SKU: 67521963985

HEUTE / Everyday Espresso Blend

Sale price$12.60 Regular price$14.00
Save 10%

Pay in installments of $3.50 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Aug 6 - Aug 11

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

HEUTE / Everyday Espresso BlendHazelnut, Milk Chocolate, Cherry Roast Level: Recommended Brew Methods: The Heute Blend is an everyday espresso, suitable to be enjoyed by everyone from the seasoned coffee professional to those seeking just a good cup of morning joe. The components of this blend change seasonally, allowing us to always use coffees that are fresh and taste good. While the coffees themselves may change, we aim to always keep the Heute Blend balanced, sweet and easy to

Hazelnut, Milk Chocolate, Cherry

Roast Level:

Recommended Brew Methods:

The Heute Blend is an everyday espresso, suitable to be enjoyed by everyone from the seasoned coffee professional to those seeking just a good cup of morning joe. The components of this blend change seasonally, allowing us to always use coffees that are fresh and taste good. While the coffees themselves may change, we aim to always keep the Heute Blend balanced, sweet and easy to use.

Brazil Cafeina Women’s Group - Natural - 70%

Ethiopia Tullu Demtu - Washed - 10%

Colombia Asociativo Cauca Piendamó - Washed - 10%

Colombia Asociativo Huila Palestina - Washed - 10%

Tasting Notes: Hazelnut, Milk Chocolate, Cherry

Cafeina Women’s Group In 2019, a group for female farmers was established within the Cocatrel Cooperative in Três Pontas, Sul de Minas, Brazil. Known as the Cafeina Women's Group, it comprises of over 1,100 women producers. The initiative aims to promote active participation by women in decision-making processes. Every two months, the group gathers to further their education, expand their knowledge, and enhance their visibility and involvement within the coffee-growing community. The group is led by Iandra Vilela, an award-winning advocate for women in coffee.
This particular coffee is a natural-process lot consisting of the Mundo Novo and Yellow Catuaí varieties. It is machine-harvested, with the beans sorted by grade before being dried on patios for 7–10 days. After drying, the coffee rests for 30 days, then is hulled and delivered to the cooperative. Sourced through our long-standing import partners at Falcon, this coffee forms the foundation of our espresso blend, contributing rich nutty and milk chocolate notes.

Tullu Demtu the name of a nearby mountain - traces its roots back to 1945, when Mr. Aaga Dinsa established a coffee farm in Kuri Kebele. His commitment to quality and tradition was passed down to his son, Mr. Fikadu Aaga, who continued to nurture the family farm while supplying high-quality coffee to local markets. In 2015, inspired by this rich heritage, Mr. Habtamu Fikadu founded Kuri Mountain Coffee with the vision of elevating the family legacy to new heights. The company revitalised the original farm and built a state-of-the-art processing facility in Gidami town, blending traditional values with modern innovation. In 2025, Kuri Mountain further strengthened its operations by opening its own dry mill in Addis Ababa, allowing greater control over every stage of the supply chain. This Grade 4 coffee is sourced from farmers located around the Hambela and Uraga areas of the Guji Zone. In total, Kuri Mountain works with nearly 400 farmers cultivating over 1,000 hectares of land. For G4 production, the company purchases carefully selected dry cherry (Jenfel) directly from farmers, primarily from its outgrower network. Selection is meticulous and based on colour, maturity, and odor, as not all Jenfel meets the quality standards required for Grade 4. Once selected, the coffee is milled at the Gidami site to remove the dried cherry husk. It is then transported to Addis Ababa, where it undergoes final milling and preparation for export.

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: 67521963985

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.7 ★★★★★
Based on 10 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
O
Om S
Carnegie, 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
Grantham, 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
Lake Worth, 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
Grantham, 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
Battle Creek, 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

recommand products