SKU: 1054735708

Brass Buddha Statue Tibet Buddhism Stone Work For Home Décor 16"

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Brass Buddha Statue Tibet Buddhism Stone Work For Home Décor 16"Product Details : Product Code 62900 Width x Depth (Inches) 12 x 8 Inches Height (Inches) 16 Inches Weight (In Kg) 10. 4 Kg Material Brass Made In India USAGE: To decorate living room, pooja room, foyuer, altar, meditation room or entrance to your home or office. And can be placed on top of table or can be installed or placed anywhere indoor outdoor home garden. POSITIVE IMPACT: Founder of World Religion of Buddhism. Creates peaceful ambience filled

  • Product Details : Product Code - 62900 || Width x Depth (Inches) - 12 x 8 Inches || Height (Inches) - 16 Inches || Weight (In Kg) - 10.4 Kg || Material - Brass || Made In India
  • USAGE: To decorate living room, pooja room, foyuer, altar, meditation room or entrance to your home or office. And can be placed on top of table or can be installed or placed anywhere indoor/outdoor/home/garden.
  • POSITIVE IMPACT: Founder of World Religion of Buddhism. Creates peaceful ambience filled with harmony, spirituality and positive energy around us. And at the same time acts as magnificient piece of art and collectible.
  • GIFTING: An ideal gifting option to gift someone as a Wedding Gift/Anniversary Gift/Corporate Gift/Return Gift/Birthday Gift/Diwali Gift/Lucky Gift and a gift that can be given on all occassions like private parties or public community events.
  • Ships directly from our warehouse in Delhi. Prices in INR include cost of the product, applicable GST, packing charges, door delivery to your place in India.

Buddha, popular as the Enlightened one, was the philosopher, spiritual teacher, meditator, protector, mentor and the founder of Buddhism on earth. He is the one who was not born as a god but as an ordinary person, named Siddhartha. He got his name owing to his several years of meditation and the life of asceticism which eventually awakened him. His entire life story is the store flooded with many inspiring events that became the part of his journey towards renunciation.

According to the history, Buddha was born into a Sakya clan somewhere in North India, Lumbini towards southern borders of Nepal. He spent his childhood in Kapilavastu. Buddha was born to Suddhodana and Maya, and initially named Siddhartha Gautam. Suddhodana was the king of the local Sakya tribe where Siddhartha was the prince surrounded by all materialistic pleasures of life.

As we dive back into the life of Buddha, we would see that strong predictions about his life were already made by the priests. As per the common ritual, after the birth of the child a ceremony was kept to announce the name of the child. Suddhodana invited Brahmin priests for the ceremony during which one of the priests declared that he would become Buddha in future and renounce the world. After hearing such words from the priest, Suddhodana became careful and surrounded Siddhartha with all forms of luxuries.

He was always kept under the shadow by one man in his service. The best of food, clothes and things were served to him. The palace was well equipped with all sources of best entertainment from music to dance by prominent artists. Suddhodana assured that Siddhartha was kept away even from the thought of misery in every possible way.

At the age of sixteen Buddha was married to Yasodhara, who gave birth to his son named Rahul. His first encounter with misery was at the age of 29 when he went out of the palace in his chariot. Four events took place which transformed the life of Siddhartha. He saw an old age, a diseased body, a corpse and an ascetic. This was the time when his journey as Buddha began and he left the palace in search of a solution to all miseries.

After attaining Enlightenment Buddha started preaching others and spreading spiritual knowledge. His images as an ascetic sitting under Bodhi Tree with different postures of hands like blessing, teaching and touching the earth are very common as a symbol of peace and purity.

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SKU: 1054735708

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4.5 ★★★★★
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Verified Purchase
David Escobar
Omaha, US
★★★★★ 5
Good starting point. But can't find the code.
Format: Kindle
Reading chapter 3. It was so far so good, but can't find the code in the repo. "All the related code can be found in the repository under project/hooks-notification." And in the repo I see no project folder. Please help!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 3, 2026
W
Verified Purchase
WU.
Natrona Heights, US
★★★★★ 4
Good overview of the leading Agentic Framework. Will become outdated quickly.
Format: Paperback
3.5 Stars rounded up. Not a bad place to start if you need to get up to speed fast with Claude Code, understand its vast feature set, how it works under the hood, best practices, and the various agent primitives and how to get the most out of them. Agentic frameworks (Claude Code in particular) are quickly becoming table stakes for anyone working in tech, so it's best to start now. I appreciated the author's ability to flesh out areas where Anthropic's documentation is lacking in depth and nuance, and for some not already working with Claude in their own repos, the fact that he provides "toy" repos where one can experiment with the tools without fear of consequence. Where the book falls short is that most of the stuff in here is already covered pretty well already in Anthropic's docs, or even better so in their free "Skilljar" courses. What's more, some areas are given a bit of a shallow treatment, while others are a bit better done. So it's a bit inconsistent in that sense. Also, I can see how this book will quickly lose its currency in a few months at the pace things are going. Ultimately, for me, the price of this book was a bit rich for my liking given the criticisms above. Still, I feel like I got valuable info that rounded up what I already knew from working with this agentic framework. Recommended.
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Reviewed in the United States on May 28, 2026
B
Brahmananda Reddy
Phoenix, US
★★★★★ 5
Practical AI Engineering Beyond Prompts — One of the Better Books on Agentic Coding
Format: Paperback
This book is not another “AI coding hype” book. A lot of books talk about agents at a very high level. This one actually explains how things work when you try to use them inside real development workflows. That was the biggest difference for me. What I liked most was the focus on context engineering, memory, MCP, hooks, subagents, and workflow orchestration instead of just “prompt better.” The author spends time explaining why long-running agent systems fail, how context grows over time, and why most AI coding setups become messy without structure. The examples also feel practical — The HookHub project, Next.js setup, GitHub workflows, Claude memory files, and MCP integrations make it easier to connect theory with actual implementation. From my retail domain experience perspective, I could immediately connect this to forecasting and pricing workflows. For example: * agents helping analysts generate specs before model development * automated code review for promo forecasting pipelines * isolated subagents for pricing, promotions, assortment * persistent memory for business rules across teams * MCP integrations to pull context from internal systems safely The section around context isolation and subagents especially stood out because that is very similar to how enterprise forecasting teams already operate in reality. Different teams own different decision spaces. One thing I appreciated: the author does not oversell AI. There is a strong focus on constraints, context pollution, hallucinations, performance degradation, and workflow reliability. That makes the book feel grounded instead of marketing-heavy. This is not for complete beginners though. If someone has never worked with Git, APIs, coding agents, or LLM workflows, parts of the book may feel overwhelming early on. The author clearly says this is not beginner-level content. Overall, probably one of the more practical books I have read recently on agentic coding systems. Good for: * software engineers * AI engineers * enterprise architecture teams * technical product teams * analytics leaders trying to operationalize AI development workflows Especially useful if your organization is trying to move from “AI demos” into actual production workflows.
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Reviewed in the United States on May 20, 2026
U
UA
Louisville, US
★★★★★ 5
A Good Reality Check on How AI Agents Actually Work in Enterprise Systems
Format: Paperback
Most AI books stop at prompts. This one goes deeper into how agent systems actually behave once you try to use them inside large workflows with memory, tools, permissions, automation, and multiple agents working together. That part felt very relevant for healthcare and enterprise environments. The book does a good job explaining why context engineering matters and how poor context handling creates hallucinations, inconsistent outputs, and degraded performance over time. Honestly, that is one of the biggest problems organizations underestimate right now. In healthcare workflows, context matters a lot: * prior interactions * business rules * auditability * escalation logic * safety constraints * tool permissions * workflow boundaries The sections on persistent memory, scoped context, subagents, and structured workflows connected strongly to that reality. I work in enterprise analytics, and while reading this book I kept thinking about use cases like: * pharmacy workflow automation * prior authorization support systems * coding assistants for healthcare engineering teams * AI copilots for operational analytics * agent-based escalation systems * claims and workflow orchestration The MCP chapters were also useful because they explain integration challenges clearly instead of treating tooling as magic. What made this book stand out for me was the balance between implementation and architecture. The author explains: * why long contexts fail * how context poisoning happens * why isolation matters * when parallel agents help * when they actually create more complexity That level of honesty is missing in many AI books right now. Another thing: the examples are not overly academic — The Next.js project setup, GitHub automation, Claude desktop workflows, memory systems, hooks, and subagents make the learning process feel practical and hands-on. One limitation: this book assumes technical background. Someone completely new to coding agents, LLMs, Git, or development workflows may struggle in the first few chapters. But for engineers, AI teams, enterprise architects, and technical leaders trying to understand where agentic coding is actually going, this book is worth reading. Especially for organizations trying to operationalize AI safely instead of just experimenting with chatbots.
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Reviewed in the United States on May 20, 2026
C
Christopher West
Massapequa, US
★★★★★ 5
Great book! Practical and for developers that already use AI!
Format: Paperback
I purchased "Agentic Coding" by Claude Code due to my desire for an alternative to generic "Prompt Template" type resources related to AI-based development. This book accomplishes just that. As opposed to merely viewing Claude Code as a "magic box", the author has explained how to utilize it in conjunction with other actual development processes. The authors' emphasis on "context engineering" (i.e., structuring data/information; managing knowledge in a project; guiding an AI agent to produce consistent results vs. producing random/unknown results) represents the strongest component of the book. It should be noted that the book appears to be intended primarily for experienced developers with prior experience in software development and/or familiarity with AI-based development tools. Should you be familiar with Git, the command-line interface, and/or modern development processes, you may find this resource very helpful. Conversely, I did appreciate the fact that there were no novice-oriented descriptions provided throughout the book. The aspect of the book that I found most valuable, however, is the extremely pragmatic nature of the material contained within. The examples illustrated through developing/maintaining CLAUDE.md files; utilizing Claude Code in combination with GitHub Workflows; employing MCP Servers; and creating multi-agent or sub-agent workflows all seemed to reflect a clear focus on "real world usage" rather than theoretical constructs. In addition, each chapter builds upon previous chapters in such a manner as to provide a logical progression through which the reader can easily understand and ultimately implement the concepts learned. I also appreciated that the author included guidance on responsible utilization of the tool(s), as well as maintaining control over what changes are made by the agent. While numerous books regarding AI focus solely on what AI tools can accomplish, this book addresses both how to utilize these tools effectively in a real codebase, as well as responsibility and safety considerations. In summary, this is not a book for individuals completely inexperienced in either programming or generative AI. However, if you are currently experimenting with tools such as Claude, Cursor, GitHub Actions, or MCP, this is likely one of the more useful and practical books available on the subject. Recommended for software engineers seeking to transition from simply "prompting an AI" into establishing a repeatable/professional workflow process surrounding agentic coding.
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Reviewed in the United States on April 11, 2026

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