Designing the Opuz Prompt Management Platform
Ragip Diler
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Posted Dec 25, 2025
Led the end-to-end design of Opuz. a clean, intuitive playground for prompt engineers to create, test, optimize, and validate prompts with confidence.
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Opuz — Prompt Engineering & Testing Platform Case Study
Project Overview
Project Name: Opuz
My Role: Product Designer
Duration: 10 weeks
Platform: Web-based saas product
Opuz is a prompt management, testing, and optimization platform designed for prompt engineers and AI developers. Users can create system prompts, configure LLM settings (model, temperature, max tokens, etc.), add tools, test responses, and validate them with checks (content controls, JSON validation, etc.). The platform enables reliable prompt development through trace runs, multi-response comparison, and detailed feedback mechanisms.
Problem & Opportunity
AI developers and prompt engineers face several challenges when manually testing prompts:
Comparing prompt variations across different models (Claude, Gemini, OpenAI, etc..) is time-consuming.
Ensuring response consistency (hallucinations, unwanted content, format errors) is difficult.
Lack of team collaboration: Prompts are scattered in code with no version control.
Manual tracking of cost and latency.
Opuz addresses this gap by making prompt engineering more systematic, collaborative, and efficient.
My Role & Process
As the Product Designer, I owned the entire design process:
Research: Competitive analysis (tools like PromptLayer, LangSmith, OpenAI Playground etc..), and reviewed prompt engineering trends.
User Flow Design: Defined flows for prompt creation, tool integration, check addition, and test result viewing through wireframes.
UI/UX Design: Created a clean, focused dashboard with settings on the left panel (System Prompt, LLM Settings) and test results/response comparisons on the right. Modern interface with blue-white tones for a user-friendly experience.
Outcomes & Impact
Opuz simplifies rapid prompt iteration and improves reliability. Users can reduce costs while enhancing response quality. The project has strong potential to transform AI development workflows.