PromptShip helps AI engineers version, test, and iterate on prompts for ML pipelines, RAG systems, and LLM applications.
Your evaluation prompts live in Jupyter notebooks, system prompts in config files, and the best few-shot examples in Slack threads. No single source of truth.
You tweak a system prompt and eyeball the output. There is no way to A/B test across models or track which version performed best.
Every engineer has their own prompt patterns. Your RAG pipeline uses different extraction prompts depending on who last touched the code.
A prompt management workspace designed for how you actually work.
Every edit creates a new version with diff tracking. Roll back when a prompt regression breaks your pipeline.
Use {{context}}, {{schema}}, and {{examples}} to build reusable prompt templates across different ML tasks.
Test the same prompt on GPT-4o, Claude, and Gemini side by side. Find which model handles your specific task best.
Clone these to your workspace and customize with your own variables.
Given the following retrieved documents: {{context}}, synthesize a comprehensive answer to: {{question}}. Cite sources inline...
Evaluate this LLM output against these criteria: {{criteria}}. Score each 1-5 with justification. Output: {{output}}...
Step 1: Extract key entities from {{input}}. Step 2: For each entity, generate {{task}}. Step 3: Synthesize results into {{format}}...
Free plan includes 200 prompts and Gemini 2.5 Flash. No credit card required.
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