Iterating on Prompts and LLMs in Production Is Challenging
Predicting the impact of a new prompt/LLM in production on user experience and overall product usage often involves guesswork and risk. Additionally, the process of iterating on prompts typically requires constant back-and-forth between product teams who want to make changes and engineering teams who need to redeploy the application. This slows down innovation and creates bottlenecks in your workflow.
Streamline Your Deployments with A/B Testing for Prompts and LLMs
Literal AI’s new Prompt A/B Testing feature allows you to deploy prompt changes or new LLMs directly in production. Here’s how:
Rollout New Prompts Progressively: You can now progressively roll out new prompt versions or LLMs, mitigating risk by gradually introducing changes. This method allows you to compare performance metrics between different versions and make informed decisions based on real-world data.
Empower Your Product Teams: With A/B Testing, your product team can independently manage and deploy prompt updates without needing constant support from the engineering team. This decouples the development cycle from prompt iteration, leading to faster innovation.
How It Works - Video
Benefits of Prompt A/B Testing
Increased Confidence in Deployments: By gradually rolling out and comparing new versions against existing ones, you can ensure that any changes are beneficial before fully committing.
Product Team Autonomy: Empower your product team to roll out and test prompt improvements without depending on engineering.
Free Engineering Resources: Engineering teams can focus on other critical tasks.
Data-Driven Decision Making: Make decisions based on real data by comparing the performance metrics of different prompt versions. This reduces guesswork and increases the reliability of your deployments.
Rapid Iteration and Optimization: Quickly iterate on and optimize prompts in a production environment, ensuring your application continues to improve in response to user needs.
Minimized Risk: If a new prompt version underperforms, you can easily roll back to a previous version, minimizing potential disruptions to your product.
Two Ways to Compare Prompt Performance
Continuous AI Evaluation: Set up continuous AI evaluation from your code or directly within Literal AI to automatically monitor and compare prompt performance.
Product-based Metrics:
Collect explicit human feedback, such as thumbs up or down from users.
Correlate this feedback with your product metrics (conversion for instance) using tools like PostHog.
Conclusion
Literal AI’s Prompt A/B Testing feature is designed to enhance the efficiency and effectiveness of your prompt management and deployment process. By enabling progressive rollouts, empowering product teams, and providing robust performance comparison tools, this feature helps you make informed, data-driven decisions with confidence and give time back to Engineering.
Start A/B Testing your prompts today and unlock a new level of control and confidence in your AI-driven products. Schedule a demo here or directly try it out.