Large Model or AI Agent?

2 min readApr 28, 2024


When utilizing ChatGPT’s large models, users typically provide brief prompts, and the model promptly generates responses. It’s akin to having someone sit at a keyboard and compose an article on ‘blockchain’ for you, translating their thoughts into words on the spot.

Yet, these large models lack awareness of potential errors or instances requiring deletion and revision. Nonetheless, this usage method has become prevalent and is extensively employed in non-Agent workflows.

Compared to this, the workflow of Agents is notably different, using an article about ‘blockchain’ as an example.

Initially, the large model autonomously generates an article outline, conducts thorough research, and utilizes online content to form a draft. Then, the Agent carefully reviews, optimizes, and iteratively modifies the draft, significantly enhancing its quality.

Iterations are key in the Agent’s workflow. Through review and refinement, the Agent continually improves the article’s accuracy and depth, similar to human thinking processes. This results in a final article that is more precise and insightful.

The Agent’s approach demonstrates advanced analytical thinking. Compared to non-Agent methods, it delves deeper into article content, iteratively refining to meet user expectations.

A research team conducted experiments evaluating AI code writing. Results:

  • GPT-3.5: 48% Accuracy
  • GPT-4: 67% Accuracy
  • GPT-3.5 + Agent: Beats GPT-4
  • GPT-4 + Agent: Significantly outperforms GPT-4.

So, when using large models, the Agent’s method brings a fresh perspective. It improves article quality and accuracy while enabling deep understanding and analysis of content. As technology advances, this iterative and reflective approach becomes essential in AI’s future development.

Imagine having a smart AI partner tackling complex problems with you. It understands your needs, analyzes your thinking, provides helpful insights, and helps find the best solutions. It follows instructions diligently, asks insightful questions, encourages deeper thought, and prompts further exploration.

DimAI is closely tracking the evolution of AI Agents, integrating this technology into its products to advance beyond current AI methods. This shift promises more intelligent, human-like experiences.

Expect deeper interactions with AI in the near future, moving beyond simple commands to collaborative problem-solving and knowledge exploration.

Let’s embrace this exciting future together. With DimAI leading the way, we can explore limitless possibilities and opportunities in the intelligent era.