2026 is an exciting year for the Rust compiler (and me)

Original Article ↗ Hacker News Discussion ↗

Rust’s evolving compiler roadmap for 2026 is raising both excitement and concern, as planned features like a new trait solver, specialization progress, polymorphization, and better debug info defaults promise to reduce technical debt, binary bloat, and target directory size. Many developers praise Rust’s safety and performance but highlight real pain points around long compile times, huge build artifacts, and hardware demands, especially compared with Go or Python in large projects and CI. Others question whether Rust can remain the language of the future or if a new ecosystem combining Rust-like safety with Go- or Zig-like simplicity and speed will eventually displace it, particularly as AI-assisted tooling changes how code is written.

Title handling and HN quirks

  • Multiple submissions had their titles auto-altered; HN’s automatic “fixes” sometimes mangle legitimate titles or jokes.
  • Editing limitations meant the correct title could only be fixed later.

Compile times and target directory bloat

  • Several comments report very large target/ dirs (tens to ~190 GB) and constraints on laptops / smaller disks.
  • Rust’s heavy debug info and monomorphization, plus large dependency trees and feature-driven crate duplication, are cited as main reasons for bloat.
  • Suggested mitigations: debuginfo = "line-tables-only" (soon default for dev), upcoming cargo gc, and tools to unify dependency features across workspaces.
  • Experiences with compile times diverge sharply:
    • Some see release builds of real apps taking 15–90 minutes, making CI and edits painful.
    • Others report sub-second to seconds-level incremental builds even for large codebases, and view multi‑minute builds as a sign of poor project architecture or environment issues (e.g., AV on build dirs, huge dep trees, heavy macros/generics).

Rust vs other ecosystems

  • Comparisons with Python and Go emphasize near-zero “build” time in those languages versus Rust’s.
  • Some recount massive runtime speedups from rewriting Python in Rust, justifying slower compiles.
  • Others argue that long compile times are a liability in operations (e.g., outages delayed by rebuilds) and make Go/Zig attractive despite trade-offs.
  • Discussion notes that generics/monomorphization and derive macros inherently cost compile time, unlike Go’s more dynamic dispatch model.

Language evolution and alternatives

  • Some think Rust’s future is bright and that it is already “the present” (Linux kernel, Windows, browser).
  • Skeptics predict a future language combining Go-like simplicity, Zig-like compile speed, and Rust-like safety, possibly with Lisp-like syntax.
  • Others point to OCaml and GC-based systems programming as viable alternatives in some domains.

Compiler roadmap and tooling

  • Excitement around the new trait solver, Polonius, and progress toward long-stalled features like specialization and async-related improvements (Return Type Notation, async functions in traits).
  • Polymorphization discussed as a way to reduce code duplication; basic forms may be enabled by default, with more aggressive forms for debug/size-optimized builds.
  • rust-analyzer’s persistent caching depends on work in Salsa; support exists but is preliminary and not yet a priority.
  • Brief questions about Clippy’s role in an LLM-heavy future; consensus is that it will remain useful.