How Compounding Breaks When Technology Resets Every Cycle
A guide for stock traders & VCs inspired by my career spent rebuilding on moving ground and adapting when the wind changes
Disclaimer: This publication and its authors are not licensed investment professionals. Nothing posted on this blog should be construed as investment advice. Do your own research.
The longer my career as a founder and engineer gets, the more one idea from The Psychology of Money keeps resurfacing: long-term success isn’t about brilliance, timing, or even hard work in isolation. It’s about staying in the game long enough for compounding to matter. That’s also a lot what I read about here on Substack.
Compounding is slow, boring, and deeply unfair in the short term. That’s why it works.
But the more years you spend inside technology - not just investing in it, but building on top of it - the clearer it becomes that tech is one of the most hostile environments for clean compounding.
Not because growth isn’t real, but because the rules reset far more often than our mental models assume.
Technology doesn’t compound, it overwrites
Most technological progress isn’t additive. It replaces what came before.
Desktop computing didn’t smoothly compound into mobile. Mobile shifted where value was created and erased entire categories of software businesses. On-prem infrastructure didn’t evolve gracefully into cloud services; it became stranded capital almost overnight. Traditional software isn’t slowly absorbing AI - it’s being repriced, re-scoped, and in some cases made irrelevant.
Each cycle quietly wipes out part of the previous advantage stack. Experience becomes table stakes and tooling turns into legacy debt. The Moats shrink into features and what once differentiated you becomes the minimum requirement just to stay in the conversation.
You don’t go back to zero, but you also don’t start from where your intuition tells you that you should. And that gap, between perceived leverage and actual leverage, is where compounding quietly dies.
I’ve lived this personally as a consultancy founder
Running an IT consultancy looks, on paper, like a textbook compounding business. Experience accumulates. Reputation spreads. Client relationships deepen. Every year should make the next one easier.
That’s the story. The lived reality is far less linear.
Every few years, the technical foundation underneath the business shifts. And when that happens, a meaningful portion of accumulated advantage simply loses relevance.
I’ve watched this play out repeatedly. From LAMP stacks to MERN. From server-rendered applications to API-driven frontends. From Magento-heavy projects to Shopify-centric ecosystems. From owning and tuning infrastructure to living entirely on managed platforms.
Each transition forces uncomfortable questions. Who do we hire now? What do we even sell? How do we price work when platforms abstract away complexity we used to bill for?
The business doesn’t reset to zero - but it absolutely does not compound smoothly. It feels more like climbing a staircase in poor lighting. You take steady steps for a while, then suddenly the geometry changes. Miss one transition and you don’t crash dramatically. You just stop ascending while others quietly move ahead.
That’s what broken compounding looks like from the inside in my opinion.
Public tech companies aren’t immune, they just hide it better
It’s tempting to believe this problem only applies to small and mid sized companies or agencies like mine. Public tech companies, we tell ourselves, are different. They have scale, capital, and optionality.
But even the best examples show how fragile compounding really is.
Microsoft didn’t smoothly compound from Windows dominance into cloud leadership. There was a long stretch where the company looked culturally and strategically stuck. Azure wasn’t an incremental extension, but it was a full reset that happened just in time.
IBM survived multiple computing eras, but survival isn’t the same as compounding. Its influence and growth flattened long before the narrative caught up, precisely because each platform shift diluted prior advantages.
Adobe is often held up as a compounding success story thanks to its subscription transition. And it deserves credit. But that transition wasn’t optional. Without it, decades of dominance would’ve turned into structural obsolescence very quickly (looking at you Sketch, Affinity and Figma).
Even companies often seen as perpetual compounders tell the same story under the surface. Amazon didn’t compound by staying still. It repeatedly rebuilt itself, using cash flow from one layer to finance reinvention in another. Meta rode social platforms to enormous scale, only to discover how fragile that compounding becomes when user behavior or platform paradigms shift.
From the outside, these stories look inevitable, but from the inside, they are a sequence of narrowly avoided dead ends.
Survivorship bias is brutal in technology
What we mostly see are the winners who crossed multiple resets. What we don’t see are the far more common outcomes.
Companies that didn’t fail loudly. They just stalled.
The product still works and the team is still competent. Revenue still grows a little, but margins compress. Hiring gets harder. Strategy becomes reactive instead of intentional. The company turns into a maintenance machine for decisions made in a previous cycle.
This is the most dangerous failure mode for founders because it doesn’t feel like failure. And it’s the most dangerous failure mode for investors because it looks like stability.
Compounding doesn’t always end with a crash. Often it ends with a long, quiet plateau.
AI doesn’t fix this - it accelerates it
There’s a seductive belief that AI finally restores compounding to software. Smarter tools, faster iteration, more leverage per person - what could go wrong?
Working with AI systems on a daily basis tells a different story.
AI dramatically lowers the cost of building, which is real progress. But it also dramatically shortens the half-life of advantage for anyone who doesn’t control their own economics. Many AI products grow quickly while sitting on top of models, infrastructure, and pricing decisions owned by someone else.
This looks familiar if you’ve lived through platform shifts
If you’ve been building long enough, AI wrapper economics should feel uncomfortably familiar.
Want to know what AI wrappers are? I’ve written another post about it: https://substack.com/home/post/p-182769365
It feels like businesses built entirely on social media APIs or mobile apps whose fate depended on App Store policy changes. Or SaaS products whose distribution vanished when a platform reprioritized its roadmap.
Those companies weren’t stupid. Many were well executed. Some even became case studies for a while. But when the platform shifted, past effort stopped compounding. Execution quality mattered less than position in the stack.
AI is replaying this pattern at a much faster pace, with far more capital and far less patience.
The real compounding question founders should ask
Re-reading The Psychology of Money pushed me to reframe the core question.
It’s not “how fast can this grow?”
It’s “what survives when the reset happens?”
What still compounds when the underlying platform changes? What advantage carries forward? And what quietly evaporates?
The companies that manage to compound across cycles aren’t the ones that avoid change. They’re the ones that can absorb it without destroying their economics. They own something fundamental enough that resets don’t erase their leverage.
Everyone else is compounding inside someone else’s system, on borrowed time, under assumptions they don’t control.
A more honest model of tech compounding
Compounding in technology isn’t a smooth exponential curve. It’s a staircase.
You accumulate quietly for years, then hit sharp transitions where the rules change. Some founders step up. Some slip. Some realize, too late, that the staircase moved while they were still climbing the previous step.
As a founder, this means staying paranoid about relevance even when things are going well. Comfort is often a lagging indicator of decay. As an investor, it means distrusting stories that project yesterday’s advantage too cleanly into tomorrow.
Compounding still matters. But in technology, it only belongs to those who survive and that group is far smaller than the success stories make it seem.
What this means for investing in tech companies
This compounding problem doesn’t stop at founders. It leaks directly into how tech gets funded - and why so much capital underperforms expectations across cycles.
For VCs, the core mistake is often assuming that early traction plus a big market automatically implies a long compounding runway. In reality, a lot of venture-scale outcomes are really bets on timing a cycle, not owning a durable advantage.
Many startups look like compounders only because the platform underneath them is still stable. When that platform shifts - cloud primitives change, distribution moves, AI pricing resets - the fund isn’t underwriting growth anymore. It’s underwriting the company’s ability to survive a reset it doesn’t control.
This is why so many VC portfolios end up with a strange shape: a few extreme winners that managed to align with or control a platform transition, and a long tail of companies that never quite die but also never deliver venture returns. They didn’t fail at execution. They failed at carrying leverage across cycles.
For public market investors, the problem shows up differently but just as painfully.
Public tech investing is full of implicit compounding assumptions. Revenue growth gets extrapolated. Margins are modeled as improving over time. Moats are assumed to widen with scale. But in technology, scale often increases exposure to resets instead of protecting against them.
A SaaS company compounding at 30% looks amazing, until a platform change turns pricing power into a negotiation. An AI-heavy product looks defensible, until inference costs or model access terms change. Suddenly the long-term margin story that justified the multiple doesn’t exist anymore.
This is why so many tech stocks don’t collapse, they just de-rate. Growth slows a bit. Margins disappoint slightly. Guidance gets conservative. The stock goes sideways for years while investors wait for compounding that never really resumes.
The uncomfortable truth is that many tech investments aren’t long-term compounding bets at all. They’re cycle bets disguised as forever businesses.
The investors who tend to do better over long horizons are usually asking different questions. Not “how big can this get?” but “what does this company still control after the next reset?” Not “is this growing fast?” but “where does the cost curve live, and who owns it?”
Because in technology, returns don’t accrue to the companies that grow the fastest inside a cycle. They accrue to the ones that still matter when the cycle ends.
And that’s a much rarer and much harder thing to underwrite.
Closing thoughts
The biggest mistake we make with technology, whether as founders, operators, or investors, is assuming that time automatically works in our favor.
In many industries, it does. Experience stacks. Advantages harden. Compounding feels almost mechanical. In technology, time is far more conditional. It only helps if you are aligned with where the system is going next, not where it has already been.
Building in tech means repeatedly letting go of things that once worked. Investing in tech means accepting that many “great” businesses are only great within the boundaries of a specific cycle. When those boundaries move, the compounding story often breaks long before the narrative does.
The uncomfortable reality is that technology rewards adaptability more than consistency, and positioning more than effort. That doesn’t make compounding impossible, but it does make it rare, fragile, and uneven.
If there is a single mental shift worth making, it is this: stop asking whether something is a good business today. Start asking whether its advantages survive a reset it does not control.
Because in technology, the future rarely belongs to the best operators of the current system. It belongs to the ones who are still standing, and still relevant, after the system forgets its own past.