How fast can you taste code? (dayson.io)

As coding agents accelerate, the author argues the human bottleneck has shifted from typing code to reading and judging it quickly. Rather than competing with synthetic speed, developers should cultivate "taste": the ability to scan code fast, recognize elegant versus brittle designs, and rapidly re-steer an agent when it produces fragile or off-spec output. Tinkering with solid open‑source projects is presented as the best training ground — a place where clean abstractions, tests, and real-world constraints sharpen judgment without “AI slop.” For the AI/ML community this reframes priorities: models can generate code quickly, but they don’t replace the human functions of evaluation, specification, and corrective guidance. Practically, that means investing in developer skills (rapid code comprehension, pattern recognition), tool support (diff-aware reviewers, automated testing and static analysis to surface brittleness), and workflows that treat human-in-the-loop steering as the core control lever. The punchline—“taste > typing”—signals that specifying what you actually want and knowing how to assess generated code are now higher-value skills than raw typing speed.