Please Explain this Gap in your Resume

There’s a stretch on my resume between leaving a computational biology role at Flagship Pioneering in Cambridge and showing up as a Senior Data Engineer at Lantern Pharma in Dallas that doesn’t look anything like career progression.

I was on a farm in North Carolina.

I’d spent two years at Etiome as the first software engineer, building ML infrastructure for single-cell RNA-sequencing and electronic medical records. We were modeling the biochemical factors of disease progression temporally, at single-cell resolution, trying to capture how disease actually evolves across patients where everybody is n=1. Great team, good data, interesting problems. But the higher the resolution got, the more it felt like I was getting a sharper and sharper image of the wrong thing. We could see what happened as disease progressed. We couldn’t see what caused it to progress. If the biochemical pathways were transistors, we were watching them flip without ever finding the programming language behind their orchestration. Those are two very different questions, and no amount of sequencer resolution was going to collapse them into one.

That realization doesn’t fit in a quarterly review. It barely fits in a conversation. But once you see it, you can’t unsee it. The data points at something the data can’t contain.

While chasing that question deeper, I wrote an essay titled Our Superconducting Consciousness theorizing a physiological mechanism for what the Vedas called Kundalini, connecting the dots between what I’d learned as a bioengineer, my training as a yoga instructor, the new science I was reading, and my own phenomenological experience. It contradicted almost everything I’d learned as a bioengineer, but made complete sense based on what I was finding in Becker, Penrose, and Jung. I went to The Science of Consciousness conference in Arizona to find people asking the same questions. To my surprise and relief, they existed. The questions were real. But none of it was going to fit inside the career I’d started in Cambridge, so I left without a plan.

I did a darkness retreat at Sky Cave in Oregon to use my own mind as the crucible to test what I’d been theorizing. No music, no phone, no external input, no photons in my eyes for 6 days. A dozen thoughts a second became six, then three, then one, then silence. Out of that silence, the model I’d been operating under (biologist who happens to write software) broke. What I was actually doing was trying to reverse-engineer cognition, and I’d been approaching it from the wrong end. The biology had shown me what intelligence looks like at the molecular level. The contemplative work showed me what it feels like from the inside. The gap between those two descriptions was my new line of research.

When I ran out of money and left Boston for good, I moved to my buddy’s farm in North Carolina to sleep on his couch while helping him out and manically building software at night. It was cheap and quiet and post-COVID had shut down the normal re-entry paths. I read a lot. Hofstadter, Schrödinger, Lilly, Sheldrake. Books I’d been circling for years but never had the space for. I built AI applications and operational automation platforms for consulting revenue to pay the bills, bouncing from odd-job to odd-job and learning how to quickly build and ship agentic intelligence and automation pipelines that survived handoff. And I spent a year with a question that had been forming since my undergrad research at Clemson and had finally become impossible to ignore: what is a living system actually doing that our models can’t capture, and what does that have to do with the intelligence we’re now building in silicon?

This is the part where I’m supposed to say I was discovering the secrets of the universe.

Some of that actually happened. But things that used to feel like separate interests started to feel like facets of one question. The engineering, the biology, the yoga, the increasingly strange psychology I was experiencing. They were all circling the same problem: what is intelligence, actually? Not the benchmark version. The phenomenon. And how are concepts like consciousness or life related?

I came out of that year a different kind of engineer. The farm didn’t hand me a neat answer. But it’s where the questions became clear enough to build around, and where my professional identity caught up with what I’d actually been trying to do for years.

I incorporated Attune Intelligence as an LLC in North Carolina at the time, now re-incorporated in Dallas. Not because I had a business plan, but because I needed a vehicle for the research I planned to do that wasn’t attached to anyone else’s roadmap. Lantern Pharma hired me to build data infrastructure for cancer drug discovery, and my experience from college writing software and data pipelines for cancer biology came back to relevance, now married with the agentic AI systems I’d been building on the farm. It turned out to be exactly the right place to keep building while the deeper questions developed in parallel. I went from Senior Data Engineer to Lead Platform Architect in a year, and now lead development of our withZeta.ai platform. The “What Lives?” paper with Michael Levin and Blaise Agüera y Arcas came out of Attune Intelligence as my first formal attempt at resolving some of these questions. The homelab I’m building from scratch is my instrument for expanding the scale of questions I can ask.

The gap produced all of it.

The questions I couldn’t answer at Flagship are the ones I’m now building infrastructure to pursue. All of it traces back to a year on a farm that looks like nothing on paper. Sometimes the most productive thing you can do is stop producing long enough to figure out what you’re actually trying to build.

If someone asks you to explain the gap, the real answer is usually the most interesting thing on your resume.