AI has now become a critically important consideration in customer environments. UiPath AI prompt engineering is a key platform capability for driving AI initiatives on the UiPath platform, and I expect it to be increasingly embedded across—and applied to—all features going forward.
Recently started working on IXP solutions and APAs, Prompts are something which always bothered me because, i use “very straight to the point” and short phrases/ sentences even in my regular communications so explaining the agent in too many words, in a detailed, clear way is a challenge but with this course, i understood what i need not explain the agent and how to structure my prompts to refine and pin point what I need.
really good course to start with!
And I learned, which I didn’t expect, the concept of tokens. The biggest difficulty is not having practical experience within the training, and the most useful thing I learned was the structuring of prompts.
“My A-ha! moment was understanding that tools are the ‘hands’ of the LLM . For a long time, I saw LLMs as just ‘brains in a jar’ that could only talk. Connecting them to search tools, calculators, or APIs turned that brain into an agent that can actually do work. It bridged the gap for me between generating text and executing real-world tasks.”
“My A-ha! moment was understanding that tools are the ‘hands’ of the LLM . For a long time, I saw LLMs as just ‘brains in a jar’ that could only talk. Connecting them to search tools, calculators, or APIs turned that brain into an agent that can actually do work. It bridged the gap for me between generating text and executing real-world tasks.”
Agreed. It is an experience!
My Takeaways from This Lesson
One thing that really clicked for me was how important it is to clearly define an agent’s role. It’s not just about getting answers; it actually shapes how the agent thinks and behaves. I also noticed that breaking tasks into clear steps makes a huge difference in how accurate and logical the output is.
What I struggled with at first was telling the difference between regular prompting and agent prompting With normal prompts, you ask and get a response. But with agents, you’re thinking more about processes and workflows, which took some time to understand. Seeing examples helped a lot.
The most useful lesson for me was learning how parameters like temperature and top-p affect responses. I used to think they only controlled creativity, but now I see how they also influence decision-making and consistency. My Takeaways from This Lesson
One thing that really clicked for me was how important it is to clearly define an agent’s role. It’s not just about getting answers; it actually shapes how the agent thinks and behaves. I also noticed that breaking tasks into clear steps makes a huge difference in how accurate and logical the output is.
What I struggled with at first was telling the difference between regular prompting and agent prompting With normal prompts, you ask and get a response. But with agents, you’re thinking more about processes and workflows, which took some time to understand. Seeing examples helped a lot.
The most useful lesson for me was learning how parameters like temperature and top-p affect responses. I used to think they only controlled creativity, but now I see how they also influence decision-making and consistency.
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This course has improved my knowledge of prompt engineering.