In cell-based computational notebooks, programmers repeatedly edit and execute cells. Recompiling and re-executing an entire cell on every execution is inefficient; ideally, stable code and data should be reused. We present \emph{annotation-guided edit-aware JIT compilation} for Julia, a technique that leverages two user-provided annotations about code and data stabilities—\texttt{@hole} and \texttt{@persistent}—to avoid unnecessary recompilation and recomputation. It partitions a cell into a stable \emph{skeleton} and an unstable \emph{hole}, compiles them separately while folding stable data as inlined constants, and reuses the skeleton across executions. We prototyped this approach as \textsc{nbjit.jl}, an IJulia kernel extension. Across five editing scenarios, cumulative execution time ranges from $3.3\times$ (lightweight workloads) to $1/167$ (compute-intensive workloads) relative to Julia’s standard \texttt{eval}. The prototype currently supports a subset of Julia: basic numeric types, control flow, and composite data structures. Automatic annotation inference and full Julia language coverage remain as future work.