Cristian Rivera

Sai Samant

Discover how we modeled our MongoDB infrastructure as a traversable graph and then use pathfinding algorithms to dynamically compute and execute recovery plans. This automated approach reduced pager volume by 30% (~200 pages/year), eliminated 12 days of unhealthy shard states annually, and supports new shard layouts with zero manual effort.

How Stripe uses graph search and state machines to auto-remediate a global database fleet

Most of the world's money still moves in batches. A wire submitted at 2pm might settle by end of day, if you made the cutoff. ACH takes one to three business days. Cross-border payments touch correspondent banks, each adding lag and a fee. Stripe has spent over a decade building the Global Payments and Treasury Network (GPTN), a programmable infrastructure for global money movement that batches transfers to reduce cost, nets opposing flows to minimize actual cash moved, and routes through the optimal path between accounts. Under the hood, it's a graph with accounts as nodes, and payment rails as edges.

Extending Stripe’s network with stablecoins

In this post we’ll dive into how we built a virtual cashless payment method that works for prepaid and Stripe-issued credits, and cleanly integrates with our accounting, compliance, and other frameworks.

How we built Stripe Credits: A programmable, auditable way to pay your Stripe fees

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Harbor is the internal tool Stripe teams use to prototype with an AI agent. This post covers how it compiles prototypes in the browser, how the agent inspects its own work, and how comments stay anchored when the page is rewritten.

Harbor: Stripe’s AI-assisted prototyping tool

About the authors

Cristian Rivera

Sai Samant