What’s next for AI: AI agentic workflows?

I’m sure that most of you would have recently heard about Devin AI, it gathered a lot of attention as the world’s first AI Software developer. Now we have another one from India called Devika. So, is this the future of AI development, AI Agents? Let’s try to go a layer deeper into what are AI agents, how they are evolving, and how they are going to change the workflow of AI development. And the most important of all, is this going to be the next steps towards AGI or AGI itself? So, without further ado, let’s jump right into AI agents and AI agentic workflows.

In general, an AI agent is a system that perceives its environment through sensors and acts upon that environment using actuators based on its perception, internal states, and experiences to achieve specific goals. But in this article, we are specifically talking about LLM-based AI agents. They operate autonomously on the web or an OS (Operating System), can learn from their interactions, and make decisions to pursue their objectives, often optimizing for certain criteria.

Table of Contents

• History of AI Agents
• Improving the Prompts
• Giving Self-Reflection Capabilities to LLMs
• Using Tools to Operate Autonomously
• Understanding AI Agents
• Agentic Workflows
• Conclusion