Devconf.US

How To Win Friends & Influence LLMs (with Prompt Engineering)
08-15, 10:00–11:20 (US/Eastern), Terrace Lounge (capacity 48)

Part art, part science, prompt engineering is the process of crafting input text to fine-tune a given large language model for best effect.

Foundation models have billions of parameters and are trained on terabytes of data to perform a variety of tasks, including text-, code-, or image generation, classification, conversation, and more. A subset known as large language models are used for text- and code-related tasks. When it comes to prompting these models, there isn't just one right answer. There are multiple ways to prompt them for a successful result.

In this workshop, you will learn the basics of prompt engineering, from monitoring your token usage to balancing intelligence and security. You will be guided through a range of exercises where you will be able to utilize the different techniques, dials, and levers illustrated in order to get the output you desire from the model. Participants of this workshop will be equipped with a comprehensive understanding of prompt engineering along with the practical skills required to achieve the best results with large language models.

See also: PowerPoint Presentation (1.1 MB)

James Busche is a senior software engineer in the IBM Open Technologies Group, currently focused on the Open Source CodeFlare project. Previously, James has been a DevOps Cloud engineer for IBM Watson and the worldwide Watson Kubernetes deployments.

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