The Trap of the Single Prompt
Most developers start their AI journey by building a 'wrapper'. You take a user input, wrap it in a system prompt, send it to an LLM, and return the result. If the result is wrong, you try to 'prompt engineer' your way out of it by adding more instructions to that single prompt.
This is a dead end. No matter how good your prompt is, LLMs struggle with complex tasks in a single pass. They hallucinate, they skip steps, and they fail to double check their own work.
Agentic workflows are different. Instead of one long prompt, you break the task into a loop of smaller, specialized steps where the LLM can reason, act, and correct itself.
From Linear to Iterative
