Q1 2026 Performance Update: Roughing It in the AI Age

2026-04-17 · Source: Interconnected · Field: Finance & Economics — Capital Markets & Investment Management, Artificial Intelligence & Machine Learning, Economic Analysis & Policy · Depth: Intermediate, medium

Summary

Interconnected Capital's Q1 2026 performance update reports material outperformance in a down market for its global technology long-only fund. This success was largely driven by high-conviction positions established in 2024 and 2025, specifically in Nebius, Intel, and Ciena. The fund also capitalized on the rapidly growing demand for CPUs driven by agentic workloads, adding to Intel and initiating a position in Arm with its new Arm AGI CPU, anticipating a shift towards a 50:50 CPU:GPU ratio for agents from a 10:90 split for LLM training. Conversely, risk management using put options yielded flat results, and a foray into the SaaS market for AI guardrails resulted in a -2.45% loss, leading to the closure of all software exposure. The analyst notes enterprises are deploying probabilistic AI agents without complete guardrails, and market volatility in software is expected until Anthropic and OpenAI IPOs in 2026. Additionally, a new dashboard tracks data center moratoriums, revealing a faster-than-anticipated, bipartisan materialization of this risk across 44 US counties.

Key takeaway

For investors navigating the AI-driven market, prioritize hardware and "picks and shovels" plays, especially those benefiting from agentic CPU demand. Keep your software exposure minimal until major AI lab IPOs clarify valuations. Actively monitor data center moratoriums, as this bipartisan risk is materializing quickly and impacts infrastructure. Cultivate equanimity to manage the inherent market chaos.

Key insights

The AI age is characterized by rapid agentic AI deployment, market volatility, and infrastructure challenges, requiring adaptable investment strategies.

Principles

• Long-term conviction in "picks and shovels" drives performance.
• CPU demand for agentic AI is a significant tailwind.
• Market sentiment for software is highly reactive to AI advancements.

Method

The fund employs a long-only strategy focused on hardware and software "picks and shovels" of the AI economy, using geopolitical analysis and operator experience to assess company prospects. It also uses put options for risk management.

In practice

• Monitor CPU demand for agentic workloads.
• Avoid software exposure until AI IPOs clarify valuations.
• Track data center moratoriums for infrastructure risk.

Topics

• AI Investment Strategy
• Agentic AI Workloads
• CPU Market
• Data Center Moratoriums
• AI Guardrails
• Semiconductor Industry

Best for: VP of Engineering/Data, AI Architect, MLOps Engineer, Investor, Director of AI/ML, CTO

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Editorial summary, takeaway, and curation by AIssential. Original article published by Interconnected.