DoorDash's AI strategy is evolving from simple chatbots to true agentic commerce. This means the system won't just suggest food but will take action, such as automatically ordering a user's lunch by integrating with their calendar to know when they're available, creating a fully automated, personalized experience.

Create a personal API endpoint with key information like your coffee order, favorite restaurants, or availability. While humans can use it, the real power is enabling AI agents to access this structured data to automate tasks like making reservations or buying gifts, bridging the gap between digital agents and personal preferences.

Companies like Uber and DoorDash build moats on customer lock-in. AI agents will eliminate this by automatically price-shopping for users, commoditizing demand. This shifts the competitive battleground to supply-side aggregation, lowering barriers to entry for new players.

Middlemen like retailers exist because of information asymmetry. Personal AI agents, with deep knowledge of individual needs, will aggregate demand and purchase goods directly from producers like farmers and manufacturers. This will eliminate the need for advertisers and retailers and enable hyper-efficient supply chains.

The true power of agentic AI lies in abstracting away complex, multi-step consumer tasks. For instance, a user could simply state they need a medical test, and an AI agent would automatically handle insurance verification, cost calculation, provider search, and appointment booking.

AI agents can perform complex tasks like ordering food by interacting directly with restaurants and drivers, bypassing aggregator platforms like DoorDash. This disintermediation removes the "middleman tax," returning margin and power to the original creators, fulfilling the internet's early promise of direct, open access without powerful gatekeepers.

The primary barrier for useful AI agents is not the underlying model but the complex task of 'data wiring'—connecting to a user's real-world context like emails, local files, and support tickets. Products that solve this difficult integration challenge, where most agents currently fail, will gain a significant competitive advantage.

AI platforms like Magic enable high-end restaurants to move beyond reactive service. By analyzing public data like social media and reservation history, they anticipate unstated guest needs to create hyper-personalized experiences, fostering deep loyalty that justifies premium pricing.

Soon, AI agents will make purchasing decisions for humans, creating a new economy that will dwarf human traffic. Businesses must shift from optimizing a "pixel-perfect" UI for humans to a "bits-perfect" platform for agents, focusing on API clarity, data structure, and overcoming agent biases.