#prompt engineering

Versioning and Managing Prompts Like Code in Your AI Projects

Somewhere between sprint three and sprint seven, a prompt in your codebase changed. Nobody announced it. The output got worse — responses started being too short, the tone shifted, or edge cases started failing. You grep through the code trying to find what happened, and eventually realize someone edited the prompt string directly in the source file, probably to fix something else, and didn't think much of it.

Fine-Tuning vs Prompt Engineering: When to Use Which Approach

Both approaches solve the same problem: getting an LLM to do exactly what you want. They solve it in completely different ways, at completely different costs, and one of them is almost always the wrong choice for what you're actually trying to do.