Previously, compute and data were the limiting factors in AI development. Now, the challenge is scaling the generation of high-quality, human-expert data needed to train frontier models for complex cognitive tasks that go beyond simply processing the public internet.
The matrix consists of industry, function, role, and workflow. Turing's CEO posits that mastering four key capabilities—multimodality, reasoning, tool use, and coding—is sufficient to automate any task within this vast economic landscape, providing a structured framework for tackling AGI.
Instead of interacting with SaaS GUIs (like Greenhouse for hiring), users will interact with AI agents. These agents will directly manipulate the underlying system-of-record data, managing entire workflows from a simple conversation and making the traditional SaaS application redundant.
Countering the "get out of the way" mantra, Turing's CEO argues leaders must stay close to the details. He emulates a strategy of identifying the single most critical problem each week and working hands-on with the relevant team to unblock it, rather than operating through layers.
The most effective CEOs avoid medium-level tasks, focusing instead on high-level strategy and, counterintuitively, minor details. These small defects serve as a "spot check" to diagnose and fix the flawed underlying process—the "generating function"—that created them, providing powerful leverage.
The CEO actively optimizes his day for enjoyment by conducting a daily "energy audit," identifying and addressing draining tasks. He believes a leader's genuine enjoyment is infectious and crucial for setting a positive, high-performance culture, making it an operational imperative, not a luxury.
Turing's CEO argues that frontier models are already capable of much more than enterprises are demanding. The bottleneck isn't the AI's ability, but the "first mile and last mile schlep" of integration. Massive productivity gains are possible even without further model improvements.
Citing Phil Jackson's model, Turing's CEO describes a hierarchy of cultures. While a "Stage Four" culture is a strong team united against a competitor, the ultimate "Stage Five" culture transcends competition. It is characterized by a shared sense of wonder and the core belief that "life is great."
Seemingly simple user requests require a complex sequence of reasoning, tool use, and contextual understanding that is absent from internet training data. AI must be explicitly taught the implicit logic of how a human assistant would research preferences, evaluate options, and use various tools.
Turing's CEO claims SaaS is dead for two reasons. First, powerful foundation models drastically lower the cost of building custom software internally. Second, existing SaaS products are built for human interaction via GUIs, not for AI agents that will increasingly use APIs and tool-calling functions directly.
Turing operates in two markets: providing AI services to enterprises and training data to frontier labs. Serving enterprises reveals where models break in practice (e.g., reading multi-page PDFs). This knowledge allows Turing to create targeted, valuable datasets to sell back to the model creators, creating a powerful feedback loop.