The Technology Boom-Slump Cycle
Track how investment booms build capacity before new supply destroys returns
- Difficulty
- Moderate
- Time to result
- ~ongoing to results
- Steps
- 6
- Confidence
- 98%
Professor Steve presents AI as an example of the boom-and-slump pattern associated in the transcript with Joseph Schumpeter. Banks and investors finance a promising technology, construction and hiring create a boom, and many providers pursue the same large prize. When the new capacity becomes operational, it undercuts existing businesses and exposes how much money was invested relative to sustainable revenue. Companies then fail or contract, but society may retain useful infrastructure, as it did after railway overbuilding. The model therefore tracks the capability, the financing wave, the capacity being built, the incumbents being displaced, and the economics after supply arrives. It supports scenario planning and valuation discipline, but it cannot establish the episode's predicted timing or severity of an AI-led downturn.
Origin
The episode attributes this pattern to economist Joseph Schumpeter; extracted from The Diary of a CEO.
Core principles
- 01A useful technology can still attract excessive investment
- 02Financing expands capacity before demand and profits are proven
- 03New capacity can undercut the businesses it replaces
- 04Failed investors can leave valuable infrastructure behind
- 05A forecast of a slump does not provide a reliable date
How to run it
- 1
Define the new capability
State what the technology now makes cheaper, faster, or possible. Keep this separate from claims about the companies financing it.
Pro tip Describe the customer outcome rather than the technology label.
Watch out A real capability does not guarantee attractive investment returns.
- 2
Map the financing wave
Estimate capital expenditure, fundraising, borrowing, and the number of entrants. Compare those inputs with current revenue and credible demand.
Pro tip Include spending by incumbents as well as startups.
Watch out The episode's spending figures are presented without source methodology.
- 3
Track capacity under construction
Identify the infrastructure, products, and labor being built before their utilization is known. Ask when that capacity will begin competing for the same customers.
Pro tip Record expected launch dates and replacement cycles.
- 4
Map the displacement
List the incumbent products, jobs, and business models the technology could undercut. Estimate who loses revenue when adoption grows.
Pro tip Include second-order effects such as reduced hiring or supplier demand.
Watch out Potential displacement is not proof that every listed role will disappear.
- 5
Stress-test post-launch economics
Model lower prices, duplicated capacity, slower demand, and failed providers once the technology is widely available. Test whether valuations survive those conditions.
Pro tip Include a case where the technology succeeds but most investors do not.
Watch out Do not turn the scenario into a certain crash date.
- 6
Separate survivors from infrastructure
Judge company survival and social usefulness independently. Failed firms may still leave assets or knowledge that benefit later users.
Pro tip Ask who can acquire stranded capacity cheaply after the slump.
In the wild
Professor Steve describes investors pouring money into railways, many railway companies failing, and society retaining the network afterward. The example separates losses borne by providers from the durable usefulness of what they built.
→ The technology changes society even though most early companies do not survive.
The episode cites very large planned AI infrastructure spending by major technology companies and contrasts it with current AI revenue. Professor Steve interprets that gap as evidence of overinvestment and predicts a later slump, while the exact figures and outcome remain claims in the conversation.
→ The model flags a need to test returns under slower demand and intense competition rather than treating the forecast as certain.
Common mistakes
Calling useful technology a safe investment
Social value and investor return can diverge when too much capital builds the same capacity.
Predicting an exact turning date
The cycle describes a mechanism, while the episode does not establish when financing or demand will reverse.
Ignoring the assets left behind
A company-level bust can still create cheap infrastructure and capabilities for later operators.
Is it for you?
Best for
It is best for investors, founders, and operators evaluating a heavily financed emerging technology.
Not ideal for
It is not a precise market-timing tool or proof that a particular company will fail.
From the transcript
“Some new technology will be developed like railways for example.”
“That investment produces a new technology which causes a boom”
“When the technology comes online it undercuts existing businesses and causes a slump.”
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