BlueTeam AI, a leading innovator in AI development tools, is announcing the invention of Decision Box, a novel solution for developers struggling with the complexities of prompt engineering for Large Language Models (LLMs). Decision Box offers an alternative approach, empowering developers to isolate LLM decision points where they can be instrumented, labelled and improved over time.
The outcome using this approach is an LLM application which exhibits measurable quality improvements with more data over time.
The challenge
Prompt engineering to improve LLM decision-making is a time-consuming and often frustrating process. Examples include agentic tool selection and model routing. Developers spend countless hours crafting intricate prompts to achieve the desired results from these powerful models.
Decision Box enables decisions to be continuously improved by data rather than laborious human effort.
How it works
Decision Box operates by distilling LLM decision points into smaller, more focused models which can be efficiently observed and trained. Developers can initially obtain a baseline measurement for recent decision efficiency, quickly label data from usage, retrain and watch app quality improve in objectively measurable terms. Examples of these key decisions might include tool or model selection, output formatting, or whether a transaction meets complex criteria.
The Benefits of Decision Box
- Escape Prompt Engineering Headaches: Decision Box eliminates the need for extensive prompt engineering, freeing up valuable resources.
- Data-Driven Refinement: Decision Box empowers models to continuously learn and improve as they encounter new data, ensuring long-term accuracy and effectiveness.
- Simplified Development: The tool's user-friendly interface streamlines the process of building and deploying AI applications, making it accessible to developers of all experience levels.
Decision Box represents a significant step forward for AI development. App developers can now provide evidence of consistent, transparent decision making in applications. Instead of relying on “black box” LLM queries with potentially inconsistent results over time, Decision Box distills these decision points into smaller, focused models.
Decision Box will be released next week for early adopters as open source. To learn more and sign up for early access, please subscribe for e-mail updates.