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Historical TigerBeetle analysis with prod-code: 8,251 invariant asserts, consensus message frames, zero-allocation invariants, and an in-memory ZLS refactoring pre-flight check.

Coverage went from 53% to 87% and every file in the coverage report crossed 80%. Three things cost a day each: a SIGKILL that silently erased a whole daemon's coverage, a test that passed by skipping, and a read with a deadline it never checked.

In a multi-agent coding fleet, running separate rust-analyzer instances for every Git worktree multiplies memory consumption. Here is how an in-memory VFS overlay shares a single analysis database across worktrees, the Salsa concurrency traps we encountered, and our proposal to upstream.

In a mixed Go/JavaScript checkout, impact analysis reported zero changed functions and claimed every edit fell outside all functions. Why root manifests blind polyglot analyzers, how arrow functions hide from LSP kinds, and why missing symbols must be a gap rather than a verdict.

Cross-language schema rename needs semantic edits for identifiers and separate text edits for wire names. A polyglot fixture shows how prod-code plans the change, validates it, and reports what remains.

prod-code v0.3.19 expands workspace detection, but a detected language is not proof of semantic support. The marker matrix and release artifacts show what the version provides.

Rename is everywhere; changing what a function takes is nowhere. Building it meant letting the declaration write the rule, checking the result against the analyzer's own reference list, and refusing, under a normal apply, to write what the analyzer rejects.

We benchmarked all 67 prod-code AST tools against prometheus/prometheus: 385K lines of Go, 84 packages, 1,485 error checks, 99% slicing reduction, and Bug #740 fixed in remote module dependencies.

We benchmarked all 67 prod-code AST tools against bevyengine/bevy: 661K lines of Rust, 97 crates, 204 exact code clones, 2 dev-dependency loops, and Bug #739 discovered and fixed in fast-sync.

The author's report of running the prod-code AST tool suite against astral-sh/uv: 559K lines of Rust, 74 crates, 347 reported duplicated test-fixture occurrences, a self-referential cycle in uv-preview, and Issue #738 resolved in fast-sync.

We benchmarked all 67 prod-code AST tools against kubernetes/kubernetes: 5.38M lines of Go across 17,823 files, 779 packages, a reported but unmeasured 0% laptop CPU, and fixed Bugs #741 and #742 in Go signature compilation and predicate inversion.

We benchmarked all 67 prod-code AST tools against Alamofire: 39,000 lines of Swift, 92 throw sites (tests included), 20 clone groups, and remote Apple Silicon test offloading.

We evaluated prod-code AST tools against arrow-kt/arrow: 72,889 lines of Kotlin across 757 files, 38-module Gradle architecture, structural search for the Raise DSL, and cluster-verified AST refactoring.

We evaluated prod-code AST tools against dotnet/aspnetcore: 1,757,169 lines of C# across 10,685 files, 625 projects in a single repository, Roslyn generator snapshot clones, and cluster-verified OmniSharp refactoring.

We evaluated prod-code AST tools against dotnet/BenchmarkDotNet: 120,810 lines of C# across 1,175 files, 29 projects in an acyclic DAG, 1,120 benchmark harnesses, and cluster-verified OmniSharp refactoring.