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In which I explain how AI agents can be used to perform tasks autonomously
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Al’s AI Implementation Guide: Part 1 - First Principles
Meet your new AI agent colleague
ChatGPT is probably smarter than you
- It can solve maths problems at competition level
- It can pass law, medicine and engineering exams
- It can probably write your partner a better romantic poem too
But working with a chatbot is like managing an intern on their first day
- They don’t have access to the right documents
- They lack the tools to do the job
- And they don’t know how things work around here!
Every time you assign a task, you have to explain it from scratch, upload the data, and manually implement the suggestions. Even then, because they’re new to the task, it can take a few iterations before getting it right.
How do we build agents that can own work tasks?
Summary
1. We equip agents with the knowledge, tools and process to get the job done
They can take a task and, with minimal guidance, complete it to the required standard.
At their core is the same LLM as a chatbot, but they’re connected to your business’s data, workflows, and tools.
💽 1A**. Data retrieval and storage**
- Agents can find and use the right data to get the job done
- They can save information which might be required later