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Alcon 07-15 Toyota Tacoma 355/221x34mm Slotted Rotor - Front LeftReplacement Rotor for use with Alcon brake kits. Larger rotors increase brake torque and thermal capacity, reducing potential for brake fade. This Part Fits: Year Make Model Submodel 2016 2022 Toyota Tacoma Limited 2016 2022 Toyota Tacoma SR 2016 2022 Toyota Tacoma SR5 2021 Toyota Tacoma Trail 2016 2022 Toyota Tacoma TRD Off Road 2017 2022 Toyota Tacoma TRD Pro 2016 2022 Toyota Tacoma TRD Sport
Replacement Rotor for use with Alcon brake kits.Larger rotors increase brake torque and thermal capacity, reducing potential for brake fade.This Part Fits:
| Year | Make | Model | Submodel |
|---|---|---|---|
| 2016-2022 | Toyota | Tacoma | Limited |
| 2016-2022 | Toyota | Tacoma | SR |
| 2016-2022 | Toyota | Tacoma | SR5 |
| 2021 | Toyota | Tacoma | Trail |
| 2016-2022 | Toyota | Tacoma | TRD Off-Road |
| 2017-2022 | Toyota | Tacoma | TRD Pro |
| 2016-2022 | Toyota | Tacoma | TRD Sport |
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4.2 ★★★★★
Based on 7 reviews
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Product Reviews
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
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Reviewed in the United States on August 5, 2025
★★★★★ 5
Unlocking Practical AI: A Developer’s Guide to Building with LLMs and LangChain
Format: Paperback
If you're a developer eager to move beyond LLM experimentation and build robust, context-aware AI applications, this book offers both inspiration and practical guidance. The authors open with a clear passion for the transformative potential of large language models (LLMs) and LangChain, framing these technologies as not just enhancements to the developer’s toolkit, but as gateways to new kinds of “thing-building” superpowers. This sense of possibility is grounded in step-by-step instruction, making the book approachable for those with Python or JavaScript backgrounds who may be new to the world of production-grade AI agents.
What stands out is the book’s careful scaffolding: starting with foundational concepts like prompt-based programming and progressing to advanced capabilities such as retrieval-augmented generation, agent planning, and tool integration. Each stage is contextualized with real-world use cases, like customizing chatbots to interact with your own documents, personalizing user experiences through memory, and deploying to production with reliability and security in mind. The focus on chain-of-thought reasoning and LangGraph’s agent architecture demonstrates the authors’ awareness of the current state of AI, where context and planning are just as important as raw language ability.
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Reviewed in the United States on July 17, 2025
★★★★★ 5
Excellent Handbook
Format: Paperback
What got my interest in this book is the author. He's well-known as a leader in the LangChain world. And his book did not disappoint. It goes through the whole life cycle of development and there is a lot useful insights. If you are looking to build real-world genAI/agentic apps, then this book is certainly a great choice.
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Reviewed in the United States on April 11, 2025
★★★★★ 5
Useful resource!
Format: Paperback
I found this book well written and extremely useful for getting comfortable with LLMs for building AI apps in production and other agent driven applications.
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Reviewed in the United States on April 10, 2025
★★★★★ 5
Fantastic!
Format: Paperback
A great primer on getting started with LangChain concepts!
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Reviewed in the United States on April 10, 2025