SKU: 95665884741

Blue Stripe iPhone 14 Pro Case – Edwardian Summers | MagSafe

Sale price$40.46 Regular price$44.95
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Description

Blue Stripe iPhone 14 Pro Case – Edwardian Summers | MagSafeSlim double pinstripes in deep burgundy run vertically over a pale duck egg blue, evenly spaced and beautifully restrained. There's a tailored, garden party ease to it, soft yet smart. The palette feels like faded summer linen. Preppy and refined, the kind of stripe that never goes out of fashion. Designed for iPhone 14 Pro. CoreShock 10ft Drop Protection our signature drop protection technology, built into the case. You won't see it. Your phone won't

Slim double pinstripes in deep burgundy run vertically over a pale duck-egg blue, evenly spaced and beautifully restrained. There's a tailored, garden-party ease to it, soft yet smart. The palette feels like faded summer linen. Preppy and refined, the kind of stripe that never goes out of fashion. Designed for iPhone 14 Pro.

CoreShock™ 10ft Drop Protection — our signature drop-protection technology, built into the case. You won't see it. Your phone won't feel a thing.

MagSafe Ready — N52 magnets, 1600g hold. Snaps onto chargers and car mounts first try, every time.

Soft Microfibre Lining — a smooth inner layer that keeps the back of your phone safe from scuffs, scratches, and daily wear.

Glossy finish with scratch-resistant coating — colours stay bright and the design stays fresh, even months down the line.

Printed in our London studio. Made with 50% recycled materials. Every order ships in a gift box with a velvet pouch. If it's for someone else, you don't need to wrap it.

Why this is the best iPhone 14 Pro case

Designed to fit the iPhone 14 Pro precisely — every port, button, and camera cut-out lines up exactly where it should. It stays slim enough to slip into a pocket while CoreShock™ takes the hits a phone actually takes: the kitchen floor, the car park, the bottom of a bag. Because the print sits under a scratch-resistant gloss, the art that made you choose it still looks new months later. No bulk, no compromise — protection you forget is there until you need it.

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SKU: 95665884741

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4.3 ★★★★★
Based on 20 reviews
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P
Paul Pollock
San Leandro, US
★★★★★ 5
Your Blueprint for Building Smarter AI!
Format: Paperback
If you're building AI and sometimes feel a bit lost, "LLM Design Patterns" by Ken Huang is like finding the secret map you've been searching for. Ken Huang, who clearly knows his stuff (he's a renowned AI expert and works with big names like OWASP and NIST), writes in a way that just clicks, without getting bogged down in super-dense tech talk. The author even acknowledges using AI to make the language clearer for a smooth reading experience! This book covers everything you need, from getting your data squeaky clean to making AI agents that can actually think and act autonomously. For me, the parts on Retrieval-Augmented Generation (RAG) and advanced ways to 'talk' to your AI (prompting) were particularly eye-opening and immediately useful for my projects. Plus, it has handy code snippets that really help you grasp the ideas. While they're not ready for direct production copy-pasting, they illustrate the concepts perfectly for learning. It's not for absolute beginners – you'll want some basic Python and machine learning smarts to get the most out of it – but the effort is totally worth it. It even delves into making sure your AI is fair and unbiased, which was a real lightbulb moment for me. This book is crammed with actionable advice; it's less about abstract theory and more about real-world solutions you can actually use. If you're serious about building impressive AI systems professionally, this is a must-read.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 7, 2025
A
Allen Wyma
Massapequa, US
★★★★★ 5
Great Resource when Integrating AI
Format: Kindle
This is a great resource when building systems that integrate with AI. It manages to cover the entire lifecycle and even tips for corporate environments!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 26, 2025
O
Om S
Natrona Heights, 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
Port Orchard, 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
Grantham, 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

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