Google's AI Prompt Engineering Course Summary
Code Conversations18 Helmi 2025

Google's AI Prompt Engineering Course Summary

The YouTube video summarizes Google's prompt engineering course, emphasizing a five-step framework for effective prompt design: task, context, references, evaluate, and iterate.

This framework can be remembered using the mnemonic "Tiny crabs ride enormous iguanas". The course also covers four methods for iterating on prompts, which include revisiting the prompting framework, simplifying the prompt, trying different phrasing, and introducing constraints.

The course also explores multimodal prompting using various inputs like text, images, and audio, and introduces advanced techniques such as prompt chaining, Chain of Thought prompting, and Tree of Thought prompting.

Furthermore, it delves into the use of AI agents, specifically Agent Sim for simulations and Agent X for expert feedback, highlighting the importance of defining a persona, context, and conversation rules. The course stresses the need for a "human in the loop" approach, emphasizing the importance of verifying outputs to minimize hallucinations and biases.

https://youtu.be/p09yRj47kNM

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(144)

The 7 Skills You Need to Build AI Agents

The 7 Skills You Need to Build AI Agents

As AI agents become more capable, the skills needed for AI jobs are shifting. Bri Kopecki breaks down the 7 skills you need to move from prompt engineering to full agent engineering, including system ...

11 Elo 19min

What is LangChain?

What is LangChain?

LangChain became immensely popular when it was launched in 2022, but how can it impact your development and application of AI models, Large Language Models (LLM) in particular. In this video Martin Ke...

5 Elo 20min

LangChain vs LangGraph

LangChain vs LangGraph

Get ready for a showdown between LangChain and LangGraph, two powerful frameworks for building applications with large language models (LLMs.) Master Inventor Martin Keen compares the two, taking a lo...

30 Heinä 16min

RAG vs Agentic AI

RAG vs Agentic AI

Agentic AI and RAG are redefining how LLMs think and act 🤖. Live from TechXchange in Orlando, Martin Keen & Cedric Clyburn unpack how vector databases, data integration, and context engineering enabl...

23 Heinä 21min

RAG's Evolution

RAG's Evolution

How did search evolve into agentic AI? Sam Anthony explains RAG's evolution, from simple retrieval to adaptive systems powered by LLMs. Learn how semantic search, hybrid retrieval, and AI agents enabl...

16 Heinä 13min

AI Agent Skills

AI Agent Skills

We're all using AI agents, but they still lack the procedural knowledge real work needs. Martin Keen explains how agent skills, LLMs, RAG, and MCP help agents follow workflows, automate tasks, and mak...

9 Heinä 24min

MCP vs. RAG

MCP vs. RAG

How do AI agents learn and take action? Live from TechXchange in Orlando, Melissa Hadley breaks down how MCP and RAG help large language models connect to data — one to retrieve knowledge, the other t...

2 Heinä 20min

RAG vs Fine-Tuning vs Prompt Engineering

RAG vs Fine-Tuning vs Prompt Engineering

How do AI chatbots deliver better responses? Martin Keen explains RAG 🛠️, fine-tuning , and prompt engineering methods that extend knowledge, refine responses, and build domain expertise. Learn how t...

25 Kesä 20min

Suosittua kategoriassa Koulutus

rss-murhan-anatomia
psykopodiaa-podcast
voi-hyvin-meditaatiot-2
rss-vapaudu-voimaasi
kesken
rss-niinku-asia-on
rss-arkea-ja-aurinkoa-podcast-espanjasta
rss-liian-kuuma-peruna
rss-laadukasta-ensihoitoa
adhd-podi
aamukahvilla
rss-luonnollinen-synnytys-podcast
solu-ja-molekyylibiologian-perusteet
psykologia
jari-sarasvuo-podcast
rahapuhetta
ihminen-tavattavissa-tommy-hellsten-instituutti
rss-narsisti
rss-duodecim-lehti
dreamtalk