Armand Ruiz, VP of Product – AI Platform @IBM, posted “The future of AI is Agentic” with this architectural schema that looks promising for business decision-making with ongoing improvements:

Among important capabilities Armand listed:

Self-Reflection and Improvement: AI agents can analyze their own output, identify problems, and provide constructive feedback. By incorporating this feedback and repeating the criticism/rewrite process, agents can continually improve their performance across various tasks, including code production, text writing, and answering questions.

Tool Utilization: AI agents can use tools to evaluate their output, such as running unit tests on code to check for correctness or searching the web to verify text accuracy. This allows them to reflect on errors and propose improvements.

Collaborative Multi-Agent Framework: Implementing a multi-agent framework, where one agent generates outputs, and another provides constructive criticism, leads to enhanced performance through iterative feedback and discussion.