The current rideshare market represents less than 1% of total vehicle miles. Autonomous vehicles will cause market expansion by at least an order of magnitude by eventually offering a service that is meaningfully cheaper than driving a personal car, shifting consumer behavior on a mass scale.
The scale of venture capital returns is escalating rapidly. According to a16z, the value of a top 1% outcome doubles every five years—from under $1.5 billion in 2009 to $10 billion today. This trend projects a top-tier outcome to be worth $40 billion within a decade, justifying larger fund sizes.
Waymo's primary growth constraint is the number of cars it can deploy, not customer demand. In San Francisco, it rapidly achieved 25% market share with a limited fleet. This suggests its market penetration is a direct function of its ability to scale its physical infrastructure across new cities.
In hyper-growth AI companies with annual contracts, renewal data is a lagging indicator. VCs scrutinize user engagement as the most critical leading indicator of future retention, as a large part of the customer base has not yet faced a renewal cycle.
a16z's growth team operates on a principle from the film *Glengarry Glen Ross*: market leaders capture a disproportionate share of value. This 'winner-take-all' mentality drives their focus on backing only the number one player, avoiding the distant second.
Prediction market Kalshi adopted a "regulatory-first" approach, similar to Coinbase. This difficult path built essential trust, directly enabling partnerships with Robinhood, Coinbase, and CNN, demonstrating how compliance can be a powerful moat and business development tool.
An a16z partner highlights a major disconnect where fewer than five public software companies are growing over 30%, while private AI giants like OpenAI and Anthropic are adding massive revenue, shifting the growth focus to private ventures.
a16z isn't deterred by AI companies' 0-50% gross margins, a stark contrast to the usual 70% software benchmark. They accept these margins if they stem from LLM costs, focusing instead on whether the company is building defensible value through unique data, workflows, and integrations.