Agentic workflows are rapidly changing how we reverse engineer binaries. Large language models are no longer limited to explaining decompiler output or writing small helper scripts; when paired with real tooling, they can drive analysis, orchestrate workflows, and connect multiple analysis layers faster and at a larger scale than a human analyst alone. In this talk, we explore what this shift means for code deobfuscation, from deflattening, opaque-predicate removal, and string recovery to interprocedural and whole-program deobfuscation. We argue that the key advance is not that models suddenly understand obfuscated code perfectly, but that they can now coordinate the broader workflow around deobfuscation. We conclude by examining what kinds of obfuscation may remain resilient in the face of increasingly agentic reverse engineering.