Four Years at Magic Leap: The Long View
Reflecting on nearly four years of building mixed reality systems - what I learned, what changed, and what's next.
Four years ago I knew nothing about AR/VR. Now I lead perception for devices shipping to customers worldwide, and the end of the year feels like the right moment to trace how that happened.
The Arc
2016 was learning everything: depth sensors, SLAM, embedded constraints, building a foundation from zero. 2017 was building teams and systems - the synthetic data team founded, eye tracking progressing, spec freeze pressure mounting. 2018 was the crucible of shipping: V1 launch, field feedback, debugging under pressure. 2019 has been maturation - V2 planning, scaling synthetic data, coordinating a global team.
Technical Evolution
Comparing what I believed in 2016 with what I know now is a little embarrassing. I thought more pixels meant better sensors; what matters is the right pixels at the right time, well-calibrated. I thought clever algorithms solved everything, when data quality and system integration dominate. I thought neural networks were magic black boxes - they're functions we can analyze, optimize, and understand. And I thought good specs led to good systems, when specs are only starting points and iteration is everything.
Leadership Evolution
The team grew from 3 to 45, including contractors, and my role changed underneath me along the way. Individual contributor became director spanning multiple sub-teams. Communication that was once mostly technical is now 50% technical, 50% people and process. Where I used to implement other people's decisions, I now make decisions that others implement.
That transformation surprised me. I came here to build, and ended up enabling others to build.
What I'd Do Differently
More real-data collection, earlier. Synthetic data is powerful, but we under-invested in real data, and the combination is stronger than either alone. I said last month that a small strategic slice of real data was the production strategy. The slice is right; the timing was not. We should have been collecting it much earlier instead of proving its value at the end. I'd also make production calibration a Year 2 priority instead of the near-ship scramble it became. In spring 2018 I wrote that production calibration would be automated in time for the Q3 ramp. It shipped, and it was still a scramble, which is what "in time" usually means in hardware. Spec-to-test traceability deserved more rigor: requirements existed but weren't systematically tested, and some V1 failures were specified features that were never verified. And more user research - we built what we thought users wanted, and more direct user involvement would have shaped priorities differently.
Industry Perspective
MR in 2016: "This is the future! Billions will wear these!" MR in 2019: "This is hard. Progress is slower than hoped. But still the future."
The hype cycle played out on schedule, and we're in the trough of disillusionment now, climbing toward productive deployment. The technology works. The use cases are still emerging.
What Comes Next?
V2 is on track, the team is strong, and the technology is maturing. For me, though, I'm starting to wonder: after nearly four years here, is there more I can learn? Are there other challenges where my experience could have more impact?
No decisions yet. But the question is there.
Whatever happens, Magic Leap gave me a masterclass in building complex systems from scratch - four years of challenges, failures, and late-night debug sessions - and that education comes with me wherever this goes.