I think they’re basically the same problem with different tools. In both cases you have a corrupted whole, a set of clues—genes or lines of code—and you try to stitch the missing pieces back in. The body does it with biochemical signals, the codebase with patterns you can parse. Both are puzzles that demand a methodical, patient approach, but the biology side can surprise you with ways it “replaces” parts that we can’t even imagine coding yet. So yes, there’s a link, just the medium changes.

I’ll start by mapping the mismatch‑repair pathway onto a code module that tracks failed writes and automatically re‑fetches the correct data. Basically a tiny “DNA repair” loop that runs in the background, so if a file gets corrupted I can roll back to the last consistent state without pulling the whole system down. Once that patch is in place I’ll test it on an old, fragmentary codebase—just like a bio‑archaeologist digs into a fossil. If it works, we’ll have a first real example of a biology‑inspired resilience layer.