To accelerate AI adoption in large, slow-moving enterprises, startups are reviving the 'forward deployed engineer' model. By embedding their own engineers within customer organizations to build and implement solutions, they overcome internal inertia and talent gaps, dramatically shortening sales and deployment cycles for complex AI products.

The rise of Forward Deployed Engineers (FDEs) at OpenAI and Google isn't just about a new job title. It's a strategic Trojan horse to bypass traditional consulting firms and directly capture the massive services revenue associated with AI implementation, shifting from software sales to outcome-based pricing.

As AI moves from co-pilot to autopilot, companies can sell outcomes directly, not just tools. This creates an opportunity to build a "software company that masquerades as a service business," capturing the much larger services budget (a 6:1 ratio to software) while maintaining software-like margins by leveraging AI.

Borrowing from Palantir, Sierra embeds its engineers directly within customer organizations. This "Forward-Deployed" model accelerates time-to-value for complex AI implementations, enabling launches with major enterprises like Cigna in under two months by becoming a true implementation partner.

The dominant per-user-per-month SaaS business model is becoming obsolete for AI-native companies. The new standard is consumption or outcome-based pricing. Customers will pay for the specific task an AI completes or the value it generates, not for a seat license, fundamentally changing how software is sold.

The business model is shifting from selling software to selling outcomes. Instead of creating a tool and inviting users, create pre-trained agents that perform valuable work. Then, invite companies to a workspace where this 'team' of AI employees is ready to start delivering value immediately.

Instead of selling software, Long Lake acquires companies to implement its AI platform. This ownership model creates a tight feedback loop between engineers and employees (the end-users), ensuring better change management, faster innovation, and superior business outcomes compared to a traditional vendor relationship.

The high-margin, pure Software-as-a-Service model is becoming obsolete in the AI era. Complex AI implementation requires hands-on integration, giving rise to consultative models like the "forward deployed engineer," where provider experts are embedded with clients to ensure success.

The most profitable way to leverage AI tools without code is to package their output as a managed service. Instead of selling access to an AI, sell lead generation, process automation, or financial analysis on a monthly retainer, with the AI doing the heavy lifting behind the scenes.