As AI models get faster at generating tokens, developer experience bottlenecks will shift from waiting for the model to thinking to waiting for tool calls and test execution. This will create pressure to rebuild DevEx teams focused on optimizing the speed of file I/O, test runners, and compilers for AI agent workflows.

• Token generation speed is approaching the point where millisecond-level differences in file reads (100ms vs 10ms) and test execution (500ms vs 2s) will determine whether an AI agent responds instantly or takes minutes.
• Fast inference models like LLaMA running at 17,000 tokens per second show what instant-response development could look like, but only if the entire tool chain keeps pace.
• Languages with fast compilers and tight dev loops like Go will have a competitive advantage for agentic coding, and companies will likely resurrect DevEx teams in the late 2020s to optimize for AI agents rather than human engineers.