I like the distinction between fixing the current task and improving the system that produces future tasks. That's a pattern that applies well beyond coding agents. Too many teams keep adding instructions to prompts when the real fix belongs in the harness, a reusable skill, a deterministic check, or a regression test. Treating repeated failures as signals to improve the surrounding system not just the model's immediate output is what makes agent workflows scale instead of accumulating more prompt debt over time.