The Zef language's baseline AST-walking interpreter was 35.4x slower than Python 3.10 according to ScriptBench results published at https://zef-lang.dev/implementation. Primary source details 17 incremental changes that delivered 14.2x improvement over baseline bringing it within 1.6x of QuickJS-ng 0.14.0. Largest gain occurred at change #6 when object model and inline caches were added improving from 1.5x to 6.8x relative speedup.

Techniques parallel Deutsch and Schiffman inline caching from the 1984 Smalltalk-80 implementation cited in https://dl.acm.org/doi/10.1145/800017.800542 and Lua 5.1 VM design described in Ierusalimschy et al. https://www.lua.org/doc/jucs05.pdf. Zef avoided hash-table property lookups via inline caches and switched from boxed IntObject to tagged values reducing allocation pressure. Original coverage omitted explicit mapping of watchpoints to deoptimization patterns used in V8 hidden classes and relevance to custom DSLs embedded in AI agent runtimes where sub-millisecond dispatch matters.

Synthesized sources show these pre-JIT methods fill documented gap in practical guides that jump directly to bytecode or tracing JITs. For AI tooling and DSLs the same value representation and monomorphic inline cache patterns apply directly to sandboxed prompt interpreters or tensor operation DSLs without requiring full GC or machine-code generation.