When evaluating AI companies, focus on customer love (gross retention) and efficient acquisition over gross margins. High margins are less critical initially, as the 99%+ decline in model input costs suggests a clear path to future profitability if the core product is sticky.

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 founders delay pricing discussions until Series A, but this is a mistake. Establishing a commercial model and value capture strategy from the pre-seed stage is crucial. If you don't charge appropriately from the start, you train your early customers to undervalue your product, making it harder to scale monetization later.

A service business's ability to consistently raise its prices is the single best indicator of its operational health. High pricing power signifies that the business has solved its core challenge of talent acquisition and training, creating more demand than it can supply.

For a true AI-native product, extremely high margins might indicate it isn't using enough AI, as inference has real costs. Founders should price for adoption, believing model costs will fall, and plan to build strong margins later through sophisticated, usage-based pricing tiers rather than optimizing prematurely.

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.

High margins create stability but also invite competition. The ideal strategy is to operate with margins low enough to build customer loyalty and a competitive moat, while retaining the *ability* to raise prices when necessary. This balances long-term growth with short-term financial resilience.

During major technology shifts like the move to cloud or AI, the best companies (e.g., hyperscalers, Snowflake) often have terrible early margins. In AI, inference costs are falling so rapidly that a company's margin profile can improve dramatically. Judging an early AI company on SaaS-era margin expectations is a mistake.

Ben Horowitz advised that pricing is the most critical decision for a company's valuation because it is the primary lever impacting both growth and margins. Founders often treat it glibly, but it deserves deep strategic thought as it underpins the entire business.