SKU: 35975687766

eBike Strike Big Boy - Army Green - In a Box

$382.05 $424.50
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Ships within 48 hours · Estimated delivery Aug 6 - Aug 11

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Description

eBike Strike Big Boy - Army Green - In a BoxStrike Big Boy Electric Bike Strike authorized dealer in San Diego & EscondidoTemecula eBike Shop supports riders in Escondido, San Diego, and the wider Southern California area with local pickup options alongside nationwide shipping. Designed with compact urban riding in mind, the Strike Big Boy Army Green In a Box combines approachable size, practical utility, and everyday electric bike convenience. Its responsive motor works with responsive power

Strike Big Boy Electric Bike

Strike authorized dealer in San Diego & Escondido

Temecula eBike Shop supports riders in Escondido, San Diego, and the wider Southern California area with local pickup options alongside nationwide shipping.

Designed with compact urban riding in mind, the Strike Big Boy - Army Green - In a Box combines approachable size, practical utility, and everyday electric-bike convenience. Its responsive motor works with responsive power delivery and electric assist to provide smooth assistance up to 19mph, while a practical battery system and 30 Miles make it a strong fit for shorter daily trips. Its compact proportions help keep the ride manageable and approachable. compact wheels and city-friendly proportions help the bike stay practical for everyday use.

Key Features

  • 350W High-Speed Brushless Motor: Efficient electric assistance designed for responsive, everyday riding.
  • 36V 10Ah Lithium Battery: Balanced power system built for dependable rides and consistent performance.
  • 16" x 4.0 Fat Tire Setup: Wide footprint for a planted feel across road, dirt, and boardwalk surfaces.
  • LCD Display: Clear, at-a-glance ride information while you’re on the move.
  • Disc Brakes: Confident braking performance for daily riding.
  • Steel Frame: Sturdy construction suited to casual cruising and regular use.

Specifications

Feature Details
Motor 350W High-Speed Brushless Motor
Battery 36v 10ah Lithium
Display LCD Display
Brake Disc Brake
Tire Size 16"x4.0 Fat Tire
Frame Steel
Max Speed 19mph
Range 30 Miles
Load Capacity 180lbs

Assembly & Build Options

In a Box (Factory-Sealed)

The “In a Box” option is delivered in the manufacturer’s original packaging and arrives unassembled.Professional assembly will be required prior to riding, including proper installation, torque verification,and a full safety inspection of all components.

This option does not include assembly services, safety inspection, tuning, or ongoing service support from our retail location.All warranty claims, technical support, and product-related concerns must be handled directly with Strike through the manufacturer’s official support channels.

Warranty & Manual

Manufacturers Warranty: https://strikecycles.com/pages/warranty

Why Choose This Model?

What helps the Strike Big Boy - Army Green - In a Box stand apart is the way it combines compact proportions with practical electric-bike capability. With its responsive motor, speeds up to 19mph, compact setup, its battery system, and 30 Miles, it presents a useful balance of approachability and everyday function.

Customers shopping with Temecula eBike Shop may appreciate how naturally it fits into short trips, errands, and everyday transportation.

Explore More

Discover more city-focused and everyday-ready eBikes at Temecula eBike Shop, where practical features and rider-friendly design help shape the overall selection.

Temecula eBike Shop supports local riders in Escondido and San Diego while also giving customers nationwide access through shipping available across the USA.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 35975687766

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4.6 ★★★★★
Based on 16 reviews
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Product Reviews
O
Om S
Port Orchard, US
★★★★★ 4
Title: Really Good Book for Learning LLMs
Format: Paperback, Format: Paperback
I picked up this book after struggling with LLM implementation at work. Ken Huang explains things clearly without too much technical jargon. The book covers everything from data preparation to building AI agents. I especially liked the chapters on RAG and prompting techniques - they helped me improve my current projects. The code examples actually work, which is nice. Some parts are pretty advanced, so you need basic Python knowledge. I had to read a few chapters twice to fully get it. The fairness and bias detection section was eye-opening. Good practical advice throughout. Not just theory - real solutions you can use. Worth the money if you're serious about LLM development. Recommended for anyone building AI systems professionally.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 25, 2025
J
Jiewen Wang
Los Angeles, US
★★★★★ 5
a comprehensive guide at the intersection of generative AI and cybersecurity
Format: Kindle
This book blends deep theoretical foundations with practical frameworks and forward-looking strategies. From adversarial risk models to actionable guidance using OWASP Top 10 for LLMs and the NIST AI RMF, it offers both technical depth and operational clarity. What makes it stand out is its balance of academic rigor and real-world CISO insights, providing a holistic perspective on securing GenAI systems. While it leans enterprise-focused, the content remains accessible to security engineers, risk managers, and policy leaders alike. Generative AI Security is a timely and essential read for anyone working to deploy GenAI responsibly—building systems with both power and integrity in today’s fast-evolving threat landscape.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 2, 2025
N
Nader
Belleville, US
★★★★★ 1
Light on substance and heavy on flaws
Format: Paperback
The book has a great list of topics, but fails to provide much substance any of them. Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!) Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples). Seems like the book was rushed, and the author has limited hands on experience (if any). At least we know based on the amount of flaws that it was not written by an LLM
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
Dallas, US
★★★★★ 5
Excellent book to truly understand LLM design patterns
Format: Paperback
I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket! Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC. - How to prepare your data for training by making it extremely clean. Developing the brains: the practical aspects of training, optimizing, and maintaining your models. - Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities. Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise. - It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!) Really, this feels like a useful toolkit, so Ken thank you for that resource Thanks, Idan Habler
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 9, 2025
R
Ryan Meyer
West Palm Beach, US
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on. That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks. Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 10, 2025

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