6 posts
Moving beyond brittle hand-written prompts: a practical guide to meta-prompting and metric-driven, programmatic prompt optimization with DSPy.
Prompt engineering is now engineering, not art. Automated optimization with DSPy, an eval-driven workflow, structured output, prompt chaining, and Turkish-specific evaluation.
Moving from hand-writing prompts to programmable pipelines with DSPy: signature, module, optimizer concepts, code examples, metric definition, a Turkish task, and KVKK-compliant production.
The era of hand-writing prompts is closing. I explain DSPy, meta-prompting and eval-driven loops that let the machine optimize your prompts.
The era of tuning prompts by hand is ending. Automatic optimization with DSPy, MIPROv2 (10-40% lift) and GEPA (beats MIPROv2 by 13%, 35x efficient). A practical guide in a Turkish/KVKK context.
A comprehensive Turkish guide that takes prompt engineering from zero to advanced. Covers the 6 components of a prompt, 14 core techniques (zero-shot, few-shot, CoT, ToT, ReAct, self-consistency, meta-prompting), Turkish-specific notes, 20+ ready templates, model-specific differences (GPT-5, Claude Opus 4.7, Gemini 3), prompt injection defenses, DSPy-based automatic optimization, and A/B testing.