The other day I had a bug in production. Something was rendering wrong in the UI and I couldn't figure out where it was coming from. I gave Claude the URL, it opened Chrome, inspected the HTML in the browser, cross-referenced what it saw in the DOM with my source code, and found the exact line where the error was. Not the file; the line. It navigated between the rendered output and the codebase, matched what was broken on screen to the component that produced it, and pointed me to the fix. That moment stuck with me. Not because AI saved me time (it does that daily), but because of what it revealed about the nature of the answer. The model didn't know where the bug was. It inferred it. It observed the rendered HTML, estimated which parts of the code could produce that output, and surfaced the most probable origin. That probabilistic inference across two different representations of the same system; browser and codebase; was more effective than my deterministic debugging would have been.…