Prompt engineering is no longer text-only. With GPT-4 Vision, Claude 3, and Gemini handling images, documents, charts—even audio—2025 demands a new discipline: multi-modal prompt evaluation. This post outlines how to evaluate image + text prompts systematically, measure performance, and build…
As prompt engineering matures, brute-force trial and error no longer cuts it. Complex tasks—multi-step reasoning, document synthesis, agent orchestration—need structured prompt refactoring. In this post, we explore reusable refactoring patterns to improve clarity, reliability, and output quality when basic prompting…
Few-shot prompts are powerful. But writing them ad hoc doesn’t scale. Serious AI teams treat few-shot prompts like code modules—reusable, versioned, tested, and optimized. This post walks through how to design, structure, and scale a few-shot prompt library that supports…
Manually testing prompts is fine for hobby projects. But if you’re shipping LLM-powered apps, you need an upgrade. Enter: LangChain + LangSmith. This combo lets you track, evaluate, and iterate on prompts automatically—with structured workflows, detailed logging, and prompt version…
You can’t improve what you don’t measure. And in prompt engineering, what you measure shapes how you build. By 2025, AI teams have moved beyond vibe checks and spot tests. If you’re deploying LLMs in production—or even prototyping seriously—you need…
