https://www.solosoft.dev/tags/prompt-optimization/Recent content in Prompt Optimization on SoloSoftHugoen-usFri, 01 May 2026 00:00:00 +0000https://www.solosoft.dev/post/dspy-framework-2026/Fri, 01 May 2026 00:00:00 +0000https://www.solosoft.dev/post/dspy-framework-2026/<p>Prompt engineering has become an unexpected skill requirement in the AI era. Developers who wanted reliable LLM output learned to craft system prompts, structure few-shot examples, chain instructions, and iterate through trial and error. The process was manual, subjective, and brittle — a prompt that worked perfectly with GPT-4 might fail with Claude, and a prompt that worked last week might degrade after a model update.</p> <p>DSPy, from the Stanford NLP group, takes a fundamentally different approach. Instead of asking developers to write prompts, it asks them to define the task. You specify what inputs the system receives, what outputs it should produce, and how to measure success. DSPy then treats the prompt as an optimization variable — searching through prompt strategies, few-shot examples, and instruction phrasings to find the combination that maximizes your metric.</p>