| # Hands-On AI: Building and Deploying LLM-Powered Apps | |
| This is the repository for the LinkedIn Learning course `Hands-On AI: Building and Deploying LLM-Powered Apps`. The full course is available from [LinkedIn Learning][lil-course-url]. | |
| _See the readme file in the main branch for updated instructions and information._ | |
| ## Lab6: Prompt Engineering | |
| With the prompt templates extracted from the code, we can iterate on the prompts to fix the problem that we have observed! | |
| Please iterate on the prompts and ensure the model can respond properly to our sample question. | |
| ## Exercises | |
| Please find a prompt in our Chainlit application's playground that ensures our sample question is answered properly. And then edit `prompt.py` with the newly discovered/engineered prompt. | |
| ## References | |
| - [Prompt Engineering vs Blind Prompting](https://mitchellh.com/writing/prompt-engineering-vs-blind-prompting) | |