Researchers have unveiled MAKER, a pioneering system that flawlessly executes over one million steps in an LLM-driven task, shattering previous limits where errors derailed processes after mere hundreds of steps. By combining extreme task decomposition with multi-agent error correction, MAKER demonstrates that long-range, human-scale AI workflows are now feasible without relying on ever-larger models. This advance signals a paradigm shift toward modular, agentic AI capable of tackling complex organizational challenges.