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In a dicey market, Oaktree prefers lending to "tech and truck" businesses with regional density. These companies are less risky than high-growth tech because they can't be displaced by software, have strong competitive moats in their local area, and grow via bolt-on acquisitions.

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Unsexy markets like plumbing or law have less competition, higher profit margins, and customers who are more receptive to expertise. This creates an environment for faster growth, akin to driving on an empty road.

Howard Marks attributes Oaktree's success to one core competency: predicting a company's probability of default better than the market. This micro-level, bottom-up analysis is the necessary condition for superior performance, allowing them to earn excess returns by identifying mispriced risk.

Unlike the asset-light software era dominated by venture equity, the current AI and defense tech cycle is asset-heavy, requiring massive capital for hardware and infrastructure. This fundamental shift makes private credit a necessary financing tool for growth companies, forcing a mental model change away from Silicon Valley's traditional debt aversion.

The greatest systemic threat from the booming private credit market isn't excessive leverage but its heavy concentration in technology companies. A significant drop in tech enterprise value multiples could trigger a widespread event, as tech constitutes roughly half of private credit portfolios.

Public markets favor asset-light models, creating a void for capital-intensive businesses. Private credit fills this gap with an "asset capture" model where they either receive high returns or seize valuable underlying assets upon default, securing a win either way.

In the current late-cycle, frothy environment, maintaining investment discipline is paramount. Oaktree, guided by Howard Marks' philosophy, is intentionally cautious and passing on the majority of deals presented. This discipline is crucial for avoiding the "worst deals done in the best of times" and preserving capital for future dislocations.

A significant portion of private credit is concentrated in software companies. Many of these loans were made when rates were low, often with high leverage and weak terms. The emergent threat of AI-driven disruption to their business models now adds a new layer of fundamental risk to this already vulnerable cohort.

Unlike venture capital, which relies on a few famous home runs, private equity success is built on a different model. It involves consistently executing "blocking and tackling" to achieve 3-4x returns on obscure industrial or service businesses that the public has never heard of.

Contrary to the "scale is everything" mantra, large private credit funds face diseconomies of scale. The pressure to deploy billions forces them to chase crowded, mainstream deals, leaving complex but lucrative niches like direct-origination ABL to smaller, more specialized firms that can manage the complexity.

New Mountain uses its PE team as a central analytical engine. If they lose a bid to acquire a company they've vetted, they leverage that deep knowledge to confidently provide debt to the winner, securing a safer position in a high-quality asset.