In a recent conversation hosted on the Sequoia Capital YouTube channel, Sierra co-founder Bret Taylor—best known for his leadership roles at Google Maps, Facebook, Salesforce, and OpenAI—laid out a compelling case for why AI isn’t just changing how software is built, but how it’s priced, sold, and consumed. Joined by Sequoia partner Ravi Gupta, Taylor shared sharp insights into the transformation underway in enterprise software as AI shifts the center of gravity from subscriptions to outcomes. This is more than just a tech trend—it's a seismic business model reset.
Taylor argues that the rise of AI agents marks the beginning of a new era in software: one where customers no longer pay for access or seats, but for real, measurable results. At Sierra, their pricing reflects this shift. Rather than charging per seat or via subscription, Sierra charges only when its AI agent successfully resolves a customer issue. If the agent escalates the issue to a human, it’s free.
“Salespeople get paid on commission. Why shouldn’t AI?”
This model, Taylor suggests, is a natural evolution of software economics—from boxed software to SaaS, and now to performance-aligned agents. The message to founders? Build for impact, and price for outcomes.
One of Taylor’s core messages to entrepreneurs is that incumbents will struggle to adapt. Not due to lack of talent or technology—but because of legacy business models and shareholder expectations. Public companies, he says, are often punished for short-term revenue dips even if they’re investing in long-term transformation.
“Startups aren’t encumbered by legacy pricing models. That’s your advantage—use it.”
He draws parallels to past transitions, like Microsoft’s painful (but eventually successful) move to Azure, and Adobe’s shift to subscriptions. Most companies couldn’t pull it off—and were outpaced by startups who embraced new business models from day one.
Taylor believes that just as websites once became the main digital presence for brands, AI agents will soon become the default interface for customer interaction. This isn’t about generic chatbots—it’s about deeply integrated, branded agents that represent the entire customer experience.
Sierra is already powering such agents for companies like ADT and SiriusXM. For Taylor, the AI agent is not just a tool—it’s the next-generation digital storefront, contact center, and brand touchpoint all rolled into one.
Taylor is deeply skeptical of horizontal AI platforms, especially in enterprise software. Instead, he advocates for vertical specialization—building agents that deeply understand the workflows, language, and pain points of specific industries.
“Insurance, telecom, healthcare—all need agents that understand them.”
The key is speed-to-value. A vertically specialized agent can deliver ROI faster, making it easier to sell, integrate, and scale.
Taylor distinguishes between cost-saving agents (automating existing workflows) and revenue-driving agents (creating new business opportunities). While both are valid, he argues that AI’s long-term impact will be judged by its ability to generate top-line growth—not just cut costs.
“Cost savings are a temporary drug. The real opportunity is in driving growth.”
He also highlights the nuances of enterprise sales: procurement cycles, budgeting quirks, and department-specific constraints (e.g., HR prefers fixed costs over usage-based pricing). AI entrepreneurs need to deeply understand their buyer's world—not just pitch a demo.
Taylor outlines three distinct AI markets:
The conversation closes with a reminder that the AI wave mirrors past tech booms. Ideas are plentiful. Execution is what matters.
“It’s like the dotcom era. Everyone had the same idea—search, e-commerce, payments. But only a few executed their way to dominance.”
The winners in this AI era will be those who solve real problems, deliver measurable value, and design business models that match the new shape of software.
Outcome-based AI isn't just a pricing strategy—it’s a new philosophy of value.
Founders who lean into this shift, specialize vertically, and speak their customers' language will be best positioned to lead the next generation of enterprise software.
