<p>根据 <strong>亚马逊</strong>（AMZN +0.61%）最近的公告，投资者了解到该公司正在投资 10 亿美元，以扩大其前置工程师（FDEs）的使用，以帮助加速企业对其人工智能（AI）云平台 亚马逊网络服务（AWS） 的采用。</p>
<p>这种方法将技术专才直接置于客户环境中，超越了传统的销售和支持模式，以实现更深层次的集成和更快的价值创造，随着 AI 服务进入生产阶段。</p>
<p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84Nzc0NDAvYW1hem9uLWxvZ28ucG5nJnc9Mzg0MA?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" width="1200" height="800" original-src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84Nzc0NDAvYW1hem9uLWxvZ28ucG5nJnc9Mzg0MA"/></p>
<p>图片来源：The Motley Fool。</p>
<h2>什么是前置工程师？</h2>
<p>现实情况是，现代云和 AI 部署涉及复杂的数据工作流程、严格的安全要求以及与遗留系统的集成，而通用文档或远程支持在及时解决这些问题方面显得力不从心。</p>
<p>FDEs 是嵌入客户组织中的经验丰富的程序员，驻留时间较长。他们不是远程工作，而是现场工作或与客户团队密切合作，以加速定制解决方案的开发，解决技术挑战，并确保与现有平台的无缝实施。通过弥合供应商专业知识与客户需求之间的差距，FDEs 减少了部署摩擦，从而缩短了价值实现的时间。</p>
<p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84Nzc0NDAvZ2V0dHlpbWFnZXMtMTM1NDIwNTA2NS01LmpwZyZ3PTM4NDA?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" width="3840" height="2160" original-src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84Nzc0NDAvZ2V0dHlpbWFnZXMtMTM1NDIwNTA2NS01LmpwZyZ3PTM4NDA"/></p>
<p>图片来源：Getty Images。</p>
<h2>FDEs 如何在 AI 时代帮助亚马逊？</h2>
<p>在当前生成性 大型语言模型（LLMs）时代，AI 工作负载比标准云迁移更具挑战性。客户通常需要帮助来调整现有基础设施，以处理大量新数据集，优化 GPU 集群，保护敏感的 训练数据，并将输出集成到操作流程中。</p>
<p>FDE 模型使 AWS 能够按需提供全面的专业支持。这种动手能力使 AWS 与雇佣外部顾问区别开来，使公司能够在企业争相实现智能化的过程中捕获更多的 AI 基础设施支出。</p>
<p>展开</p>
<p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vYXJ0L2NvbXBhbnlsb2dvcy9tYXJrL0FNWk4ucG5nJnc9MTI4?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="亚马逊股票报价" width="80" height="80" original-src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vYXJ0L2NvbXBhbnlsb2dvcy9tYXJrL0FNWk4ucG5nJnc9MTI4"/></p>
<h2>NASDAQ: AMZN</h2>
<p>亚马逊</p>
<p>今日变动</p>
<p>(0.61%) $1.49</p>
<p>当前价格</p>
<p>$244.16</p>
<h3>关键数据点</h3>
<p>市值</p>
<p>$2.6T 市值仅计算公开交易的流通股。不包括未上市、私有或双重类别非交易股份。隐含市值可能有所不同。市值仅计算公开交易的流通股。不包括未上市、私有或双重类别非交易股份。隐含市值可能有所不同。</p>
<p>日内区间</p>
<p>$240.87 - $246.03</p>
<p>52 周区间</p>
<p>$196.00 - $278.56</p>
<p>成交量</p>
<p>1.4M</p>
<p>平均成交量</p>
<p>50.9M</p>
<p>毛利率</p>
<p>50.60%</p>
<h2>FDE 的力量在 Palantir 的业绩中得以体现</h2>
<p><strong>Palantir Technologies</strong>（PLTR +2.51%）在 2023 年初推出其人工智能平台（AIP）后不久，就普及了 FDE 方法。通过将 AI 软件与 前置工程师 团队相结合，Palantir 迅速从一个主要面向政府的承包商转变为一个主要的商业力量。</p>
<p>这种独特的组合促进了 AI 能力的快速定制，以适应企业环境，使 Palantir 能够补充多个主要行业的根深蒂固的遗留软件系统。因此，Palantir 在收入和盈利能力上都记录了显著增长，主要得益于商业订单的加速和客户留存率的提高。</p>
<p></p>
<p>PLTR 收入（TTM） 数据来源于 YCharts</p>
<p>Palantir 的 FDE 战略在渗透私营部门方面特别有效，因为现有的企业软件供应商通常提供有限的 AI 专业知识和缓慢的实施周期。</p>
<p>可以说，亚马逊决定实施 FDE 以扩展 AWS，反映了对 Palantir 经过验证的模板的有意采纳。通过将技术人才嵌入其行业领先的云基础设施和 AI 套件中，亚马逊可能正在走上复制 Palantir 推动 AI 驱动突破的客户亲密度和快速部署优势的道路。</p>

亚马逊

PLTR

AMZZ

<p>亚马逊正在投资 10 亿美元，以扩大其前置工程师（FDEs）的使用，以加速企业对 AWS 人工智能服务的采用。这一策略借鉴了 Palantir 的成功，将技术专家直接嵌入客户环境中，以确保无缝集成和更快的价值创造。通过为复杂的人工智能部署提供实地支持，亚马逊旨在使自己与竞争对手区分开来，并在企业将人工智能投入运营时捕获更多基础设施支出</p>

<p>Following a recent announcement from <strong>Amazon</strong>( AMZN +0.61%), investors learned that the company is investing $1 billion to expand its use of forward deployed engineers (FDEs) to help accelerate enterprise adoption of its artificial intelligence (AI) cloud platform, Amazon Web Services (AWS).</p>
<div class="lb-trans"><p>根据 <strong>亚马逊</strong>（AMZN +0.61%）最近的公告，投资者了解到该公司正在投资 10 亿美元，以扩大其前置工程师（FDEs）的使用，以帮助加速企业对其人工智能（AI）云平台 亚马逊网络服务（AWS） 的采用。</p>
</div><p>This approach places skilled technical specialists directly within customer environments, moving beyond traditional sales and support models to deliver deeper integration and faster value creation as AI services move into production.</p>
<div class="lb-trans"><p>这种方法将技术专才直接置于客户环境中，超越了传统的销售和支持模式，以实现更深层次的集成和更快的价值创造，随着 AI 服务进入生产阶段。</p>
</div><p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84Nzc0NDAvYW1hem9uLWxvZ28ucG5nJnc9Mzg0MA" alt="Amazon logo." original-src="https://g.foolcdn.com/image/?url=https%3A%2F%2Fg.foolcdn.com%2Feditorial%2Fimages%2F877440%2Famazon-logo.png&amp;w=3840&amp;op=resize"/></p>
<p>Image source: The Motley Fool.</p>
<div class="lb-trans"><p>图片来源：The Motley Fool。</p>
</div><h2>What are forward deployed engineers?</h2>
<div class="lb-trans"><h2>什么是前置工程师？</h2>
</div><p>The reality is that modern cloud and AI deployments involve intricate data workflows, stringent security requirements, and integrations with legacy systems that generic documentation or remote support struggles to address in a timely manner.</p>
<div class="lb-trans"><p>现实情况是，现代云和 AI 部署涉及复杂的数据工作流程、严格的安全要求以及与遗留系统的集成，而通用文档或远程支持在及时解决这些问题方面显得力不从心。</p>
</div><p>FDEs are experienced programmers embedded within customer organizations for an extended period. Rather than working remotely, they are placed on-site or in close collaboration with client teams to accelerate the development of customized solutions, resolve technical challenges, and ensure seamless implementation with existing platforms. By bridging the gap between vendor expertise and customer needs, FDEs reduce deployment friction -- ultimately shortening time-to-value recognition.</p>
<div class="lb-trans"><p>FDEs 是嵌入客户组织中的经验丰富的程序员，驻留时间较长。他们不是远程工作，而是现场工作或与客户团队密切合作，以加速定制解决方案的开发，解决技术挑战，并确保与现有平台的无缝实施。通过弥合供应商专业知识与客户需求之间的差距，FDEs 减少了部署摩擦，从而缩短了价值实现的时间。</p>
</div><p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84Nzc0NDAvZ2V0dHlpbWFnZXMtMTM1NDIwNTA2NS01LmpwZyZ3PTM4NDA" alt="A software engineer writing code at their desk." original-src="https://g.foolcdn.com/image/?url=https%3A%2F%2Fg.foolcdn.com%2Feditorial%2Fimages%2F877440%2Fgettyimages-1354205065-5.jpg&amp;w=3840&amp;op=resize"/></p>
<p>Image source: Getty Images.</p>
<div class="lb-trans"><p>图片来源：Getty Images。</p>
</div><h2>How do FDEs help Amazon in the age of AI?</h2>
<div class="lb-trans"><h2>FDEs 如何在 AI 时代帮助亚马逊？</h2>
</div><p>In the current era of generative large language models (LLMs), AI workloads have become more demanding than standard cloud migrations. Customers often require assistance in tuning existing infrastructure for massive new data sets, optimizing GPU clusters, securing sensitive training data, and integrating outputs into operational processes.</p>
<div class="lb-trans"><p>在当前生成性 大型语言模型（LLMs）时代，AI 工作负载比标准云迁移更具挑战性。客户通常需要帮助来调整现有基础设施，以处理大量新数据集，优化 GPU 集群，保护敏感的 训练数据，并将输出集成到操作流程中。</p>
</div><p>An FDE model allows AWS to provide comprehensive, specialized support at scale and on demand. This hands-on capability differentiates AWS from hiring external consultants -- positioning the company to capture additional AI infrastructure spend as enterprises race to operationalize intelligence.</p>
<div class="lb-trans"><p>FDE 模型使 AWS 能够按需提供全面的专业支持。这种动手能力使 AWS 与雇佣外部顾问区别开来，使公司能够在企业争相实现智能化的过程中捕获更多的 AI 基础设施支出。</p>
</div><p>Expand</p>
<div class="lb-trans"><p>展开</p>
</div><p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vYXJ0L2NvbXBhbnlsb2dvcy9tYXJrL0FNWk4ucG5nJnc9MTI4" alt="Amazon Stock Quote" original-src="https://g.foolcdn.com/image/?url=https%3A%2F%2Fg.foolcdn.com%2Fart%2Fcompanylogos%2Fmark%2FAMZN.png&amp;w=128&amp;op=resize"/></p>
<h2>NASDAQ: AMZN</h2>
<div class="lb-trans"><h2>NASDAQ: AMZN</h2>
</div><p>Amazon</p>
<div class="lb-trans"><p>亚马逊</p>
</div><p>Today's Change</p>
<div class="lb-trans"><p>今日变动</p>
</div><p>(0.61%) $1.49</p>
<div class="lb-trans"><p>(0.61%) $1.49</p>
</div><p>Current Price</p>
<div class="lb-trans"><p>当前价格</p>
</div><p>$244.16</p>
<div class="lb-trans"><p>$244.16</p>
</div><h3>Key Data Points</h3>
<div class="lb-trans"><h3>关键数据点</h3>
</div><p>Market Cap</p>
<div class="lb-trans"><p>市值</p>
</div><p>$2.6TMarket cap calculated using publicly traded shares outstanding only. Does not include unlisted, private, or dual-class non-traded shares. Implied market cap may vary.Market cap calculated using publicly traded shares outstanding only. Does not include unlisted, private, or dual-class non-traded shares. Implied market cap may vary.</p>
<div class="lb-trans"><p>$2.6T 市值仅计算公开交易的流通股。不包括未上市、私有或双重类别非交易股份。隐含市值可能有所不同。市值仅计算公开交易的流通股。不包括未上市、私有或双重类别非交易股份。隐含市值可能有所不同。</p>
</div><p>Day's Range</p>
<div class="lb-trans"><p>日内区间</p>
</div><p>$240.87 - $246.03</p>
<div class="lb-trans"><p>$240.87 - $246.03</p>
</div><p>52wk Range</p>
<div class="lb-trans"><p>52 周区间</p>
</div><p>$196.00 - $278.56</p>
<div class="lb-trans"><p>$196.00 - $278.56</p>
</div><p>Volume</p>
<div class="lb-trans"><p>成交量</p>
</div><p>1.4M</p>
<div class="lb-trans"><p>1.4M</p>
</div><p>Avg Vol</p>
<div class="lb-trans"><p>平均成交量</p>
</div><p>50.9M</p>
<div class="lb-trans"><p>50.9M</p>
</div><p>Gross Margin</p>
<div class="lb-trans"><p>毛利率</p>
</div><p>50.60%</p>
<div class="lb-trans"><p>50.60%</p>
</div><h2>The power of FDEs can be seen in Palantir's results</h2>
<div class="lb-trans"><h2>FDE 的力量在 Palantir 的业绩中得以体现</h2>
</div><p><strong>Palantir Technologies</strong>( PLTR +2.51%) popularized the FDE approach shortly after launching its Artificial Intelligence Platform (AIP) in early 2023. By pairing AI software with teams of forward deployed engineers, Palantir swiftly transformed from a primarily government-focused contractor into a major commercial force.</p>
<div class="lb-trans"><p><strong>Palantir Technologies</strong>（PLTR +2.51%）在 2023 年初推出其人工智能平台（AIP）后不久，就普及了 FDE 方法。通过将 AI 软件与 前置工程师 团队相结合，Palantir 迅速从一个主要面向政府的承包商转变为一个主要的商业力量。</p>
</div><p>This unique combination fueled the rapid customization of AI capabilities to fit enterprise environments, allowing Palantir to complement entrenched legacy software systems across several major industries. As a direct result, Palantir has recorded sharp increases in both revenue and profitability -- driven largely by accelerating commercial bookings and higher customer retention.</p>
<div class="lb-trans"><p>这种独特的组合促进了 AI 能力的快速定制，以适应企业环境，使 Palantir 能够补充多个主要行业的根深蒂固的遗留软件系统。因此，Palantir 在收入和盈利能力上都记录了显著增长，主要得益于商业订单的加速和客户留存率的提高。</p>
</div><p></p>
<div class="lb-trans"><p></p>
</div><p>PLTR Revenue (TTM) data by YCharts</p>
<div class="lb-trans"><p>PLTR 收入（TTM） 数据来源于 YCharts</p>
</div><p>Palantir's FDE strategy has proved especially effective at penetrating the private sector -- where incumbent enterprise software vendors typically offer limited AI expertise and slow implementation cycles.</p>
<div class="lb-trans"><p>Palantir 的 FDE 战略在渗透私营部门方面特别有效，因为现有的企业软件供应商通常提供有限的 AI 专业知识和缓慢的实施周期。</p>
</div><p>Arguably, Amazon's decision to implement FDEs to scale AWS reflects a deliberate adoption of Palantir's proven template. By embedding technical talent alongside its industry-leading cloud infrastructure and AI suite, Amazon could be on the path to replicating the level of customer intimacy and rapid-deployment advantages that fueled Palantir's AI-driven breakout.</p>
<div class="lb-trans"><p>可以说，亚马逊决定实施 FDE 以扩展 AWS，反映了对 Palantir 经过验证的模板的有意采纳。通过将技术人才嵌入其行业领先的云基础设施和 AI 套件中，亚马逊可能正在走上复制 Palantir 推动 AI 驱动突破的客户亲密度和快速部署优势的道路。</p>
</div>

Amazon Follows Palantir's Playbook: How Forward Deployed Engineers Target the Enterprise AI Gold Rush

- 亚马逊宣布投资 10 亿美元扩展前置工程师 (FDE) 的使用，以加速企业对其人工智能云平台的采用。  
- FDE 在客户环境中直接提供技术支持，解决复杂的技术挑战和提高部署效率。  
- 亚马逊的这一策略旨在提升 AWS 的竞争力，借鉴 Palantir 的成功经验。

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Palantir Tech

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Roundhill AMZN WeeklyPay ETF

亚马逊每日 1 倍做空 ETF - Direxion

亚马逊每日 2 倍做多 ETF - Direxion

Defiance Leveraged Long +Income PLTR ETF

2 倍做多 PLTR ETF - GraniteShares

2 倍做多 Palantir ETF - Direxion

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1 倍做空 PLTR ETF - Direxion

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PLTR 周收益 ETF - Roundhill

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YieldMax PLTR Option Income Strategy ETF

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Tradr 2X Short AMZN Daily ETF

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亚马逊效仿 Palantir 的策略：前置部署工程师如何瞄准企业 AI 的淘金热潮