AI companies should align their pricing with what matters to their customers after demonstrating value, rather than relying solely on fixed or consumption-based pricing models.

AI companies often struggle to define the value they generate, leading to uncertain pricing strategies as they experiment with different models.

Agent-based pricing allows companies to charge based on the work done by AI agents, which can replace a significant portion of traditional sales development roles.

Charging by activity and changing pricing based on workflows are effective strategies for AI companies, moving towards value-based pricing rather than cost-based pricing.

AI companies need better tools to understand their unit economics and capture more value from their offerings.

To succeed, AI companies need to understand their unit economics and how to price their services effectively based on the value they provide.

AI agents represent an opportunity to reclaim energy and focus in product management, allowing for deeper customer engagement and more enjoyable work.

AI startups should focus on niche markets and specific applications to avoid being overshadowed by larger companies like OpenAI and Google.

AI agents can help product managers offload draining tasks, allowing them to focus on customer immersion, data analysis, and strategic thinking.