In the second installment of our Day in the Life series, we follow Microsoft researcher Flavio Griggio, a quantum-hardware specialist navigating superconducting circuits, mentoring sessions, and the occasional sci-fi escape.

What Does a Typical Workday Look Like for You?

7:00 am: My morning begins with a cup of green tea and a quick glance at my calendar. I use this time to scan my inbox for anything urgent and jot down my top priorities for the day. On Tuesdays and Wednesdays, I have weekly early morning meetings with our European counterparts.

7:30 am: I lace up for a brisk morning run—my favorite way to charge up both mind and body before the day’s adventures begin. It helps organize my thoughts for the day.

8:30 am: I hop aboard the Connector bus from Seattle to our Redmond campus—easily my favorite Microsoft perk. The commute transforms into a rolling think tank, where I devour the latest quantum circuit papers and jot down fresh insights to share with my team. Staying ahead of the curve is a must in a field that rewrites itself daily.

9:00 am: Most days, right after a cup of espresso, my first meeting is a standup with our fabrication team. We briefly sync on progress, blockers, and any discoveries. It’s energizing to hear how every member is advancing their part of the puzzle.

10:00 am–12:00 pm: This is my most productive block—deep work time. I typically code, design experiments, or assess our fabrication yields. I mute notifications and dive in, often covering my whiteboard with so many equations and sketches that colleagues joke it could qualify as modern art—or perhaps as an unsolved riddle for visiting physicists.

12:00 pm: Lunch is usually a quick affair. If the weather’s nice, I take a walk outside or share a meal with coworkers. These informal moments often spark creative conversations or lead to new ideas.

1:00 pm: Afternoons are reserved for collaboration—mentoring engineers, meeting with academic partners, or hosting brainstorming sessions. I love these interactions; they challenge my thinking and keep me inspired.

3:00 pm: I might have a 1:1 with my manager or one of my reports. This is also a good time to catch up on Teams discussions and provide feedback to colleagues across different time zones.

4:30 pm: Most days wrap up with reviewing experiment results and planning the next steps. I log what worked, what didn’t, and create a short list for the days ahead.

6:00 pm: Before signing off, I do one last sweep of urgent emails and jot down a few lines in my research journal—a practice that helps me track progress and reflect on the day’s challenges and wins.

My Research: Superconducting Circuits for Quantum Computing

Opening New Doors in Fault-Tolerant Quantum Technology

I’m working on building superconducting circuits that can spot the tiniest changes in capacitance—these shifts show us what’s happening with our topological qubits. We’re always checking out what other teams are learning about superconducting circuits, so we can stay up to date and keep improving.

What really matters is our big goal: to create a quantum machine that stays reliable even when things go wrong, for example if the readout is noisy, slow or miscallibrated, it can misrepresent the qubit state, leading to incorrect results or failed error correction. My team’s readout circuits are key to making this happen—they help us actually see and use the power of topological qubits. When we get this right, it could have a tremendous impact—helping research in medicine, energy, environmental science, smart materials, and much more. 

Most importantly, Microsoft is working to build a quantum system that can scale up and help as many people as possible. It’s exciting to be part of a team that’s moving this technology forward, and I can’t wait to see how it will shape the future.

Can You Share a Specific Challenge You’ve Faced Recently in Your Research and How You Approached Solving It?

One time when our team faced a real challenge was during the early development of a design of our superconducting circuits. We noticed some performance inconsistencies that didn’t line up with our simulations. Rather than just tweaking parameters at random, we held a brainstorming session to map out which fabrication or material variables might be at play. We narrowed down our shortlist to the most likely culprits and designed quick experiments to test each one, even syncing up with colleagues in different time zones to analyze the results in real time. That methodical approach helped us zero in on a subtle manufacturing issue that, once fixed, noticeably boosted our circuit performance. It was a great reminder of how collaboration and targeted experiments can turn a vague problem into a breakthrough.

How Do You Decide Which Research Questions Are Worth Pursuing?

Here’s what guides me: Will cracking this puzzle help teams everywhere sidestep setbacks? Can we run quick, low-cost experiments for a sneak peek before diving deep? And above all, can we capture lessons that fuel real progress—not just stories traded in the coffee room?

What Emerging AI Trends Are You Most Curious About, and Why?

I'm focused on AI that boosts engineering performance and reliability by automating tasks and generating testable hypotheses. Foundation models impress me with their ability to generalize and explain outcomes, and I’m interested in designing energy-efficient AI that still delivers strong results. For example, my team tracks product performance metrics, and AI now helps correlate deviations with process variables, offering targeted parameters for engineers to review. These advancements motivate us to develop technology that's both effective and efficient.

Can You Recall a Moment in Your Career That Made You Think, “This Is Why I Do This Work”?

One time when our team was deep into testing a new component, I witnessed a moment that truly crystallized why I do this work. After weeks of fabricating, dicing, and packaging, we gathered to review the radiofrequency characteristics. As the system team pulled up the cryogenic temperature plot, the room fell silent—the performance characteristics landed precisely where our projections had predicted, a rare alignment of theory and reality. There was a collective pause, an unspoken acknowledgment that all the careful tracking of process telemetry, projections, and etched tolerances had paid off. In that quiet, each of us felt the impact of our work and the power of collaboration, as a subtle tweak in etch bias and oxide deposition proved decisive in hitting our frequency targets. It was a reminder that behind every breakthrough, there's a team willing to test, refine, and celebrate the moments when science comes alive.

How Do You Hope Your Research Will Impact People or Society in the Next Decade?

In the next decade, I want our lab work to make quantum‑scale hardware feel dependable. By making readout components more power‑efficient and our fabrication more predictable, we’ll help larger quantum systems—and the science they enable—move from fragile prototypes to reliable tools that benefit medicine, materials, and climate research.

How Do You Stay Inspired or Recharge During the Day?

When I need a burst of inspiration, I reach for my favorite sci-fi novel—nothing fires up my imagination like exploring worlds where the impossible feels close at hand. Outside the lab, group runs are my secret recharge button; the rhythm of shared strides clears my mind and sparks new ideas before I’m back at my desk. And of course, you’ll often find me fueling up during spontaneous coffee chats with colleagues—where some of our best brainstorms begin.