Low-Cost Option Portfolio
Increase your chances of discovery by trying more reversible options
- Difficulty
- Easy
- Time to result
- ~months to results
- Steps
- 5
- Confidence
- 96%
The Low-Cost Option Portfolio accepts that prediction is weak when outcomes depend on experience. Rather than concentrate on one supposedly best choice, increase the number of attempts while keeping each attempt inexpensive to enter and leave. Roberts uses Bill Belichick's reported habit of trading one draft choice for more lower selections: the coach may not know which player will succeed, but more picks create more chances to discover contributors. The same logic appears in index investing and venture capital, where a few successes can carry many failures. The essential safety condition is reversibility. Try many things only when unsuccessful options can be cut without unacceptable cost. Observe actual performance, retain what works, and let selection after exposure replace false confidence before it.
Origin
Roberts draws the method from a speculative interpretation of Bill Belichick's draft strategy and connects it to index funds, venture capital, and life experiments.
Core principles
- 01You often cannot identify winners before experiencing them
- 02More attempts increase the chance of finding a valuable outlier
- 03Reversibility keeps the cost of failed attempts tolerable
- 04Selection after experience can outperform prediction before experience
How to run it
- 1
Admit prediction limits
Estimate how reliably you can identify the winning option before trying it. Use the portfolio only when that confidence is genuinely low.
Pro tip Review previous confident predictions against their actual results.
Watch out Do not diversify merely to avoid choosing when strong evidence already identifies a winner.
- 2
Design small options
Create multiple attempts that expose you to real performance or lived experience. Each option must be large enough to teach something but small enough to remain affordable.
Pro tip Prefer direct trials over further speculation about what an experience will feel like.
Watch out A token trial that cannot reveal performance produces false learning.
- 3
Cap exit costs
Set the maximum money, time, obligation, and damage attached to each failed attempt. Remove options whose downside cannot be reversed safely.
Pro tip Define the stop condition before beginning.
Watch out Trying many high-cost options multiplies risk instead of creating useful optionality.
- 4
Increase the denominator
Run enough independent attempts to improve the chance that one or more will work. Avoid spending the entire budget polishing the first selection.
Pro tip Reserve capacity for later attempts before funding the first.
Watch out More attempts help only when each receives a fair test.
- 5
Select after exposure
Judge options by observed contribution or experience. Keep successful options, cut weak ones according to the stated rule, and reallocate resources toward what proves itself.
Pro tip Record why an option survived so the portfolio generates learning as well as winners.
Watch out Do not keep failures merely because the initial choice created attachment.
In the wild
Roberts speculates that Bill Belichick trades a draft choice for more choices later in the draft because he cannot predict every successful NFL player. More selections enlarge the pool from which actual contributors can emerge, including undrafted players other teams rejected.
→ The team gets more opportunities to discover useful players through performance rather than prediction alone.
A person uncertain about which kind of work will fit runs several bounded projects instead of making one permanent commitment from imagination. Each project has a small time budget and a clear exit, allowing real experience to reveal which work deserves continuation.
→ The person learns from direct exposure while limiting the cost of projects that do not fit.
Common mistakes
Making every attempt expensive
The strategy depends on low exit costs; otherwise multiplying attempts multiplies serious downside.
Pretending to know the winner
Concentrating resources based on weak prediction removes the discovery advantage of the portfolio.
Failing to cut weak options
The method requires selection after experience, not indefinite support for every experiment.
Is it for you?
Best for
Reversible experiments, auditions, investments, hires, projects, and experiences where several affordable attempts can be made.
Not ideal for
Irreversible choices or experiments whose entry, failure, or exit could cause severe harm.
From the transcript
“the bigger he makes the denominator he's going to get a few good players out of the whole thing he can't predict in advance who…”
“try lots of stuff”
“you want to be in a lot of things as long as they're not too high costs to get out of”
From the episode
#613: Russ Roberts on Lessons from F.A. Hayek and Nassim Taleb, Decision-Making Insights from Charles Darwin, The Dangers of Scientism, Wild Problems in Life and the Decisions That Define Us, Learnings from the Talmud, The Role of Prayer, and The Journey to Transcendence
Russ Roberts