The "Capital River" is a concept where one or two companies in a category gain unstoppable momentum. Once "in the river," they attract a disproportionate share of capital, top-tier talent, and high-quality customers, creating a powerful, self-reinforcing flywheel that helps them dominate.
Greylock's core ethos is to be a service-oriented firm that acts as a "supporting actor" to the founder, who is the star. This translates to a people-first, low-ego culture focused on being the founder's first call, rather than seeking press or marketing.
Before the internet, Greylock partners identified emerging companies by scanning classified ads in newspapers from various cities. Job postings signaled a hiring company, prompting partners to fly out and meet the founders in person, a process that could take months.
Greylock measures partner contribution by whether they were "causally impactful" to a successful investment, rather than just who sourced it. This model incentivizes deep collaboration, such as building a prepared mind, helping win a deal, or adding critical value post-investment.
To manage performance despite long feedback cycles, Greylock developed an "inputs-based" model. They assess partners on 18 specific actions, like seeing 75% of competitive deals, believing that consistently strong inputs are the best predictor of long-term success.
With high partner turnover at large venture firms, a key diligence question for founders is whether the specific partner joining their board is likely to remain at that firm. A partner's departure can be highly disruptive, making their stability more important than firm brand.
True alpha in venture capital is found at the extremes. It's either in being a "market maker" at the earliest stages by shaping a raw idea, or by writing massive, late-stage checks where few can compete. The competitive, crowded middle-stages offer less opportunity for outsized returns.
When initiating companies, Greylock targets opportunities with validated market demand but significant execution challenges. They bet that elite founders can solve hard technical or go-to-market problems, which in turn creates a strong competitive moat in an established market.
The current moment is ripe for building new horizontal software giants due to three converging paradigm shifts: a move to outcome-based pricing, AI completing end-to-end tasks as the new unit of value, and a shift from structured schemas to dynamic, unstructured data models.
While impressive, hypergrowth from zero to $100M+ ARR can be a red flag. The mechanics enabling such speed, like low-friction monthly subscriptions, often correlate with low switching costs, weak product depth, and poor long-term retention, resembling consumer apps more than enterprise SaaS.