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AI is no longer a black box reserved for researchers, it is now a daily tool for product managers, analysts, and engineers. But as you have probably noticed, the complexity of AI-driven tasks is exploding. Gone are the days when a single prompt could wrangle a nuanced research summary or a multi-step business analysis. Today, you are expected to orchestrate multi-stage workflows, ensure audit trails, and deliver outputs you can trust.
That is where prompt chaining comes in. By breaking complex tasks into smaller, traceable subtasks, you gain three things: accuracy (each step gets the model’s full attention), clarity (instructions and outputs are easier to audit), and control (you can fine-tune or debug any link in the chain). In this article, we will see why prompt chaining is fast becoming a must-have skill for anyone working with advanced AI systems.
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