Credo: Declarative Control of LLM Pipelines via Beliefs and Policies

1. 1Implement Credo's declarative control framework in your LLM pipeline to enable beliefs and policies-based decision-making
2. 2Define beliefs and policies using a declarative language to specify agent behavior
3. 3Integrate Credo with existing LLM models to adapt to new evidence and revise prior conclusions
4. 4Evaluate the performance of Credo-controlled LLM pipelines using metrics such as transparency and adaptability
5. 5Refine Credo's beliefs and policies to optimize agent behavior in continuously evolving conditions

AI engineers and researchers designing agentic AI systems can benefit from Credo's declarative control approach to improve the transparency and adaptability of their systems

💡 Declarative control of LLM pipelines enables more transparent and adaptable agent behavior, allowing for better incorporation of new evidence and revision of prior conclusions

🤖 Credo introduces declarative control of LLM pipelines via beliefs and policies, enhancing transparency and adaptability in agentic AI systems! #AI #LLM