AI Essentials for CX Teams

Prompting is one of the most important new skills in AI and CX teams are uniquely positioned to excel at it. If you’ve ever written a help center article or trained a new teammate, you already understand the basics: clear instructions lead to better outcomes. 

A strong prompt follows a simple structure: instruction, context, and input.

• Instruction is what you want the model to do: “Summarize the customer’s issue.”
• Context provides background: “The customer is on a premium plan and was double-charged.”
• Input is the actual message: “I think I was billed twice this month, can you check?”

Together, these elements guide the model to produce accurate and relevant responses. Prompts can also assign roles and goals: “You are a fintech support agent. Your goal is to reassure the customer and explain the next steps.” This anchors tone and intent, ensuring consistency.

Effective prompts share a few best practices: be explicit about structure, provide grounding context, and anticipate ambiguity. For example, instead of a vague “Help the customer,” you might write: “Draft a response that acknowledges frustration, confirms we’ve checked their account, and explains the refund timeline.”

When scaling AI in support, you’ll encounter three approaches: 

1. Prompt stuffing crams everything into one giant prompt — flexible but costly and error-prone.
2. Coded workflows enforce strict rules but slow teams down with engineering bottlenecks.
3. Decagon’s Agent Operating Procedures (AOPs) combine the best of both, using flexible natural language with structured, traceable logic that CX teams can own.

Finally, prompts can encode safety rules, like asking for missing details or escalating sensitive issues to a human. Good prompting techniques ensure AI agents reflect your brand standards and operational safeguards.