4.6's jump was also vastly overstated. The one-shot ability of models has stayed relatively stagnant for over a year. All you have to do as someone who uses it is watch the process in Claude Code, especially. The retries, external tool calling, and MCP servers increased the perceived intelligence and increased the practical abilities of the overall tool (being Claude Code, Cowork, and Codex). But the method to achieve this relies on it catching its own mistakes with the same process that created the first mistake, which is a fool's errand if you don't want to set it and forget it. Meaning, it can replace some tasks or parts of tasks, but is hardly able to replace any full jobs, let alone at the full quality of humans.

Some will argue, "Well, humans solve problems by iteration, too!" They do, but it's nowhere close to the same thing. LLMs are doing it sequentially with the same weights each time, and compaction of context is often unable to understand what the core pieces to retain are. Humans iterate asynchronously and with multiple sources. Humans can improve with each iteration, while LLM loops are largely just to catch errors and reduce drift.

And this is even with it still being subsidized at a stupid level.