The Core Skill You Need to Build an LLM Agent

Do you want to become an LLM full-stack developer? Do you know about the chain of thought (CoT)? A typical LLM agent utilizes perception, memory, planning, and action like humans. If the LLM fails to think and solve complex problems like humans, then it has no advantages. It’s never the simple input-output mapping system, but a system that performs step-by-step reasoning. Normally, an LLM is helpful in parsing natural language instructions into executable plans and by applying external tools like databases, obtaining feedback that matches human cognition.

The LLM full-stack developer’s core skills lie in prompt engineering, tool learning, in-context learning, memory mechanisms, action planning, and multimodal interaction.

For example, you want your LLM agent to help you with the following tasks.

“Help me plan a holiday trip to Casablanca for next Friday. There are 4 people on this trip, and the budget is about $3000 per person. The trip is about one week. It should be interesting and entertaining.”

In order for your LLM to perform the above task, it must execute the following path.

1. Search for the availability of flights with respect to budget.
2. Create a questionnaire to collect preferences for hotels.
3. The collection of important visiting areas.
4. What are the best areas for local food?

Obviously, the above is the sample path, but in reality, the list is much larger. But it should be important after the event has been planned; the LLM can collect feedback from you like which areas are most interesting. Moreover, the LLM learns from these experiences and does better when planning similar activities in the future.

The core skill of an LLM full-stack developer is to build an agent that collects information and activities and organizes processes. It can handle various affairs, freeing people from tedious details and allowing them to do more important things.