PromptEngineeringforDevelopers

The same model can produce wildly different outputs depending on how you prompt it. A well-engineered prompt on GPT-4o-mini often outperforms a lazy prompt on GPT-4o, at a fraction of the cost and latency.

Prompt engineering is the highest-leverage skill in AI development. Before you fine-tune a model, scale your infrastructure, or add complexity, optimize your prompts. The ROI is immediate.

Prompt chaining breaks complex tasks into sequential steps, where each prompt handles one focused subtask. This is more reliable than asking a single prompt to handle everything.

Self-consistency techniques run the same prompt multiple times and aggregate results. Reflection prompts ask the model to critique and improve its own output. These patterns add latency but dramatically improve accuracy for high-stakes outputs.