Michaela Burpoe

A Career Built By Asking Questions

The method that defines Michaela's work showed up long before she had a title. As a business major, and the first in her family to go to school, she decided the best way to use the opportunity was to find out what people actually did all day. So she went and asked the adjunct professors: how they got into their roles, what they liked, what they did not. She ran a whole series of those sessions before she knew such a thing could be a job description.

The answers pointed her toward a co-op in Washington, DC, a rotation program with the USO that moved her through a host of departments, one of which was recruitment. That was the intersection she had been looking for, a place where business, people and analytics met in the same seat. She came back and took an internship as a sourcer at an executive search firm near her college, one that supported finance, pharma and tech. It doubled as a sampling exercise. Which profiles did she most enjoy talking to? Which functions held her attention? The answer was tech, and specifically the agency and executive search side of it, where she worked with a range of technology companies and began pattern matching on stage as well as sector, noticing what a Series B felt like against a Series D and which environments suited her.

That pattern recognition led her to Grafana Labs, and Grafana Labs led her to Supabase. The symmetry is not lost on her: a career that started with asking people about their careers.

The People Who Handed Over The Keys

Michaela had worked all through high school, but the executive search firm was her first role that functioned as a career rather than a job. Its two co-founders, each with more than 20 years in the industry, gave her the fundamentals: how to source, how to work a cold call, and the business acumen that is difficult to acquire any other way. Looking back, what stands out to her is less the curriculum than the risk. She was fresh out of school, had never done the work before, and was interfacing with executives constantly. That was a significant amount of trust to place in someone, and she has not forgotten it.

The other lasting influence is Roshni Sondhi, VP of Customer Experience at Grafana Labs during Michaela's years there. Michaela has two young daughters, and Roshni offered proof that ambition and motherhood in tech were not competing bids for the same person. Watching someone equally driven navigate both at once was, in Michaela's word, refreshing. The relationship also became a technical sounding board. Before she moved to Supabase, Michaela went to Roshni to ask what she made of the company and the founders she was connected to.

Automate The Operational, Protect The Human

Supabase sits underneath much of the current building boom as a de facto backend for AI companies including Lovable, Bolt and Figma, which means Michaela works inside an organization that is AI native at the product level. She counts that as luck. It has also sharpened her thinking about where the tools genuinely help.

Her rule is that AI absorbs the operational load so the team can spend its hours on people. An AI note taker feeds structured feedback forms that recruiters then supplement. Pipeline updates flow automatically into Slack channels. Because being remote and async has made documentation both an asset and a flood, she built a weekly intelligence brief for her team that consolidates the go-to-market channels and flags what actually requires attention.

The more interesting applications point at hiring managers. Michaela has used AI to compare what three different panelists on the same loop are really assessing, then read the differences back to them. In a company growing this fast, she has found, articulating precisely what a team is looking for is harder than it sounds. Supabase closes its process with a values-based bar raiser stage, and she was able to pull a full readout across it and give each panelist individual feedback on whether they had held to values or drifted into functional territory. That exercise, she estimates, would have taken a full month before.

Not everything has worked. Early experiments with AI-generated outreach produced messages that looked personalized but did not read as authentic. The reason for the discipline is the nature of the hiring itself: in hypergrowth, much of the assessment targets intangibles like adaptability, grit and creativity, and those do not compress neatly into an agent prompt. Dealing with people, she argues, requires a delicate balance.

She does not build any of it alone. Zach Choquette, who first brought her over to Grafana Labs and is now a Supabase colleague, runs much of the AI project management across the team, including a headcount request form he built with a Supabase backend and a Vercel frontend. Michaela tag teams tool evaluations with Dasha, who oversees the tech side while Michaela covers go-to-market.

Advice For 2026

Heading into the new year, Michaela's counsel to other talent leaders is to stay curious and to stop flinching at new tools. She understands the hesitation. The fears are legitimate ones: automation reaching processes that should stay human, and questions about privacy and data access, the kind her own security team has raised as Supabase has started evaluating platforms. But she believes the industry is thoughtful enough to work through those hurdles, and that avoidance is the costlier position.

"The more you can experiment, the more you can figure out what works and what doesn't," she says. Force the fun early, is her framing, because these tools are going to be a substantial part of the day-to-day either way. The payoff she cares about most is a strategic one. Recruiters have always done anecdotal pattern matching on profiles and markets, and for the first time there is enough data behind those instincts to carry them into the rooms where decisions get made.