SKU: 59160227373

Clevite Tri Armor Chevrolet V8/ 293-325-346-364/ 1997-00 Main Bearing Set

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Description

Clevite Tri Armor Chevrolet V8/ 293-325-346-364/ 1997-00 Main Bearing SetClevite Tri Armor Chevrolet V8 293 325 346 364 1997 00 Main Bearing Set This Part Fits: Year Make Model Submodel 2008 2009 Buick LaCrosse Super 2004 2007 Buick Rainier CXL 2004 2005 Buick Rainier CXL Plus 2004 2007 Cadillac CTS V 2002 2014 Cadillac Escalade Base 2009 2013 Cadillac Escalade Hybrid 2010 2013 Cadillac Escalade Hybrid Platinum 2011 2014 Cadillac Escalade Luxury 2008 2014 Cadillac Escalade Platinum 2011 2014 Cadillac Escalade Premium 2003

Clevite Tri Armor Chevrolet V8/ 293-325-346-364/ 1997-00 Main Bearing Set

This Part Fits:

Year Make Model Submodel
2008-2009 Buick LaCrosse Super
2004-2007 Buick Rainier CXL
2004-2005 Buick Rainier CXL Plus
2004-2007 Cadillac CTS V
2002-2014 Cadillac Escalade Base
2009-2013 Cadillac Escalade Hybrid
2010-2013 Cadillac Escalade Hybrid Platinum
2011-2014 Cadillac Escalade Luxury
2008-2014 Cadillac Escalade Platinum
2011-2014 Cadillac Escalade Premium
2003-2006,2009-2010 Cadillac Escalade ESV Base
2009-2010 Cadillac Escalade ESV Platinum
2002-2006,2009-2010 Cadillac Escalade EXT Base
2013 Chevrolet Avalanche Black Diamond LS
2013 Chevrolet Avalanche Black Diamond LT
2013 Chevrolet Avalanche Black Diamond LTZ
2007-2010,2012 Chevrolet Avalanche LS
2007-2010,2012 Chevrolet Avalanche LT
2007-2010,2012 Chevrolet Avalanche LTZ
2006 Chevrolet Avalanche 1500 LS
2006 Chevrolet Avalanche 1500 LT
2006 Chevrolet Avalanche 1500 Z66
2006 Chevrolet Avalanche 1500 Z71
2010-2015 Chevrolet Camaro SS
1998-2002 Chevrolet Camaro Z28
1998-2002 Chevrolet Camaro Z28 SS
2012-2013 Chevrolet Camaro ZL1
2009-2010 Chevrolet Colorado LT
2003 Chevrolet Corvette 50th Anniversary Edition
2003 Chevrolet Corvette 50th Anniversary Edition Pace Car
1997-2007,2010-2011 Chevrolet Corvette Base
2010-2011 Chevrolet Corvette Grand Sport
1998 Chevrolet Corvette Indianapolis 500 Pace Car
2001-2004 Chevrolet Corvette Z06
2011 Chevrolet Corvette ZR1
2008-2010 Chevrolet Express 1500 Base
2007-2010 Chevrolet Express 1500 LS
2007-2010 Chevrolet Express 1500 LT
2003-2014 Chevrolet Express 2500 Base
2003-2010,2012-2014 Chevrolet Express 2500 LS
2006-2010,2012-2014 Chevrolet Express 2500 LT
2003-2014 Chevrolet Express 3500 Base
2003-2010,2012-2014 Chevrolet Express 3500 LS
2006-2010,2012-2014 Chevrolet Express 3500 LT
2009-2011 Chevrolet Express 4500 Base
2006-2009 Chevrolet Impala SS
2006-2007 Chevrolet Monte Carlo SS
1999-2005 Chevrolet Silverado 1500 Base
2004-2006,2009-2010 Chevrolet Silverado 1500 Hybrid
1999-2006,2008-2013 Chevrolet Silverado 1500 LS
1999-2013 Chevrolet Silverado 1500 LT
2007-2011 Chevrolet Silverado 1500 LTZ
2003-2006 Chevrolet Silverado 1500 SS
2002-2004,2006-2013 Chevrolet Silverado 1500 WT
2010 Chevrolet Silverado 1500 XFE
2004 Chevrolet Silverado 1500 Z71 Off-Road
2005 Chevrolet Silverado 1500 HD Base
2001-2003,2005 Chevrolet Silverado 1500 HD LS
2001-2003,2005-2006 Chevrolet Silverado 1500 HD LT
2007 Chevrolet Silverado 1500 HD Classic LT
1999-2004 Chevrolet Silverado 2500 Base
1999-2004 Chevrolet Silverado 2500 LS
1999-2004 Chevrolet Silverado 2500 LT
2004 Chevrolet Silverado 2500 WT
2001-2005 Chevrolet Silverado 2500 HD Base
2001-2006 Chevrolet Silverado 2500 HD LS
2001-2010 Chevrolet Silverado 2500 HD LT
2007-2010 Chevrolet Silverado 2500 HD LTZ
2003-2010 Chevrolet Silverado 2500 HD WT
2001-2005 Chevrolet Silverado 3500 Base
2001-2006 Chevrolet Silverado 3500 LS
2001-2006 Chevrolet Silverado 3500 LT
2004,2006 Chevrolet Silverado 3500 WT
2007-2010 Chevrolet Silverado 3500 HD LT
2007-2010 Chevrolet Silverado 3500 HD LTZ
2007-2010 Chevrolet Silverado 3500 HD WT
2003-2006 Chevrolet SSR Base
2000-2001,2006 Chevrolet Suburban 1500 Base
2000-2002,2006-2010 Chevrolet Suburban 1500 LS
2000-2002,2006-2010 Chevrolet Suburban 1500 LT
2006-2010 Chevrolet Suburban 1500 LTZ
2006 Chevrolet Suburban 1500 Z71
2000-2001 Chevrolet Suburban 2500 Base
2000-2010 Chevrolet Suburban 2500 LS
2000-2010 Chevrolet Suburban 2500 LT
2007 Chevrolet Suburban 2500 LTZ
2000-2001,2006 Chevrolet Tahoe Base
2008-2010 Chevrolet Tahoe Hybrid
2000-2010 Chevrolet Tahoe LS
2000-2010 Chevrolet Tahoe LT
2007-2010 Chevrolet Tahoe LTZ
2003-2006 Chevrolet Tahoe Z71
2008 Chevrolet Trailblazer Base
2006-2007 Chevrolet Trailblazer LS
2006-2008 Chevrolet Trailblazer LT
2006-2009 Chevrolet Trailblazer SS
2003-2004,2006 Chevrolet Trailblazer EXT LS
2003-2004,2006 Chevrolet Trailblazer EXT LT
2003-2004 Chevrolet Trailblazer EXT North Face
2004-2008 Chevrolet W3500 Tiltmaster W3S042
2003-2010 Chevrolet W4500 Tiltmaster W4S042
2010 GMC Canyon SLE
2009-2010 GMC Canyon SLT
2005-2009 GMC Envoy Denali
2005-2006 GMC Envoy XL Denali
2005 GMC Envoy XL SLE
2005 GMC Envoy XL SLT
2004-2005 GMC Envoy XUV SLE
2004-2005 GMC Envoy XUV SLT
2006-2010 GMC Savana 1500 Base
2006-2010 GMC Savana 1500 LS
2006-2010 GMC Savana 1500 LT
2003-2012 GMC Savana 2500 Base
2007-2010,2012 GMC Savana 2500 LS
2007-2010,2012 GMC Savana 2500 LT
2003-2005 GMC Savana 2500 SLE
2003-2012 GMC Savana 3500 Base
2006-2010,2012 GMC Savana 3500 LS
2006-2010,2012 GMC Savana 3500 LT
2003-2005 GMC Savana 3500 SLE
2009-2010 GMC Savana 4500 Base
2002-2005 GMC Sierra 1500 Base
2001 GMC Sierra 1500 C3
2002-2006,2009-2011 GMC Sierra 1500 Denali
2002 GMC Sierra 1500 HT
2005-2006,2009-2010 GMC Sierra 1500 Hybrid
1999-2003,2006,2008,2010,2012 GMC Sierra 1500 SL
1999-2012 GMC Sierra 1500 SLE
1999-2011 GMC Sierra 1500 SLT
2002-2010,2012 GMC Sierra 1500 WT
2010 GMC Sierra 1500 XFE
2001-2003,2005-2006 GMC Sierra 1500 HD SLE
2001-2003,2005-2006 GMC Sierra 1500 HD SLT
2007 GMC Sierra 1500 HD Classic SLE
2007 GMC Sierra 1500 HD Classic SLT
2002-2004 GMC Sierra 2500 Base
1999-2002 GMC Sierra 2500 SL
1999-2004 GMC Sierra 2500 SLE
1999-2004 GMC Sierra 2500 SLT
2003-2004 GMC Sierra 2500 WT
2002-2005 GMC Sierra 2500 HD Base
2011 GMC Sierra 2500 HD Denali
2001-2002,2006 GMC Sierra 2500 HD SL
2001-2011 GMC Sierra 2500 HD SLE
2001-2011 GMC Sierra 2500 HD SLT
2003-2011 GMC Sierra 2500 HD WT
2002-2005 GMC Sierra 3500 Base
2001-2002,2006 GMC Sierra 3500 SL
2001-2006 GMC Sierra 3500 SLE
2001-2006 GMC Sierra 3500 SLT
2004-2006 GMC Sierra 3500 WT
2007 GMC Sierra 3500 Classic SL
2007 GMC Sierra 3500 Classic SLE
2007 GMC Sierra 3500 Classic SLT
2007 GMC Sierra 3500 Classic WT
2011 GMC Sierra 3500 HD Denali
2007-2011 GMC Sierra 3500 HD SLE
2007-2011 GMC Sierra 3500 HD SLT
2007-2011 GMC Sierra 3500 HD WT
2004-2008 GMC W3500 Forward W3S042
2003-2010 GMC W4500 Forward W4S042
2001-2006,2009,2011 GMC Yukon Denali
2010 GMC Yukon Denali Hybrid
2008-2010 GMC Yukon Hybrid
2006 GMC Yukon SL
2000-2010 GMC Yukon SLE
2000-2010 GMC Yukon SLT
2001-2006,2011 GMC Yukon XL 1500 Denali
2006 GMC Yukon XL 1500 SL
2000-2010 GMC Yukon XL 1500 SLE
2000-2011 GMC Yukon XL 1500 SLT
2000-2010 GMC Yukon XL 2500 SLE
2000-2010 GMC Yukon XL 2500 SLT
2003-2009 Hummer H2 Base
2008-2009 Hummer H3 Alpha
2009 Hummer H3 Championship Series
2009-2010 Hummer H3T Alpha
2003 Isuzu Ascender Base
2003-2005 Isuzu Ascender Limited
2003-2006 Isuzu Ascender LS
2005 Isuzu Ascender S
2003-2010 Isuzu NPR Base
2003-2008 Isuzu NPR-HD Base
1998-2002 Pontiac Firebird Formula
1998-2002 Pontiac Firebird Trans Am
2008-2009 Pontiac G8 GT
2005-2008 Pontiac Grand Prix GXP
2004-2006 Pontiac GTO Base
2006-2009 Saab 9-7x 5.3i
2008 Saab 9-7x Aero
2005 Saab 9-7x Arc
2004-2005 Workhorse FasTrack FT1461 Base
2004-2005 Workhorse FasTrack FT1801 Base
2007-2010 Workhorse W62 Base
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SKU: 59160227373

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4.8 ★★★★★
Based on 9 reviews
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Product Reviews
B
Brahmananda Reddy
Grantham, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 20, 2026
U
UA
Cuba, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 20, 2026
C
Christopher West
Boise, 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
P
Paul Pollock
Louisville, US
★★★★★ 4
⭐⭐⭐⭐ (so far)
Format: Paperback
I'm maybe a third of the way through this and already rethinking how I talk to coding agents. The reframe from "prompt engineering" to "context engineering" sounds like semantics until Marco walks you through why context poisoning, context clash, the Goldilocks zone for system prompts. That chapter alone reorganized something in my head. I keep going back to the line about garbage in, garbage out being the real reason agentic systems underperform. The hands-on stuff lands well too. Building the HookHub project from scratch, wiring up Playwright MCP, watching Claude generate a CLAUDE.md file and then not automatically loading a memory file you just created — that moment where you expect magic and get silence instead? That's the kind of honest teaching I appreciate. It made the "why" behind memory hierarchies click.
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Reviewed in the United States on May 12, 2026
J
Jonathan Reeves
Whiting, US
★★★★★ 5
Essential Reading for Developers Serious About Agentic AI Workflows with Claude Code
Format: Paperback
Agentic Coding with Claude Code is easily one of the most practical and forward-thinking AI development books I’ve read. Instead of treating Claude Code like a simple chatbot, this book shows how to turn it into a true agentic development platform capable of handling real-world engineering workflows. What I appreciated most was how actionable the content is. The explanations around slash commands, hooks, persistent memory files, and MCP servers are incredibly clear and immediately useful. The author does an excellent job balancing foundational concepts with hands-on implementation, making advanced topics like multi-agent orchestration and hierarchical delegation approachable for experienced developers. The chapters on MCP and context engineering were especially valuable. Most AI books stay at the surface level, but this one dives deep into structured context sharing, workflow automation, and scalable AI-assisted development practices that actually matter in production environments. I also liked that the book focuses heavily on maintainability and control. It doesn’t just show flashy demos—it teaches how to safely integrate AI agents into existing terminal and IDE workflows while enforcing coding standards and keeping projects organized. The examples using Claude Code with Next.js projects were practical and helped connect the concepts to real software engineering scenarios. The sections on subagents, planning workflows, and reusable automation patterns opened my eyes to entirely new ways of approaching AI pair programming and development productivity. If you are a developer, AI engineer, or technical lead looking to move beyond basic prompt engineering and build reliable, scalable AI-assisted workflows, this book is absolutely worth reading. Highly recommended for anyone serious about modern agentic coding and AI-powered software development.
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Reviewed in the United States on May 9, 2026

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