The AI Record
We built Agentic MLE, short for machine learning engineer, to take on more of that work. It’s a set of tools and instructions that lets AI agents operate in Stripe's existing ML infrastructure, carrying an experiment from an idea to a result: explore the data, implement a feature, compute its historical values, train a model, and evaluate it against a baseline.

StripePublished by the organization itself (post), no named author

Post: Scaling Radar: Fighting fraud with agent-assisted machine learning, Stripe developer blog, October 19, 2026, at Giving agents the experiment lifecycle.

Checked against the source [ Grade B ] Said in the last year

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Checked against the source by a first reader, then confirmed independently by a second reader who fetched the source without seeing the first reader's notes (Independent review agent (Claude Sonnet), blind second pass from passage text and citation only, no repository access, 2026-11-08).

Exact match, with curly apostrophe in 'It’s'. Under 'Giving agents the experiment lifecycle'.

How to cite this passage

Stripe, “Scaling Radar: Fighting fraud with agent-assisted machine learning”, Stripe developer blog, 2026-10-19, at Giving agents the experiment lifecycle. https://stripe.dev/blog/scaling-radar-fighting-fraud-with-agent-assisted-machine-learning Archived at https://the-ai-record.com/passages/stripe-built-agentic-mle-tools-instructions-agents-2026

More from the same source

In a controlled comparison, the new configuration improved recall by over 8%, translating to an estimated tens of millions of dollars a year in additional fraud prevention for Stripe’s merchants.

StripePublished by the organization itself (post), no named author

Post: Scaling Radar: Fighting fraud with agent-assisted machine learning, Stripe developer blog, October 19, 2026, at Learning from a fraud attack.

  • 8% fraud model recall improvement, controlled comparison, 2026

Checked against the source [ Grade B ] Said in the last year Passage page

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