SaaStr's initial AI, a clone of founder Jason Lemkin for giving advice, unexpectedly received many questions about events and sales. This user behavior revealed a clear need for dedicated go-to-market AI agents, pivoting their AI strategy from a simple experiment to a core business function.

To ensure optimal performance, each AI agent at SaaStr is given one primary objective. The AI VP of Marketing's goal is to "own the number." This singular focus ensures all its data analysis, campaign ideas, and actions are goal-seeking and aligned, preventing it from getting overloaded.

Don't try to build a complex AI agent from day one. SaaStr's AI VP of Customer Success started as a basic project management portal to replace a clunky tool. Its advanced, agentic capabilities were layered on over months as real user needs became clear post-launch.

Initial adoption of AI agents was driven by solving small, personal annoyances like ordering groceries, dubbed "computer errands." This low-stakes entry point helped users build familiarity and trust with the agent before graduating them to more complex, high-value professional work.

SaaStr's AI marketing agent "10k" analyzes data, ideates campaigns, segments lists, and writes copy without human intervention. This moves beyond simple automation to proactive, strategic marketing tasks, even operating on weekends.

Plurium’s founder followed a proven path for B2B innovation. He started a marketing agency (service), identified a core data attribution problem (pain point), built a dashboard (tool), and then layered on an AI agent (automation) after observing users spend hours manually analyzing the data themselves.

SaaStr's AI marketing agent, "10k," has become so effective at generating strategic daily tasks that the company is hiring a human to execute them. This reverses the typical hierarchy, with the human employee reporting directly to the AI manager for their daily priorities.

The true power of an AI agent is its capacity to handle the mundane, repetitive work that humans—both internal teams and external agencies—often neglect or de-prioritize. SaaStr couldn't find people willing to consistently manage hundreds of follow-ups, a task their AI now handles flawlessly.

SaaStr's AI VP of Marketing (10k) and VP of Customer Success (QB) began as basic dashboards and project management tools. They gradually gained more capabilities through iterative development, showing that complex agents can start with simple, focused use cases to solve a specific pain point.