o1-preview: The Future of CoT Changed by Reasoning Models

**.

---

Until now, LLMs have been 'machines that are best at guessing the next word.' But OpenAI's o1-preview is different. This model unfolds a Chain of Thought (CoT) before it speaks, verifying its own logic.

We summarize how this has brought destructive innovation to agent design.

---

1. The End of Prompt Engineering?

Previously, developers had to craft long prompts like "Think step-by-step" to make models think intelligently. But o1 performs this process within its own architecture. Even without complex instructions, the model finds the optimal solution path on its own.

---

2. Breaking Through Scientific and Mathematical Limits

In complex physics problems, decryption, and high-level mathematical proofs—where traditional LLMs struggled—o1 shows PhD-level performance. This means we can build agents that act as 'research assistants' in specialized fields, beyond simple chatbots.

---

3. The Era of Slow Thinking

o1 is slow. It can take 30 seconds or more to give an answer. But this 'slowness' isn't incompetence; it's 'sophistication.' In agent services where "accurate judgment" is more important than "a fast answer" (e.g., security analysis, system design), o1 is irreplaceable.

---

Henry's Perspective: "A Paradigm Shift in Intelligence"

Watching o1, we realize once again that intelligence isn't just about having a good memory, but about the 'power of deep consideration.' If your agent is at an orchestration stage where it must make important decisions, actively adopt the o1 model.

---

(Only one post left until 100% completion of the final goal!)