We present Holey, a Python library that stages satisfiability predicates to SMT via dynamic operator overloading and light AST rewriting. By symbolically executing Python and emitting portable SMT‑LIB, Holey swaps solvers cleanly and re‑verifies candidate models in Python. On the P3 benchmark, the symbolic executor alone solves 64% of int puzzles, 34% of str, and 27% overall, revealing a clear gap around list encodings and synthesis queries. We discuss design patterns that make staging practical in Python, a failure taxonomy that guides solver‑friendly encodings, and a pragmatic hybrid where LLM guidance complements solver‑checkable guarantees. We discuss a recipe for staging to SMT and a research agenda around relational encodings and solver interfaces for Python tooling. Holey is available at https://github.com/namin/holey.