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Interruptor de Llave Tubular / Diseño "See-Saw'"Anti retorcimiento / Carcasa de Aleación de Zinc Cromado / Contactos Plateados con Tratamiento Anti-Sulfuración / Base de Bachelita / Terminales Redondos / 2A@12VDCEl interruptor de llave tubular de SECO LARM ofrece un diseo patentado 'see saw' que asegura un contacto confiable y autoajustable en todo momento. Su construccin 'pick proof' evita la manipulacin no autorizada, garantizando seguridad y durabilidad. Esta solucin est concebida para aplicaciones que demandan una operacin robusta en entornos exigentes. Especificaciones Caractersticas Principales: Diseo patentado 'see saw' que asegura un contacto

Interruptor de Llave Tubular / Diseo "See-Saw'"Anti retorcimiento / Carcasa de Aleacin de Zinc Cromado / Contactos Plateados con Tratamiento Anti-Sulfuracin / Base de Bachelita / Terminales Redondos / 2A@12VDC
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SKU: 65885647426

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4.5 ★★★★★
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J
Verified Purchase
James Gianoglio
Chelsea, US
★★★★★ 5
Comprehensive Guide with Practical Insights
Format: Paperback
This is a solid book for understanding the art and science of working with LLMs and other generative AI models. I always struggled with getting the output I was looking for, and wasn't sure how best to "ask" the models for what I wanted. This book did a great job of laying out the strategies and practical guidance to craft the prompts. There were a lot of tips and tricks, but the overall understanding and framework around prompt engineering has been super useful.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 25, 2024
M
Verified Purchase
Matt B
San Leandro, US
★★★★★ 5
A must read!
Format: Paperback
Hands down, the best book on prompt engineering and implementing LLMs. Really enjoyed Michael and James deep dive. Whether you're technical or not, this book is foundational to a deeper understanding in how to properly explore and implement LLMs.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 25, 2024
S
Verified Purchase
SR
Chelsea, US
★★★★★ 4
Helpful for GPT/LangChain framework
Format: Paperback
I applaud the authors for putting forth a comprehensive introduction in a rapidly evolving space. I absorbed a lot, helpful as I was developing a prototype — using open source methods. And that’s where I was disappointed. The LLM and examples are highly adapted to OpenAI’s GPT-x and the bulky LangChain framework, something not obvious until you dig in to the book. Sure, this may be where newbie demand was when the authors began writing. But as the open source models and OpenAI alternatives gain speed (e.g. Llama 3.1, Groq, etc.) this book may quickly need an updated and expanded version to stay relevant.
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Reviewed in the United States on August 7, 2024
K
Verified Purchase
K. Wain
Charlottesville, US
★★★★★ 3
Good concepts, but uneven depth
Format: Paperback
Some helpful prompt frameworks, but parts felt repetitive and a few sections stayed too high-level for advanced users. Beginners will likely benefit more than experienced practitioners. If you’re new to prompt engineering it’s a decent starting point; if you’re already building structured prompts daily, it may feel light.
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Reviewed in the United States on January 17, 2026
K
Verified Purchase
Kevin Barry
Houston, US
★★★★★ 5
Necessary book to actually get value from AI tools
Format: Kindle
If you don't know how to prompt AI models correctly, you're missing out on substantially better results. This book has literally everything I could have asked for, it's an awesome resource.
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Reviewed in the United States on June 21, 2024

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