How Ramp Built Self-Maintaining Software

In this talk from Data Driven NYC, Alex Levinson, Software Engineer at Ramp Labs, dives into the future of "Self-Maintaining Software." As AI takes over the heavy lifting of writing code, the new bottleneck in the development lifecycle is maintenance and observability. Alex introduces Ramp Inspect, an agentic system designed to autonomously monitor production, triage alerts, and propose code fixes without human intervention. From building a "nightly QA pass" to the visionary concept of the "Software Factory," learn how Ramp is shifting the engineering focus from building software to building the pipelines that build—and maintain—software at scale. 00:04 - Introduction to Ramp Labs and self-maintaining software 01:11 - The shift from writing code to code maintenance 01:59 - Introducing Ramp Inspect, the background coding agent 03:05 - The first experiment: Nightly AI code automation 04:23 - The limits of stateless monitoring in large observability surfaces 05:47 - Using Datadog monitors to give the AI state and focus 07:23 - Real-world example: AI autonomously fixing an authentication bug 08:14 - How to control noise and implement an AI triage pattern 09:27 - The old vs. new paradigm for continuous code observability 10:21 - Key learnings on building autonomous AI software factories Ramp Labs Website - https://labs.ramp.com/ X/Twitter - https://x.com/RampLabs HOSTED BY: FirstMark Capital Website - https://firstmark.com X/Twitter - https://twitter.com/FirstMarkCap Matt Turck (Managing Director) Blog - https://mattturck.com LinkedIn - https://www.linkedin.com/in/turck/ X/Twitter - https://twitter.com/mattturck This session was recorded live at a recent Data Driven NYC, our in-person, monthly event series. If you are ever in New York, you can join the upcoming events by following FirstMark on Luma: https://luma.com/firstmarkcap Check out the MAD Podcast: Spotify - https://open.spotify.com/show/7yLATDSaFvgJG80ACcRJtq Apple - https://podcasts.apple.com/us/pod