How to Become a Payment Agent for the AI Economy
The AI economy is the freshest, most underserved vertical in payments. What a payment agent does, why AI businesses make exceptional residual accounts, and how to start with zero experience.
Strategies, guides, and deep dives on payment infrastructure, monetization, and the economics of building AI applications.
The AI economy is the freshest, most underserved vertical in payments. What a payment agent does, why AI businesses make exceptional residual accounts, and how to start with zero experience.
A tactical playbook for closing AI-startup merchant accounts: where to find prospects, the discovery questions to ask, the pain points to lead with, and how to handle the objections.
Merchant of record, PayFac, MIDs, interchange, tokenization — the embedded-payments concepts every agent and builder should be able to explain, and why embedding is a high-value residual play.
Why AI and SaaS businesses with usage-based and recurring revenue make the strongest residual accounts, and how agents build a compounding portfolio that grows on its own.
AI agencies and dev shops bolt payments on as an afterthought and leave recurring revenue on the table. How a payments partner delivers better client products and a new residual stream.
A decision framework for choosing the right revenue model for your AI product. Covers the four dominant strategies, when each works best, and the metrics that matter.
AI startups face unique payment challenges: bursty usage, micro-transactions, and unconventional MCCs. Here's how to evaluate processors and avoid the common mistakes.
A deep comparison of the two dominant SaaS pricing models, with specific scenarios for AI products. When does usage-based win? When do subscriptions still make sense?
AI agents are executing transactions autonomously. Learn about the agent payment stack, 4 patterns for agent payments, and the security considerations most teams miss.
Three integration patterns for AI products, merchant account setup for AI-specific MCCs, and the edge cases — metered billing, retry logic, multi-currency — that most guides skip.
PCI compliance levels, SAQ types, tokenization vs encryption, and the AI-specific risks — training data, agent PAN access, logging — that can break your compliance.