Category Archives: Agents
Creating a multi-agent application – Part 4
In part 3 we looked at creating the researcher. As promised, today we’ll look at the author. You’ll notice in the following code a great deal of similarity to what we’ve seen before. The goal is to create a code … Continue reading
ReAct and Agents in AI
In the previous post, we looked at the use of Chain of Thought (CoT) reasoning in the context of LLMs. For an LLM to take action in the world, however, it needs agents. The paradigm for this is called ReAct—that … Continue reading
AI Reasoning and Planning
Until very recently, it was observed that LLMs had a very hard time with complex problems. Context was lost, memory of previous steps was distorted, and so forth. This led to unreliable results (hallucinations) and, consequently, to a lack of … Continue reading
PEAS for Agent AI
A classic AI framework to define an agent’s task environment is PEAS. It stands for:





































