of deep technology, product execution, and investment decision making.
References
[1] CB Insights. Startup failure analyses consistently identify execution and technical challenges among the top causes of failure.
[2] McKinsey. Multiple reports on AI and advanced technology initiatives show a majority fail to reach sustained production or expected business impact.