Why This Blog Exists

The blog post that started it

Sometime during my graduate studies, I found Stephen Turner’s Getting Genetics Done blog. One post in particular rewired how I thought about staying current in a fast-moving field: How to Stay Current in Bioinformatics/Genomics.

I read it and added every resource he mentioned to my RSS reader that same afternoon. That one post kicked off my genomics and bioinformatics career in a way no lecture or textbook had. Someone working in the field took time to write down what they knew and share it openly, and that alone made the whole field feel reachable.

Years later, Turner wrote about learning in public, crediting Simon Willison’s idea of blogging as an accountability mechanism. Willison, with 25 years of experience, still writes TIL (“Today I Learned”) posts about things as basic as bash for-loops. Writing it down forces you to explain what you think you understand. The gap between “I get it” and “I can explain it clearly” is where the learning happens.

Building the system

Writing is the hard part of learning. I’ve started drafting explanations of things I thought I understood and realized halfway through that I’d been carrying a wrong mental model for years. You can’t wave your hands in a blog post. The draft sits there, exposing every gap.

I’m also 37, which means my brain has started deleting things I read to make room for mortgage rates and knee pain. I used to hold an entire paper in my head for weeks. Now I forget what I read last Tuesday. Half this blog is a letter to my future self, who will need the help more than I’d like to admit.

But a blog is chronological. Posts pile up. Six months later, even with the posts, I can’t remember what I wrote about multi-omics integration or where I left off with network pharmacology. I needed something structural alongside the timeline.

That’s why I built a wiki, inspired by Andrej Karpathy’s LLM Wiki concept: let an LLM handle the bookkeeping (cross-references, summaries, consistency checks) while you focus on curating sources and asking good questions. Every atomic concept gets its own page: “ADME determines whether a drug reaches its target.” “Negative feedback loops enable homeostasis.” One claim per page, with links to related concepts and source citations. The pages connect through typed relationships (depends-on, enables, challenges, creates-tension), forming a knowledge graph I can browse visually.

The fields I’m working in (computational biology, AI, drug discovery) are converging fast. A concept from systems biology connects to how you’d design an agentic AI workflow. Protein language models borrow the same pretraining logic as GPT, but the inductive biases differ in ways that matter. The wiki is where those cross-domain links become visible, and the blog posts are the public output built on top of it.

What you’ll find here

Book and paper digests. I read something, pull out the one idea that changes how I think, and write about why it matters. More conversation with the source material than summary.

TILs. Short notes when I learn something surprising. A tool that solved a problem. A finding that contradicted my assumption. Quick to write, useful to revisit.

Mini reviews with hands-on analysis. I survey a method or field, then run it on public data to see what happens. These double as portfolio pieces and learning exercises.

The wiki. The connective tissue. Browse the knowledge graph, search across concepts, or trace how ideas in one domain relate to another.

Learning maps. The books, papers, and lectures I found helpful, organized by domain.

Every post shows the work: what I read, what surprised me, what I’m still confused about, what I’d try next. If I only wrote about things I fully understood, I’d never write anything.

Starting late, starting now

I wish I’d started this years ago when I first read Turner’s blog. I didn’t, because I thought I needed to know more first. I’m still learning. I’ll always be learning. That’s the whole point.

If you’re reading this, you’re watching someone figure things out in real time. I’ll get things wrong, and I’ll update posts when I do. The archives will show the trajectory.

What would your career look like if you’d written down everything you learned, every week, for the last five years?