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Description
High FiveOut of bail skippers and rent money, Stephanie Plum throws caution to the wind and follows in the entrepreneurial bootsteps of Super Bounty Hunter, Ranger, engaging in morally correct and marginally legal enterprises. So, a scumball blows himself to smithereens on her first day of policing a crack house and the sheik she was chauffeuring stole the limo. But hey, nobody's perfect Anyway, Stephanie has other things on her mind. Her mother wants her to
Out of bail skippers and rent money, Stephanie Plum throws caution to the wind and follows in the entrepreneurial bootsteps of Super Bounty Hunter, Ranger, engaging in morally correct and marginally legal enterprises. So, a scumball blows himself to smithereens on her first day of policing a crack house and the sheik she was chauffeuring stole the limo. But hey, nobody's perfect Anyway, Stephanie has other things on her mind. Her mother wants her to find Uncle Fred who's missing after arguing with his garbage company; homicidal rapist Benito Ramirez is back, quoting scripture and stalking Stephanie; vice cop Joe Morelli has a box of condoms with Stephanie's name on it; and Stephanie's afraid Ranger has his finger on her trigger. The whole gang's here for mirth and mayhem in Janet Evanovich's High Five. Read at your own risk in public places.Binding Type: Paperback
Publisher: St. Martin's Press
Published: 06/15/2000
ISBN: 9780312971342
Pages: 340
Weight: 0.37lbs
Size: 6.85h x 4.18w x 0.96d
Accelerated Reader Quiz #/Name: 87034 / High Five: A Stephanie Plum Novel
Reading Level: 3.9 / Interest Level: Upper Grade / Point Value: 11
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4.6 ★★★★★
Based on 1045 reviews
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Product Reviews
★★★★★ 5
Great book
Format: Paperback
Great book! It is helpful as I work towards my Masters of Science in Applied Artificial Intelligence
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Reviewed in the United States on December 20, 2025
★★★★★ 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.
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Reviewed in the United States on June 25, 2024
★★★★★ 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.
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Reviewed in the United States on June 25, 2024
★★★★★ 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
★★★★★ 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
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