SKU: 29850975846

Necromunda: Escher Cutters

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Description

Necromunda: Escher CuttersThis multipart plastic kit builds four Escher Cutters, lightning fast jetbikes that can be added to any Escher gang. These ferocious flying machines boast a powerful front turbine with exposed engine cylinders, providing thrust for their sleek, bladed chassis. Each Cutter has a deadly gas trap launcher installed on its undercarriage, and sports a pair of mounted weapons on either side of the jetbike you can choose between twin linked grenade

This multipart plastic kit builds four Escher Cutters, lightning-fast jetbikes that can be added to any Escher gang. These ferocious flying machines boast a powerful front turbine with exposed engine cylinders, providing thrust for their sleek, bladed chassis. Each Cutter has a deadly gas trap launcher installed on its undercarriage, and sports a pair of mounted weapons on either side of the jetbike – you can choose between twin-linked grenade launchers, twin-linked heavy stubbers, or twin-linked plasma guns. The kit includes a choice of two different head designs and four interchangeable hairstyles, to give each of your Escher riders their own distinct appearance.

This set consists of 124 plastic components, and is supplied with 4x Citadel 60x35mm Oval Bases, each with a ball top flying stem. These miniatures are supplied unpainted and require assembly – we recommend using Citadel Plastic Glue and Citadel Colour paints.

Rules for using Escher Cutters in your games of Necromunda can be found in The Aranthian Succession: Cinderak Burning supplement.

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SKU: 29850975846

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B. Black
Louisville, US
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
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Reviewed in the United States on August 5, 2025
J
Joe Faith
Lake Worth, US
★★★★★ 5
Unlocking Practical AI: A Developer’s Guide to Building with LLMs and LangChain
Format: Paperback
If you're a developer eager to move beyond LLM experimentation and build robust, context-aware AI applications, this book offers both inspiration and practical guidance. The authors open with a clear passion for the transformative potential of large language models (LLMs) and LangChain, framing these technologies as not just enhancements to the developer’s toolkit, but as gateways to new kinds of “thing-building” superpowers. This sense of possibility is grounded in step-by-step instruction, making the book approachable for those with Python or JavaScript backgrounds who may be new to the world of production-grade AI agents. What stands out is the book’s careful scaffolding: starting with foundational concepts like prompt-based programming and progressing to advanced capabilities such as retrieval-augmented generation, agent planning, and tool integration. Each stage is contextualized with real-world use cases, like customizing chatbots to interact with your own documents, personalizing user experiences through memory, and deploying to production with reliability and security in mind. The focus on chain-of-thought reasoning and LangGraph’s agent architecture demonstrates the authors’ awareness of the current state of AI, where context and planning are just as important as raw language ability.
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Reviewed in the United States on July 17, 2025
T
Tom C Taulli
Fort Morgan, US
★★★★★ 5
Excellent Handbook
Format: Paperback
What got my interest in this book is the author. He's well-known as a leader in the LangChain world. And his book did not disappoint. It goes through the whole life cycle of development and there is a lot useful insights. If you are looking to build real-world genAI/agentic apps, then this book is certainly a great choice.
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Reviewed in the United States on April 11, 2025
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Lydia O
New York, US
★★★★★ 5
Useful resource!
Format: Paperback
I found this book well written and extremely useful for getting comfortable with LLMs for building AI apps in production and other agent driven applications.
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Reviewed in the United States on April 10, 2025
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Jacob Lee
Belleville, US
★★★★★ 5
Fantastic!
Format: Paperback
A great primer on getting started with LangChain concepts!
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Reviewed in the United States on April 10, 2025

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