AI Native Engineering

The goal is to shift engineering work away from repetitive maintenance tasks such as updating tests, fixing broken systems, and reviewing mundane code changes. The vision is to reduce daily toil so engineers can focus on meaningful productivity using human creativity. This approach is intended to scale across team sizes from small to very large. Current time allocation includes substantial effort on administrative tasks and modernization alongside feature development, with less time devoted to feature exploration. Over seven months, an AI4P community was built to enable AI-native engineering and improve productivity. The community grew from zero to over 400 members, with increasing tool adoption and time savings in workflows that require heavy lifting.

"I'm really excited to share a case study of how we've been embracing AI native engineering in my small part of Reality Labs, which is called Horizon Experiences. I want you to imagine that you aren't here and you're back in your chair, working away, thinking about what you're doing on a day-to-day and thinking about how much of that time you spend is focused on toil, updating tests, fixing things that are broken, reviewing mundane code changes, time that you could be spending otherwise focused on solving interesting problems. That's the core vision behind what we're trying to do within our little part of Meta."

"Our vision is that we want to move people away from being builders to becoming explorers and innovators. Focusing on reducing the toil that happens on a day-to-day basis so that you can spend your time doing something meaningfully productive using your human creativity for its maximum effect. The timeline for this may look something like what you see on the slides here now."

"I think we're broadly aligned with end of year 2025 right now where a significant amount of our time is spent on both administrative tasks and modernization as well as feature development. A much smaller portion of that time is spent on feature exploration. What I've been doing over the last seven months is building up a community around what we call AI4P, AI for productivity. I'm going to share with you some of the numbers and some of the things that we've been doing to try and make that leap effective from engineering as we know it, to AI native engineering."

"In the seven months that we've been at this, we've driven organic growth of a community from nothing to over 400 members. We see significant tool adoption now and also significant time saving in some workflows where the specific workflow is the heavy lifting i"

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