In bioinformatics, wearing too many hats isn’t a metaphor. It’s a Tuesday.

One minute you’re troubleshooting a Docker build. Next, you’re tweaking a DESeq2 cutoff. Then comes a Slack message: “Can you just rerun that pipeline, but with the updated genome and that other annotation file we talked about last week?"

Many of us in computational biology are expected to be full-stack everything: devops, data wrangling, stats, visualization, user support, documentation, while also being experts in biology. And while it’s true that our field attracts people who can do a bit of everything, that doesn’t mean we should.

The Cost of Doing It All

Versatility is celebrated early in our careers, and it can feel good to be that person people turn to for analysis or advice. But at scale, it becomes a liability.

• You lose hours to context switching
• You burn out doing things you’re good at, but not best at
• You block your team when everything depends on you

For example, one time I built my own pipeline manager. It worked: jobs ran, parameters were tracked, and it even had a UI. But every new use case was a patch job, and every edge case slowed me down. 

Specialization Makes the Science Better

Real breakthroughs happen when we focus on what we do best and trust others to do the same. At Via Scientific, our focus is on infrastructure: making workflows reproducible, containerized, and scalable. This focus opens the door for:

• UX designers to make tools intuitive, even for users who’ve never touched the command line
• Cloud engineers to ensure reliability, observability, and security across clusters
• Computational biologists to chase insights without tripping over lower-level tech

When each person stays in their lane, velocity increases not because we’re faster individually, but because we’re not losing time untangling each other’s cables.

You don’t get that kind of cohesion when everyone’s trying to do everything. You get it when each person does what only they can do, while leaning on experts in other areas.

Final Thoughts: Focus Where You Add the Most Value

My highest contribution isn’t designing buttons or tweaking cluster queues. It’s building platforms where other people can do their best work without me in the loop every time. That shift in mindset has changed how I lead, how I code, and how I think about the future of bioinformatics.

It’s not about doing everything. It’s about doing what only you can do.

And by the way, the whole point of Via Foundry is to make this possible for any computational biologist, data scientist, or bioinformatician. It wasn’t built to replace anyone’s ingenuity. It was built to free them up to do what only they can do: design new methods, build pipelines that others can actually run, and chase the biology. Foundry takes care of the reproducibility, the containerization, the scaling. So specialists can spend their time making an impact, instead of patching infrastructure.

Turns out, taking off a few hats is the best way to actually move the science forward.

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