For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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DocumentationIntegrationsAgent OptimizationSelf-hosting OpikSDK & API referenceOpik University
DocumentationIntegrationsAgent OptimizationSelf-hosting OpikSDK & API referenceOpik University
    • Overview
  • Intro
    • Opik Overview
    • Next steps / Set expectations
  • Observability
    • Log Traces
    • Annotate Traces
  • Evaluation
    • Evaluation Concepts and Overview
    • Create Evaluation Datasets
    • Define Evaluation Metrics
    • Evaluate your LLM Application
    • No-code LLM Evaluation Workflow
  • Prompt Engineering
    • Prompt Management
    • Prompt Playground
  • Testing
    • PyTest Integration
  • Production Monitoring
    • Online Evaluation Rules
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  • Scaling Prompt Engineering with Systematic Management
  • Key Highlights
Prompt Engineering

Prompt Management

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Scaling Prompt Engineering with Systematic Management

This video addresses a critical but often overlooked aspect of LLM application development: prompt management. As applications grow, teams can end up with dozens or hundreds of prompts that become duplicated, outdated, or inconsistently applied without proper organization. You’ll learn how Opik’s prompt management features help organize, version, and share prompts across teams, transforming chaotic prompt handling into systematic, scalable workflows.

Key Highlights

  • Systematic Organization: Organize prompts into logical “prompt buckets” with clear naming conventions (project-based + prompt type) to prevent chaos as you scale
  • Complete Version History: Track full commit history with 16+ versions per prompt, including timestamps and commit messages for complete prompt evolution visibility
  • Experiment Integration: See all experiments connected to specific prompts, making it easy to identify which prompt variations performed best across different test runs
  • Side-by-Side Comparison: Use compare features to analyze differences between prompt versions, enabling data-driven prompt optimization decisions
  • Rich Metadata Support: Attach key-value metadata to prompts as standard JSON objects for additional context and organization
  • Programmatic Management: Use opik.Prompt class to create and commit prompts directly from code, integrating prompt management into development workflows
  • Team Collaboration: Tag and share prompts across team members, ensuring consistency and preventing duplication across projects
  • Performance Tracking: View attached metrics from experiments directly in prompt views, connecting prompt changes to performance outcomes
  • Playground Integration: Seamlessly use tracked prompts in Opik’s playground for testing and iteration (covered in next video)