The physical inputs powering the AI buildout.

Concentrated long-only positions in uranium, critical minerals, renewable power, and energy infrastructure — the supply chains that every version of the AI buildout requires.

The Energy Thesis

Why Energy?

The energy transition and AI infrastructure buildout share a common dependency: physical commodities. Uranium, rare earths, copper, lithium, and natural gas are not optional inputs — they are structural bottlenecks that no technology roadmap can bypass. GZC’s Energy pool identifies the companies and operators that own or control these supply chain constraints.

The pool positions for multi-year cycles driven by three forces: geopolitical supply dynamics (rare earths, uranium), AI-driven demand (power, grid infrastructure), and structural under-investment creating supply gaps that are measured in years, not quarters.

Every position in the Energy pool originates from the same BTT framework: identify the physical constraint, validate the non-discretionary demand, confirm supply concentration, assess pricing power, and size with conviction. Energy assets are held for the duration of the forced-spend cycle — not for quarterly earnings beats.

Bottleneck Categories

Six structural themes. One framework.

Nuclear / Uranium

Domestic uranium producers at the intersection of nuclear energy renaissance and AI-driven power demand.

UUUUCCJ

Critical Minerals

Rare earth elements, lithium, and strategic minerals essential to EV drivetrains, batteries, and semiconductor manufacturing.

MPALB

Renewable Power

Renewable energy infrastructure contracted to hyperscalers for long-term clean power agreements.

BEPBE

Energy Infrastructure

Midstream pipelines and natural gas infrastructure providing the dispatchable baseload AI data centers require.

KMICOP

Grid Modernization

Utilities and power operators supplying the grid capacity required for large-scale data center interconnection.

ETRVST

Oil & Gas E&P

Disciplined producers with low break-even costs, durable cash flows, and shareholder return frameworks.

FANGCOP
Why This Pool

Three reasons the Energy pool matters.

01

AI infrastructure requires power at a scale that outstrips renewable capacity alone. Natural gas, nuclear, and uranium are non-discretionary inputs — data centers cannot run on intermittent solar and wind at hyperscale.

02

The Energy pool identifies supply chain bottlenecks in physical commodities — uranium supply constraints, rare earth geographic concentration, critical mineral processing chokepoints. The BTT framework applies directly: where is the forced spend, who controls the supply, and what is the pricing power?

03

Energy assets have long capital cycles and structural under-investment. A decade of ESG-driven capital withdrawal followed by AI-driven demand surge creates exactly the forced-spend dynamics GZC is built to identify and hold.

Pool Characteristics

How the Energy pool is managed.

Position Count Target
5–8 names
Typical Position Size
7%–15% of pool
Market Exposure
U.S. and Canadian public equities, long only
Rebalancing
Thesis-driven. Exits are driven by thesis invalidation, not calendar.
Benchmark
S&P 500 Total Return (for comparison only)
Custody
Interactive Brokers, LLC — client-owned SMA
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