Before this, “AI agents” sounded complicated.
Now I understand them in a much simpler way:
AI agents are like helpful teammates they don’t just answer questions, they can think, decide, and take action.
They can book things, plan tasks, analyze info, use tools, and even remember what you said earlier.
Here are the biggest insights I took away:
1. Agents are not chatbots
A chatbot replies.
An agent does things like search, calculate, recommend, summarize, or complete a multi-step task.
2. Agents use “tools”
You can teach an agent to use an API, look up data, or perform actions.
It’s like giving them apps to work with.
3. Memory matters
Good agents don’t forget.
They remember context so they can help over multiple steps like a real assistant.
4. Safety + evaluation is a big deal
We learned how to check if the agent behaves correctly and doesn’t hallucinate or make unsafe decisions.
5. Anyone can start building
You don’t need deep AI knowledge.
The course showed simple ways to structure an agent and connect it with everyday tasks or workflows.
Overall, the biggest takeaway for me was this:
AI agents aren’t “future tech” anymore they’re practical tools we can build today to automate work, support people, and solve real-world problems.
Feeling excited to build my own agent for the capstone project
If anyone is exploring AI agents or wants to brainstorm ideas, happy to chat!
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