The venture capital benchmark for elite growth has shifted for AI companies. The old "T2D3" (Triple, Triple, Double, Double, Double) heuristic for SaaS is no longer the gold standard. Investors now consider achieving $100M ARR in under three years as the strongest signal of exceptional product-market fit in AI.

SaaS valuations are under pressure. Growth has slowed from 30%+ to the low teens, while multiples remain high compared to faster-growing sectors like semiconductors. SaaS firms must leverage AI to reignite top-line growth or their valuations will inevitably compress to match their new reality.

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.

For established software companies with sluggish growth, the path forward is clear: find a way to become relevant in the age of AI. While they may not become the next Harvey, attaching to AI spend can boost growth from 15% to 25%, the difference between a viable public company and a sale to a private equity firm.

Unlike traditional SaaS, AI companies have significant variable costs for compute and tokens. This makes revenue a poor proxy for profitability, as their gross margins are fundamentally different from high-margin software businesses—a fact many investors miss.

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.

Counterintuitively, very high gross margins in a company pitching itself as "AI" can be a warning sign. It may indicate that users aren't engaging with the core, computationally expensive AI features. Lower margins can signal genuine, heavy usage of the core AI product.

The long-standing 'Rule of 40' (Revenue Growth % + EBITDA Margin %) is no longer ambitious enough. By leveraging AI for efficiency in coding, support, and sales, Vista sees enterprise software companies achieving a 'Rule of 70,' dramatically increasing profitability.

The traditional SaaS growth metric for top companies—reaching $1M, $3M, then $10M in annual recurring revenue—is outdated. For today's top-decile AI-native startups, the new expectation is an accelerated path of $1M, $10M, then $50M, reflecting the dramatically faster adoption cycles and larger market opportunities.