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.

Many AI coding agents are unprofitable because their business model is broken. They charge a fixed subscription fee but pay variable, per-token costs for model inference. This means their most engaged power users, who should be their best customers, are actually their biggest cost centers, leading to negative gross margins.

The compute-heavy nature of AI makes traditional 80%+ SaaS gross margins impossible. Companies should embrace lower margins as proof of user adoption and value delivery. This strategy mirrors the successful on-premise to cloud transition, which ultimately drove massive growth for companies like Microsoft.

Unlike in traditional SaaS, low gross margins in an AI company can be a positive indicator. They often reflect high inference costs, which directly correlates with strong user engagement with core AI features. High margins might suggest the AI is not the main product driver.

AI companies operate under the assumption that LLM prices will trend towards zero. This strategic bet means they intentionally de-prioritize heavy investment in cost optimization today, focusing instead on capturing the market and building features, confident that future, cheaper models will solve their margin problems for them.

In rapidly evolving AI markets, founders should prioritize user acquisition and market share over achieving positive unit economics. The core assumption is that underlying model costs will decrease exponentially, making current negative margins an acceptable short-term trade-off for long-term growth.

The traditional SaaS model—high R&D/sales costs, low COGS—is being inverted. AI makes building software cheap but running it expensive due to high inference costs (COGS). This threatens profitability, as companies now face high customer acquisition costs AND high costs of goods sold.

Unlike SaaS, where high gross margins are key, an AI company with very high margins likely isn't seeing significant use of its core AI features. Low margins signal that customers are actively using compute-intensive products, a positive early indicator.

Many AI startups prioritize growth, leading to unsustainable gross margins (below 15%) due to high compute costs. This is a ticking time bomb. Eventually, these companies must undertake a costly, time-consuming re-architecture to optimize for cost and build a viable business.