Mildly annoyed by the big green owl's limitations, I decided to build Translamore - an app that lets you turn whatever you're reading into your own language exercises. What started as a small weekend project quickly turned into a full-blown side quest. I'll kick things off with a quick demo of Translamore and then share some of the lessons from building it in my spare time: Project Management: staying organized when no one's watching, figuring out what's worth your time, keeping motivation alive, and the few tools that saved my sanity; LLMs & Prompt Engineering: what actually worked for me, using unit tests to wrangle prompts, a bit of templating magic, and my Prompt Resolver contraption; Server-Side Dart: why you really shouldn't ship your LLM API keys, how I structured packages and dependencies, used sealed classes for the API, and yes - called Python from Dart in the least elegant way possible. Expect some lessons, a few confessions, and probably one or two dont do what I did moments.

In this session, we’ll show how to structure and deliver the right context to large language models (LLMs) so they can actually reason through tasks - not just retrieve answers. We'll show practical ways to provide context across prompts and tools, using a Model Context Repository to make your AI apps much smarter.

This 2-hour intensive session provides a foundational and practical guide to the burgeoning field of prompt engineering. As large language models become a core part of professional workflows, the ability to communicate with them effectively is crucial. This course will demystify the art and science of crafting powerful prompts.\n\nWe'll move beyond simple queries and introduce you to the fundamentals of structured prompting, showing you how small changes can lead to dramatically better results. You will learn to optimize your prompts for clarity, specificity, and control to ensure the AI delivers the responses you need.\n\nBy the end of this session, you'll be able to:\n- Recognize the limitations of basic prompting and avoid common trial‑and‑error pitfalls.\n- Apply key prompting techniques for enhanced control, accuracy, and repeatable results.\n- Understand the shift to programmatic prompt engineering, exploring how templates and automation optimize AI workflows.\n- Power advanced AI applications like Retrieval‑Augmented Generation (RAG) and Agentic AI.\n- Improve AI reasoning and decision‑making, learning how advanced techniques can reduce hallucinations and improve logical output.

This 2-hour intensive session provides a foundational and practical guide to the burgeoning field of prompt engineering. As large language models become a core part of professional workflows, the ability to communicate with them effectively is crucial. This course will demystify the art and science of crafting powerful prompts.

We'll move beyond simple queries and introduce you to the fundamentals of structured prompting, showing you how small changes can lead to dramatically better results. You will learn to optimize your prompts for clarity, specificity, and control to ensure the AI delivers the responses you need.

By the end of this session, you'll be able to: - Recognize the limitations of basic prompting and avoid common trial-and-error pitfalls. - Apply key prompting techniques for enhanced control, accuracy, and repeatable results. - Understand the shift to programmatic prompt engineering, exploring how templates and automation optimize AI workflows. - Power advanced AI applications like Retrieval-Augmented Generation (RAG) and Agentic AI. - Improve AI reasoning and decision-making, learning how advanced techniques can reduce hallucinations and improve logical output.

This 2-hour intensive session provides a foundational and practical guide to the burgeoning field of prompt engineering. As large language models become a core part of professional workflows, the ability to communicate with them effectively is crucial. This course will demystify the art and science of crafting powerful prompts. We'll move beyond simple queries and introduce you to the fundamentals of structured prompting, showing you how small changes can lead to dramatically better results. You will learn to optimize your prompts for clarity, specificity, and control to ensure the AI delivers the responses you need. By the end of this session, you'll be able to: - Recognize the limitations of basic prompting and avoid common trial-and-error pitfalls. - Apply key prompting techniques for enhanced control, accuracy, and repeatable results. - Understand the shift to programmatic prompt engineering, exploring how templates and automation optimize AI workflows. - Power advanced AI applications like Retrieval-Augmented Generation (RAG) and Agentic AI. - Improve AI reasoning and decision-making, learning how advanced techniques can reduce hallucinations and improve logical output.

This 2-hour intensive session provides a foundational and practical guide to the burgeoning field of prompt engineering. As large language models become a core part of professional workflows, the ability to communicate with them effectively is crucial. This course will demystify the art and science of crafting powerful prompts.

We'll move beyond simple queries and introduce you to the fundamentals of structured prompting, showing you how small changes can lead to dramatically better results. You will learn to optimize your prompts for clarity, specificity, and control to ensure the AI delivers the responses you need.

By the end of this session, you'll be able to: - Recognize the limitations of basic prompting and avoid common trial-and-error pitfalls. - Apply key prompting techniques for enhanced control, accuracy, and repeatable results. - Understand the shift to programmatic prompt engineering, exploring how templates and automation optimize AI workflows. - Power advanced AI applications like Retrieval-Augmented Generation (RAG) and Agentic AI. - Improve AI reasoning and decision-making, learning how advanced techniques can reduce hallucinations and improve logical output.

Learn Day session on advanced prompt engineering and a quick review of AI fundamentals.

Live, end-to-end demonstration of Firebase Studio and Gemini Code Assist, taking an idea from a natural language prompt to a production-ready application. Includes collaboration on features and architecture, full-stack code generation, deployment, and a live URL.

What meta prompting techniques drive better code quality and maintainability?

Introductory session covering mental models of LLMs, prompt engineering techniques, and evaluation of LLMs. Modules include How LLMs are trained; Prompt Engineering; Evaluating LLMs.

How can we influence quality during the prompt creation stage, as well as how to work with already-generated text—improving it, identifying errors, and filtering out undesirable results. We'll explore linguistic approaches that help achieve better, more controlled outcomes from LLMs.

Techniques to build AI applications using prompt engineering and pre-trained models without custom model training.

Overview of generative AI concepts and prompt engineering as foundation for building AI applications.

When working with Large Language Models (LLMs), how do we ensure a probabilistic blob of text is something our code can actually use? In this talk, we explore how Pydantic emerged at a perfect moment exactly for this task; bridging Python's flexibility with the structured data needs of modern AI applications. We will introduce Pydantic and then demonstrate practical applications of it; from prompt engineering and parsing responses, to example of robust function calling and tool chaining via APIs.

Hands-on exercises comparing weak vs. strong prompts

Hands-on exercises comparing weak vs. strong prompts

Learn how to build and manage robust AI infrastructure using Kong AI Gateway for efficient GenAI application development and deployment. From AI Gateway essentials to advanced management techniques, you'll learn to optimize your applications, implement governance and security measures, and adapt to various deployment environments.

In this session you will discover how to create, and fine-tune prompts for a diverse range of AI models on AWS, leveraging fundamental principles of prompt engineering. Whether you're a seasoned AI enthusiast or just stepping into the realm of artificial intelligence, this session promises to equip you with fundamental concepts and practical techniques to enhance your prompt engineering skills. What you will learn: Foundation models and large language models; Key concepts of prompt engineering; Basic prompt techniques; Zero-shot prompting; Few-shot prompting; Chain-of-thought prompting.

Self-paced: Introduction to Prompt Engineering and LLM Fundamentals.