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'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.
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.
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.
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.
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.
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.
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.
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.
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.