Our Operating Principles

How we’re aligning our values with action, especially when the going gets rough

10 May 2023

We founded Arcadia with an optimism for a different way of doing science. We wanted the Arcadian way to be rooted in our values and unique goals.

Our values can’t just be ideals though; they must be embodied in principled actions. This is, of course, easier said than done. Building a new organization involves a seemingly endless onslaught of decision points and pivoting. Abiding by principles in the face of this uncertainty and discomfort requires commitment.

To keep ourselves accountable, we’ve developed a set of operating principles to guide us. Our principles are both emergent and aspirational — reflective of the collective qualities of current Arcadians and also representative of what we want to strive toward. And that work is never done. By putting these out into the world, we hope you will help hold our feet to the fire too.

Below, we’ve shared the operating principles we think are most unique to Arcadia and our mission. As a team, we discussed concrete places where these ideals show up in our day-to-day, and we provide examples below.

1. We do the right thing — right now.

Honesty and integrity are critical for our success. Principles shouldn’t be context-dependent, so the “right time” is always right now. We don’t wait for situations to be less risky or more convenient.


One of the ways this principle shows up is how we share our work with the scientific community. Most research findings stay hidden for months or even years before they’re published in scientific journals, adding drag to the scientific process. In our first major blog post, we stated, “...no work produced or funded by Arcadia will be published in journals.” Rather than wait for better platforms, more aligned career incentives, and greater certainty of the path forward, we decided to just start publishing our work on our own terms. We’ve since released 17 pubs — read more about our ongoing publishing experiment here.

This certainly made the decision to join Arcadia harder for some. This is a feature, not a bug. We understand the immense privilege we have to take this risk, but every Arcadian believes waiting for a more convenient time is a greater risk to scientific progress as a whole.

2. We maximize the utility of our science.

Ultimately, we want our science at Arcadia to be useful. We define our success by how much our science gets reused by others. This has to be our constant North Star.


We want all aspects of our science to have utility, which extends beyond commercial applications. We want our science to be reused in all sectors. We often discuss a very practical consideration — that our research equipment and reagents have to be cost-effective enough for most scientists to be able to adopt our approaches. The return-on-investment ceiling for our science depends on it. For this reason, we value frugal, scalable science. This guides our decision-making in a variety of areas, like which microscopes to buy, which software packages to build upon, and what general strategies to take. 

We also try to write about our work in a way that is simple and accessible. Learn more about our work, and check out a specific example of an imaging tool that we’ve designed to be useful to others.

3. Symbiosis is our superpower.

We believe the whole is greater than the sum of its parts. Our strength lies in coordinating diverse, complementary strengths across the team to tackle science that can’t be achieved otherwise. Arcadians are low ego + high ambition individuals, and we work hard to align personal goals with collective mission.


A few months into starting Arcadia, we had our first company-wide scientific brainstorming session. It was kind of magical. With low-ego, mission-aligned people in the room representing an exceptionally diverse array of scientific disciplines, our ideas moved in directions that wouldn’t have been possible otherwise. And then Arcadians experimentally went after the ideas together at warp speed without being territorial. We’ve continued with these brainstorming sessions, now called “Sandbox.” And because you can't engineer people prioritizing collective outcomes, we aggressively recruit for people who already have this mindset.

4. Our model should be replicable.

We are trying to unlock a new way of doing science, which is critical for human progress. Our degree of impact is directly related to how many people outside Arcadia can adopt our model, so we must make it scalable and replicable by others.


We’ve been generously funded to try out a different approach to science over the next decade. We hope our lessons inform new organizational models that others pursue, sparking ecosystem-level change. But if there isn’t sufficient philanthropic funding for new efforts, the potential impact will be limited. That’s why we are testing the hypothesis that fundamental science can yield sufficient revenue to sustain operations, if approached strategically and over a long enough period of time. If we show that basic research is indeed a smart financial investment, our experiment could expand the pool of investors and resources for similar efforts.

To best position ourselves for this experiment, we made the early call to switch to a for-profit tax structure. Read more about our thinking.

5. Data, not drama.

When in doubt, do the experiment. We believe in the scientific process — an empirical and iterative approach. In the absence of an established blueprint for how Arcadia should work, we will be pragmatic and evidence-driven in lieu of inaction or forceful opinions.


Diving into the unknown means accepting partial information about what next steps are best. Ironically, the less we know, the more opinionated we become. However, in moments of uncertainty, we should strive to be more objective and scientific. This means running informative experiments. Our Software team has taken this approach many times. There are often differing opinions around tool selection, team structure, and computational training at Arcadia. Luckily, there are usually small test runs we can do to collect key data. For example, this is how we ultimately chose to use Nextflow as our workflow-building tool.

Arcadians should strive for self-awareness and learn to notice when we’re slipping into drama without data. Read more about how our Software team has navigated some of these moments.

6. We have to bring our A-game.

We are doing something hard. We need to learn from every experiment. Poor execution is a bad experiment. We expect excellence across the organization, from science to operations.


This one’s pretty self-explanatory. If you’re excited to join a team of people who hold each other to a very high bar, check out our latest job opportunities!


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