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Top 5 Prompt Engineering Problems (and How POML Solves Them)
Prompt engineering has exploded as one of the most sought-after skills in the AI era. Whether you’re cranking out marketing copy, documenting products, or powering customer-facing chatbots, one thing is clear: the way you phrase a prompt can make or break the quality of the output. But here’s the reality no one likes to admit—prompt…
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POML vs JSON: Why Structured Prompts Need a Markup Language
If you’ve ever worked with large language models, you’ve probably encountered JSON as a way to structure inputs and outputs. But as prompt workflows get more complex—multiple steps, tools, validations, and outputs—plain JSON starts to feel clunky. That’s where POML (Prompt Orchestration Markup Language) comes in. Let’s break down why a markup language purpose-built for…
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What Is POML? A Beginner’s Guide to Prompt Orchestration Markup Language
If you’ve heard people talk about “prompt orchestration” and you’re wondering where POML fits in, this guide is for you. We’ll keep it friendly and practical, with a simple example you can adapt right away. TL;DR POML (Prompt Orchestration Markup Language) is a human-readable way to describe multi-step AI prompt workflows—inputs, steps, model calls, tools,…
