Constants Into Variables
Find the assumptions everyone treats as fixed, watch which ones are becoming negotiable, and you have located the next decade's volatility.
- Difficulty
- Moderate
- Time to result
- ~months to results
- Steps
- 5
- Confidence
- 89%
Srinivasan's forecasting primitive is deceptively simple: look for things everyone treats as constant and identify which are becoming variable. His formal statement is that the biggest way to increase volatility is to take something with total consensus, where 100 percent of people agreed, and turn it into something only 80 or 70 or 60 or 50 percent agree on. When that happens, every assumption downstream changes. He uses a programmer's analogy: operating on the assumption that it is just the United States or just English versus coding your program to work in every country and language is an enormous difference. It can be done, but it is a rewrite. His worked examples span the deliberately uncomfortable and the technical. Two genders was an assumption in the 2000s that turned into a variable, and literally all kinds of back ends and databases had to get rewritten. The US dollar was not a variable before Bitcoin and now it is a huge one, no longer the thing you must reform but the thing you can exit from. Then geography, morality, and the nation itself. The pattern he predicts is that after the 2010s asked what is a currency, the 2020s will ask what is a nation, and everything that question touches becomes negotiable.
Origin
Srinivasan formalised this while writing The Network State, needing a way to explain why the 2020s feel structurally unstable rather than merely eventful, and connected it to Ray Dalio's observation that some trends run longer than any cycle a normal human lifespan can perceive.
Core principles
- 01The biggest single way to increase volatility is to take something 100 percent of people agreed on and turn it into something only 50 to 80 percent agree on.
- 02Constants are invisible precisely because you were born into a world where they had already been fixed.
- 03The 2010s asked what is a currency; the 2020s will ask what is a nation, and each such question converts a constant into a variable.
- 04Turning a constant into a variable forces every dependent system to be rewritten, exactly as internationalising software is a far bigger job than it looks.
- 05Digitisation mechanically introduces combinatorial complexity, since every previously singular option becomes a choice between physical, virtual, and a dozen apps.
- 06Both technological and political forces push in the same direction here, converting economic and social constants into variables simultaneously.
How to run it
- 1
Inventory your silent constants
Write out the things your plan, product, or thesis treats as background facts nobody would argue about. These are usually absent from any strategy document precisely because they are assumed.
Pro tip Ask what a program you built would hard-code rather than parameterise; that is the constant list.
Watch out You will miss the deepest constants on the first pass because you were born into them.
- 2
Score current consensus on each
For each constant, estimate what fraction of the relevant population still treats it as fixed. Movement from near-total agreement toward a split is the signal.
Pro tip Consensus dropping from 100 percent to 80 percent matters more than a shift from 60 to 50, because the first is a phase change.
Watch out Loud disagreement is not the same as broad disagreement; measure the distribution, not the volume.
- 3
Trace the rewrite cost
For each constant now trending toward variable, map what would need rebuilding: schemas, contracts, business models, institutions. This is where the actual disruption and the actual opportunity sit.
Pro tip The back ends and databases that had to be rewritten when gender became a variable are the canonical concrete case.
Watch out The rewrite is usually larger than it appears, since dependencies on a constant are rarely documented.
- 4
Look for the pattern in adjacent domains
Check whether the same conversion already happened in a neighbouring field, since the sequence tends to repeat. Currency going variable in the 2010s is his stated precedent for nation going variable in the 2020s.
Pro tip The domain that converted first also shows you the shape of the institutions that emerge afterwards.
Watch out The precedent gives you the shape, not the timing.
- 5
Build to operate under both states
Rather than betting on which value the new variable settles at, build so you function whichever way it resolves. This is the equivalent of internationalising rather than picking a second country.
Pro tip Optionality is cheapest to build before the constant has visibly moved.
Watch out Many variables never resolve, so plans that require settlement can wait indefinitely.
In the wild
Before Bitcoin, Srinivasan argues, essentially nobody treated the US dollar as a variable. Now it is a huge variable, something a significant fraction of people think about every day as something they can swap in or out of at some percentage. The change is not that the dollar weakened but that it stopped being the thing you must reform and became the thing you can exit from.
→ A single constant flipping produced an entire asset class, an industry, and a live policy debate at central bank level.
His softer illustration is everyday: a meeting used to be in person and now must be chosen as in person or virtual. A book is physical or digital. A conversation is a phone call or one of ten apps. The news was CBS, ABC, or NBC and is now an unbounded set. Each conversion multiplies the options and therefore the coordination cost.
→ The complaint about filter bubbles is really a complaint that there is now more than one, which is the visible symptom of constants becoming variables.
Common mistakes
Auditing only the variables you already argue about
Contested topics are already priced in. The disruptive conversions come from constants so settled that nobody has thought to list them, which is exactly why they are missing from the analysis.
Assuming a variable will resolve back to its old value
Once consensus breaks, the assumption typically stays contested rather than snapping back. Planning for restoration means planning for the least likely state.
Underestimating the rewrite
Srinivasan's programming analogy exists because people consistently underrate this. Making a system work across every country and language is not a feature, it is a rebuild, and the institutional equivalent is the same.
Is it for you?
Best for
Long-horizon strategists, founders, and investors trying to identify where genuine structural change will originate rather than tracking existing debates.
Not ideal for
Short-cycle operational decisions where the relevant constants will not move inside the decision horizon.
From the transcript
“variable and that is when we talked about earlier about volatility increasing the biggest way that you can increase volatility is you turn something that…”
“another example is the us dollar like before the before bitcoin no one really thought that that was a variable and now it is it's…”
“so these are things where there are extremely deep questions where you just didn't even have to think of them as variables because you're born…”
From the episode
#606: Balaji S. Srinivasan — 5-10-Year Predictions, How to Start a New Country, Society-as-a-Service (SaaS), Bitcoin Maximalism, Memetic Warfare, How Prices Are Born, Moral Flippenings, The One Commandment, and The Power of Missionary over Mercenary