Learning is better when it’s shared—and you’ve just explored the agentic twist on prompt engineering!
With this occasion, we invite you to share your “A-ha!” moments with us and fellow learners. If it’s easier for you to take some time and reflect on this lesson with some guidance, don’t hesitate to refer to one or more of the following questions:
What did I learn and did not expect?
What was difficult for me and how did I overcome it?
What is the most useful thing that I learned in this lesson?
Feel free to share with us and your peers whatever comes to your mind!
Agent memory and task chaining are game-changers.
The moment I saw how an agent can remember prior steps and build on them across tasks, it clicked: this is how AI moves from single-use tools to true digital co-workers.
Treating prompts as user experience design opened my eyes. Every prompt is a choice that affects how the agent reasons, behaves, and prioritizes goals.
Agentic Prompt engineering framework course not only touches the basic briefing about what are prompts and LLM Tokens, But also goes beyond with evaluation parameters for a better prompt. It teaches us various types of prompts, in depth explanation and example about System and User prompts as well as the the various parameters it will get evaluated on. It also throws light on how to choose your LLM.
Completed an AI Prompt Engineering course where I gained a solid understanding of prompt design techniques including zero-shot , one-shot , and few-shot prompting strategies.
I also learned best practices for structuring both system and user prompts to optimize performance and accuracy across various LLM applications
Just Now Completed the Agentic Prompt engineering course which is very important for every knows because right now AI is very advanced it helps to career growth and Upskill as Automation Developer. We can easily Understand like LLM,Embedding, Tokens, Traditional prompt vs AI Agentic prompt and many more .
I was actually waiting for this course to be available in academy. This would be very much helpful for the associates who are starting new with Agent (or agentic or AI Agents).
For your questions
What did I learn and did not expect?
Agent prompting (new term, though we know prompt in general) and traditional prompting. I did not expect it covered the Touching up on the LLM basics , parameters to choose. It would be great if you would have given some public sources to learn the current llm in market and its bench mark to link this parameters would be a good help.
What was difficult for me and how did I overcome it?
The difficult part is how we optimize the prompt and I realize the autopilot in agent builder would assist here. The good part is it uses the training data to suggest on the better prompts. Interesting.
What is the most useful thing that I learned in this lesson?
Agent Prompt and Traditional Prompt differences. Its a good one, though we know when such questions comes this actually helps to elaborate.
I was looking for courses and documentation to really help me getting better with prompts and we have the course just right there now!!
The course provides understanding on what prompt engineering is concepts like zero-shot prompt, chain of thought prompt really provide a deep understanding on to get best from LLMs.
The course also dove deeper in making us understand about System and User Prompt which helps in clearing defining roles of the agent and get the best out the agent.
Overall this the only course you need to level up your game and start building your agents.
Kudos to the team who designed the course and explaining concepts in clear, concise way to be understood by beginners as well.