Guillermo Flor, founder of AI Market Fit and a VC and angel investor, has written extensively on how outcome pricing restructures the unit economics of service businesses: the deliverable shifts from “we send X emails per month” to “we build and run your outbound engine, optimized for qualified meetings,” with pricing moving from hourly retainers to performance-anchored packages in the $5,000 to $15,000 monthly range. When an agency uses AI to produce the work internally, marginal cost per unit collapses and revenue model can then be decoupled from headcount entirely.

Where the Outsourcing Already Exists

The Sequoia framework identifies a practical entry wedge: start where the work is already outsourced. If a task is handled externally, the budget line exists, the scope is defined, and the buyer is already purchasing an outcome. Replacing an outsourcing contract with an AI-native provider is a vendor swap. Replacing internal headcount is a restructuring. The former is a much lower-friction sale. Sequoia maps several verticals against an intelligence-to-judgement spectrum and an outsourced-to-insourced ratio. Insurance brokerage sits at $140 to $200 billion globally. Accounting and audit represents $50 to $80 billion in outsourced spend in the US alone, a market under supply pressure as the US has lost roughly 340,000 accountants over five years while demand has grown. Healthcare revenue cycle management, essentially the translation of clinical notes into billing codes, represents another $50 to $80 billion in outsourced, intelligence-heavy work.

These are markets where the work is well-defined, the outsourcing infrastructure already exists, and the gap between human unit cost and AI unit cost is now wide enough to sustain a new category of company. Distyl AI, which delivers AI-native solutions to Fortune 500 firms and ties pricing to measurable outcomes, raised $175 million at a $1.8 billion valuation in September 2025, led by Lightspeed Venture Partners and Khosla Ventures.

The Innovator’s Dilemma for Existing Tool Companies

The structural tension Sequoia identifies is real and already playing out. Copilots that sell to agencies, law firms, and accounting practices face a specific version of the innovator’s dilemma: if they shift to autopilot mode and begin delivering work directly, they cannibalize the customers who currently pay for their tools. This creates a window for new entrants with no legacy tool business to protect. The companies best positioned to become autopilots are those built as autopilots from day one, which is exactly what the YC Spring 2026 cohort is expected to contain. According to Crunchbase, AI startups captured 80% of global venture funding in Q1 2026, totaling $242 billion in the quarter. Within that figure, the concentration at the infrastructure layer, OpenAI, Anthropic, xAI, is masking what may be the more durable opportunity at the application layer, where the competition is not who builds the best model but who deploys AI to deliver the best outcome in a specific professional vertical.

What This Means for Investors and Founders

The investor implication is a revaluation of what a services company can be valued at. Traditional professional services firms are valued on EBITDA multiples constrained by the assumption that revenue scales with headcount. AI-native service firms break that assumption. If the marginal cost of delivering an additional contract review, insurance placement, or outbound meeting approaches zero, the margin profile resembles software even if the product is a service. Sequoia’s thesis is explicit: the next trillion-dollar company will be “a software company masquerading as a services firm.”

For founders, the practical question is whether to compete for the tool budget or the work budget. In most professional verticals, the work budget is larger by a factor of six. The founders who will define this category are not building another AI-powered workflow layer on top of existing agency operations. They are replacing the agency model entirely, starting with the tasks that are already outsourced, already priced on outcomes, and already subject to a buy-versus-build decision their customers make every year. The wedge is narrow but the TAM behind it is not.