The last five months with Claude Code have completely changed how we work.
matsen.group/agentic.html details:
• How agents work (& why it matters)
• Git Flow with agents
• Using agents for science
• The human-agent interface
Questions? What has your experience been?
Phylogenetic inference should be impossible, and yet it works. Lena Collienne led a project to build deep learning on the classical ideas that make it work. Now out in Systematic Biology.
matsen.group/general/2026/10…
Coding tools are great at producing code. But they don't fit how I do science, where the manuscript is the central artifact. So I built bipartite: manuscript-driven development with a team of agents, directed the way a PI directs a group.
matsen.fredhutch.org/general…
Spec-kit points to the future of software development. New post: when I use it, how it's changed my dev flow overall, and a complete walkthrough building a bioinformatics pipeline from scratch. matsen.group/general/2026/02…
Over the past 5+ years we've had the honor of working with the Victora lab on a project to "replay" affinity maturation evolution from a fixed starting point.
My summary
matsen.group/general/2025/11…
is for both immunologists and evolutionary biologists.
The era of coding agents is here. How do we approach this as scientists?
Wednesday Dec 10th at 9am PT I'll livestream an interactive demo of what I have learned (matsen.group/agentic.html) about how to leverage agentic coding to do rigorous science.
piped.video/watch?v=Rbhs7CoL…
The Mahan postdoctoral fellowship offers 21 months of support to develop your own research with Fred Hutch computational biology faculty-- lots of excellent labs to choose from!
Apply: apply.interfolio.com/172697
Faculty: fredhutch.org/en/research/di…
The final version of our transformer-based model of natural selection has come out in MBE. I hope some molecular evolution researchers find this interesting & useful as a way to express richer models of natural selection. doi.org/10.1093/molbev/msaf1… (short 🧵)
I forgot to post two things I liked doing in this paper that I hope catch on. First is to have links in the methods section to the model fitting code (in a tagged version github.com/matsengrp/netam/r… as the code continues to evolve):
... and second is to have a map from the figures to where they are made in the associated "experiments" code repository (github.com/matsengrp/dnsm-ex…):