The problem you don’t know you have
Why X doesn’t work the way you think
Source: Pexels
Intro
This week I met with 5 combat reservists.
Each has done hundreds of days of reserve duty since October 7.
I volunteer in the MiluimTek program. We drink coffee and I listen. We talk about tomorrow.
We talk about finding their next job, their first job or how to build a startup that will solve a painful problem they personally experience.
3 out of the 5 serve in the same field intelligence unit, and 2 in armor. One wants to build a device to treat PTSD, one wants to build an app for pre-school teachers.
2 are looking for bioengineering jobs - practically non-existent now in Israel.
Last week, I promised you I’d walk through a real case where factual reasoning (with current data) was perfect but counterfactual blindness (to future paths) blocked the outcome.
Today, I’ll share the framework I use to stress-test personal, regulatory and commercial paths before they become irreversible.
Let’s get started.
Israeli bioengineering grads 2026
Biomedical engineering programs are built in universities and funded by governments. Programs that started 10-15 years ago. Long before AI and long before the wars between Russia and Ukraine, Israel and its near and far neighbors.
In April 2022, the IIA (Israeli Innovation Authority) committed $80M/year for the next 5 years to fund bioconvergence programs.
On 24 February 2022, Russia invaded Ukraine, Hamas attacked Israeli October 2022, and in November 2022; 6 months after the IIA bioconvergence budget was approved, ChatGPT was released, reaching 100 million users within 2 months.
The wars between Russia and Ukraine, between Israel, Hamas, Hezbollah, Yemen and Iran along with AI, shifted the Israeli tech industry demand for engineering talent far away from biomed to defense, cyber and AI.
How far?
2 orders of magnitude far.
In 2025 - the Israeli defense and cyber industries recorded $80BN in sales, the Israeli MedTech industry $3M and digital health $850M.
If you were a 2026 university graduate looking for a job in MedTech or digital health, your decision to study biomedical engineering in 2020 might seem irreversible after 258 days of combat reserve duty.
How to explore irreversible paths
This is where most of us struggle because we’re used to using factual reasoning.
Factual reasoning asks:
What does the data say right now?
Counterfactual reasoning asks:
What paths did we quietly close while making reasonable decisions under uncertainty?
Sometimes those paths close because of our own decisions.
Sometimes because of exogenous shocks like war or technology.
Counterfactual Reasoning explores what could be under different conditions - imagining alternative scenarios to understand causal relationships and hidden risks.
We can model careers, products, regulatory processes, and commercial strategies using causal flows — sequences of assumptions, decisions, and states that narrow future options over time.
Here’s what a simplified causal flow of a career path looks like:
What this is and what it isn’t
This is not a forecast, and it’s not career advice.
It’s a causal flow model of how reasonable decisions, made under uncertainty, can quietly eliminate future options.
The point isn’t that you chose incorrectly.
The point is that your original intent didn’t survive global and local change.
Threat paths don’t explain what went wrong after the fact. They explain how futures become unavailable long before outcomes are visible. Optionality doesn’t disappear in a moment — it collapses when accumulated commitments make counterfactual choices no longer viable.
The techniques you learned at BGU for 3D printing of biomaterial are less important than your ability to apply your skills, discipline, and lived experience to different problem domains — like pre-school, cybersecurity, defense, or complex systems engineering.
But even when your options seem limited, you have a powerful choice.
Make this powerful choice
When your career or company seems stuck, you have two options:
Do nothing
Build with the skills, life experiences and professional knowledge you already have
Option one leads you to burnout. To be angry. To be bored. To engage in mindless scrolling on social media at 11 PM.
Option two leads to a beautiful life. One where you solve other people’s problems. Where you become an inspiration. Where you start a movement. Where you create something new you can be proud of.
Whenever you’re stuck, label the feeling with either “I’m going to wait and see” or “I’m going to build.” I recommend building.
Final Thought
It sounds cliche as hell, but doing or building can either make you or destroy you.
No one tells us this because the attention economy profits from keeping you passive.
I don’t.
This week on Life Sciences Today Podcast
I had the pleasure of hosting Daniel Blumenthal, VP Strategy at MDClone, on the Life Sciences Today podcast to dig into what really matters in healthcare data now. MDClone started in 2016 as a synthetic data pioneer, turning privacy from a barrier into an enabler. But in 2025, with synthetic data and privacy-preserving analytics becoming crowded and partially commoditized, Danny argues the real frontier is data integrity: trusted, contextual, and action-ready data that actually improves patient outcomes.
We explored MDClone’s “nexus” position in the data supply chain—extracting longitudinal, privacy-protected patient data from messy clinical systems and generating different flavors of synthetic data for research, collaboration, and AI model development and validation.
Our conversation centered on strategic moats, partnerships with hyperscalers, and how health systems and pharma are waking up to the idea that their real IP is their clinical data—and that without data integrity, all the AI in the world won’t matter.
Visit MDClone here
You can see the episode here
About me
I’m a writer, host of Life Sciences Today podcast, ex-pharmatech founder, father of 4.
I’ve been building in tech, cyber, privacy, and clinical data for 25+ years across Israeli medical device startups, Verily, Amgen, and the Fortune 1 company. I work at the intersection of engineering, AI and clinical data.
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