1. Skip‑lists in production
Why they’re used: Simpler to implement, provide O(log n) average performance, and shine in range queries, concurrency, and memory‑constrained systems.
"skiplists form the basis of in‑memory tables used by LSM trees, which are themselves the basis of most modern DBs (written post 2005)." — mrjn > "Redis sorted sets are probably the most widely deployed example. Redis uses a skiplist for range queries and ordered iteration paired with a hash table for O(1) lookups." — cremer
2. AI may erode low‑level data‑structure expertise
A recurring worry is that reliance on LLMs for “quick fixes” will make deep algorithmic knowledge—and the ability to craft efficient structures—obscure.
"In the age of agentic programming … we’ll just throw more hardware at problems, write yet another service, and soon lose the skills to develop new ones." — teiferer
3. Simplicity vs. raw performance trade‑offs (especially concurrency)
Many note that skip‑lists offer an attractive middle ground: easy to reason about for concurrent use, with predictable pointer‑chasing patterns, even if raw speed can lag behind tuned trees in some cases.
"The nice thing with skip lists, is all 'rungs' of the list are stored in an array for a given node, so there's a lot less pointer chasing." — torginus
--- These three themes—real‑world adoption, concern over AI‑diminished systems knowledge, and the balance of simplicity versus performance—capture the dominant perspectives in the discussion.