What Comes After Selling Work

Key claims

• For every $1 businesses spend on software, they spend $6 on services — meaning the total addressable market for AI-native services (AINS) is approximately 6x larger than the market for AI-augmented software.
• America has followed a historical arc from agriculture to manufacturing to services economy, and AI is now eating the services layer — law, consulting, accounting, healthcare administration — the same way software ate earlier economic layers.
• Crosby, an AI-native legal services company, is 18 months in and has fine-tuned open-weight models on attorney redline acceptance data, building a proprietary feedback loop that gets better the more deals it touches — a data moat impossible for incumbents to replicate without changing their workflows.
• Incumbents are spending massively: Kirkland & Ellis is investing $500M in proprietary AI, McKinsey has built Lilli (its internal AI tool), EY spent $1.4B on EY.ai, and PwC is one of OpenAI’s largest enterprise customers — suggesting the services AI race is already underway at scale.
• AINS startups face two structural risks: incumbents already have the customers, the brand, and potentially more proprietary data; and services sales are relationship-based and slow, meaning even a technically superior product faces a long go-to-market cycle.
• The “Sell the Network” thesis: give the service away free, then monetize the network, transactions, or data underneath — the same logic Google used when it made search free because the network of commercial intent data was more valuable than charging for search.
• Rockwell’s free benefits concierge steers healthcare spend — the concierge becomes the engagement layer and the real business is the network of healthcare spend flowing beneath it; personal injury firms can give away free case management software and monetize by steering cases to vetted provider networks who pay for patient volume.
• Technological abundance rarely destroys value outright — it relocates value, revealing what was actually scarce all along, which is why AI eating services will make relationships, trust, and proprietary workflow data more valuable rather than less.

Notable quotes

“America has shifted from an agriculture economy, to a manufacturing economy, to a services economy; and now, AI is eating services.”

“If a service is the only thing you sell, you have to compete with incumbents who already possess the customers, the brand, and potentially even more proprietary data than you do.”

“The free concierge becomes the engagement layer; the real business is the network and healthcare spend flowing beneath it.”

“In the past, Google made search free because the network of commercial intent data was more valuable than search itself.”

“Services firms have always sold time, but what if time is no longer the only asset we have to sell?”

“Technological abundance rarely destroys value; rather, it relocates it, pointing out what was actually scarce all along.”

How it connects

• Rex Woodbury — author; investor at Daybreak Fund writing the Digital Native newsletter
• AI — the enabling technology that makes AI-native services possible and that is “eating services”
• SaaS — the prior model AINS is replacing or supplementing; the 6x services-vs-software ratio is the core argument against pure SaaS thinking
• Go-To-Market — the central strategic puzzle: “Sell the Network” is a GTM inversion, not just a product decision
• Google — the canonical example of the “give away the service, monetize the network” model (search was free, ad network was the business)
• Services Economy — the historical arc from agriculture → manufacturing → services → AI-eaten-services
• Data — proprietary workflow and transaction data as the durable moat AINS companies can build that incumbents cannot easily replicate
• Network Effects — the mechanism that makes the “Sell the Network” strategy defensible once scale is reached
• McKinsey — investing in Lilli, its internal AI, as an incumbent response to AINS threat
• Kirkland and Ellis — investing $500M in proprietary AI, the most aggressive incumbent response in legal