Prompt Engineering for AI Agents: 7 Production Patterns That Beat “Better Prompts”

Most prompt engineering advice is still written for one-off ChatGPT conversations.

That is useful, but it misses where developers are spending more time now: AI agents, coding assistants, automation workflows, and LLM-powered product features .

In those systems, the winning prompt is not usually the longest prompt. It is the prompt that makes the model easier to control, test, debug, and reuse.

I checked recent DEV topics around #ai , #productivity , and #promptengineering , and a clear pattern stood out: developers are talking less about magic wording and more about agent architecture, token costs, control flow, prompt quality, and production reliability .

So here is the practical version: seven prompt patterns I would use when moving from “cool demo” to “repeatable AI workflow.”

1. The Role + Boundary Pattern

Bad agent prompts often give the model a role but no boundary.

You are a senior developer.…