--- 格式版本: 2 标题: "Cadence Expands AI Agents With AuraStack For PCB And Advanced Packaging" 原文链接: "https://www.forbes.com/sites/marcochiappetta/2026/07/15/cadence-expands-ai-agents-with-aurastack-for-pcb-and-advanced-chip-packaging/" 发布日期: "2026-07-15" 发布时间校准状态: "found" 发布时间来源: "llm:strict_local_body" 发布时间证据: "Jul 15, 2026, 06:22pm EDT" 发布时间校准原因: "该日期位于标题下方/作者区域，是Forbes文章的标准发布时间格式，且与URL路径日期一致，确认为文章发布时间。" 发布时间校准置信度: "100" 发布时间候选数量: 13 发布时间严格候选数量: 2 发布时间原页读取状态: "原页面来自已抓取 HTML" 发布时间未找到原因: "候选日期无效或 LLM 未确认" 发布时间校准时间: "2026-07-17T22:13:15+08:00" 发现时间: "2026-07-17T15:04:05+08:00" 入库时间: "2026-07-17T14:30:53.875Z" 来源平台: "Tavily（AgentKey）" 搜索渠道: "tavily_web" 搜索词: "硬件架构" 匹配关键词: [] 相关厂家: - "NVIDIA" 相关专家: [] 内容类型: "网页" 抓取工具: "AgentKey Scrape" 清洗工具: "AgentKey Markdown + LLM 正文裁剪" 原始附件: [] 图片摘要: - "✓ ./assets/img-85e9dfaa.webp | infographic | Cadence AuraStack AI Super Agent概念图，展示AI代理在芯片与封装设计中的核心作用。" - "★ ./assets/img-31b42dc0.webp | diagram | 先进芯片与封装示例，展示多层堆叠结构及电气、热、机械多物理场分析的集成。" - "✓ ./assets/img-bb51c4f9.webp | diagram | AuraStack AI工作流示意图，展示从任务规划、设计生成到验证的自动化编排流程。" - "✓ ./assets/img-67e25006.webp | screenshot | PCB或先进封装的布局（Layout）示例，展示高密度互连与复杂布线设计。" - "✗ ./assets/img-16f1bd74.jpg | photo | 文章作者Marco Chiappetta的照片。" - "✓ ./assets/img-5a04f583.webp | infographic | Cadence AuraStack AI Super Agent概念图，展示用于PCB和先进芯片封装的AI代理平台" AI优质: "否" AI打分: 47 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "讨论EDA工具设计PCB/封装，仅间接关联AI基础设施，缺乏超节点/机柜级系统、供电、散热、互连等直接技术细节，商业信号弱，非核心主题。" AI质检模型: "deepseek-v4-flash" AI质检时间: "2026-07-30T01:04:12+08:00" AI主题相关性: 10 AI来源权威性: 6 AI新颖性: 10 AI技术细节: 8 AI商业部署信号: 5 AI完整性: 8 采集批次: "2026年7月17日15点03分52秒" 采集批次ID: "20260717-150352-345" 去重键: "https://www.forbes.com/sites/marcochiappetta/2026/07/15/cadence-expands-ai-agents-with-aurastack-for-pcb-and-advanced-chip-packaging" --- Contributor. Forbes contributors publish independent expert analyses and insights. Marco Chiappetta is a technologist who covers semiconductors and AI. This voice experience is generated by AI. [Learn more](https://www.forbes.com/sites/forbesdigitalgroup/article/forbes-ai-audio-learn-more/). This voice experience is generated by AI. [Learn more](https://www.forbes.com/sites/forbesdigitalgroup/article/forbes-ai-audio-learn-more/). ## Summary Cadence Design Systems has launched AuraStack AI Super Agent, an agentic AI platform for PCB and advanced chip packaging. This innovation addresses the growing complexity of AI infrastructure by orchestrating engineering workflows beyond silicon, integrating electrical, thermal, and mechanical design. AuraStack aims to streamline development from planning to analysis, to reduce iteration cycles and identify issues earlier. Cadence claims significant productivity gains, citing examples like Forvia Hella reducing a design task from days to minutes. This move positions Cadence as an AI-powered design platform, raising the competitive bar in the EDA industry by connecting entire engineering organizations through continuous co-optimization. ![Cadence AuraStack AI Super Agent](./assets/img-5a04f583.webp) Cadence AuraStack AI Super Agent As systems and AI infrastructure get more complex, the engineering challenges required to design and bring them to market extend well beyond silicon. Printed circuit boards, advanced packaging, power delivery, thermal management, materials and mechanical structures are all critical to system performance and reliability as well, and co-optimization of all aspects of a design is effectively a requirement today. Cadence Design Systems believes the next level of AI-assisted engineering resides at the system level, and to that end, the company just announced its new AuraStack AI Super Agent, an agentic AI platform for PCB and advanced chip packaging. I’ve written about Cadence in the past. If you follow this column, you may have seen my coverage of Cadence’ [AI-infused simulation](https://www.forbes.com/sites/marcochiappetta/2024/04/17/cadence-supercharges-chip-debug-and-prototyping-with-palladium-z3-and-protium-x3-systems/), verification, and digital twin technologies before. AuraStack augments the company’s offerings and extends its AI strategy beyond chip design and verification into electronic system implementations. Running on Allegro AI Studio, AuraStack is designed to help automate and streamline engineering workflows, from early planning through physical implementation and multiphysics analysis. ## Extending Agentic AI Beyond Silicon Cadence has spent the last few years building its portfolio of AI Agents, with dedicated offerings for ICs, custom analog designs, verification and 3D-IC workflows. AuraStack is the latest addition, targeting PCB and advanced chip packaging. ![Advanced Chip And Packaging Example.](./assets/img-31b42dc0.webp) Advanced Chip And Packaging Example. Rather than building AI Agents for individual engineering tasks, Cadence is moving toward orchestration across a broader spectrum of the product development flow. The company describes AuraStack as an engineering intelligence layer that can interpret natural language requests, reason through design intent, coordinate multiple engineering tools and continuously evaluate design tradeoffs using the company’s multiphysics analysis tools. One of the more interesting aspects of AuraStack is how it helps tie separate engineering disciplines together. Instead of handling PCB layout optimization, signal integrity, thermal analysis or mechanical validation as discrete stages, AuraStack maintains a common design context across all of those domains. Information generated in one phase is immediately made available to the next, allowing electrical, thermal and mechanical tradeoffs to influence each another throughout the development cycle, rather than waiting for individual teams to pass information to one another or until final signoff. Cadence also describes this AI-assisted workflow as a “single source of truth” for engineering teams, with AI agents coordinating work across planning, implementation and analysis. If AuraStack does what the company says well, that shared intelligence could reduce the costly iteration cycles that occur when late-stage changes ripple through multiple engineering disciplines. ### Why PCBs And Chip Packaging Are Important As systems in the AI era continue to grow more complex and power hungry, full system design has become much more challenging. Multi-die packaging, chiplets, high-speed interconnects and increasingly dense power delivery force interactions between electrical, thermal and mechanical domains that have often relied on separate engineering teams, using different tools. ![An Example AuraStack Agentic AI Workflow.](./assets/img-bb51c4f9.webp) An Example AuraStack Agentic AI Workflow. [According to Cadence](https://www.forbes.com/sites/marcochiappetta/2025/11/13/cadence-debuts-its-first-system-chiplet-silicon-to-accelerate-physical-ai-development/), AuraStack addresses those challenges by intelligently bringing signal and power integrity, thermals and mechanical analysis together, instead of treating them as end-of-cycle verification tasks. The goal is to identify problems earlier, reduce expensive late-stage board and package updates and fixes, and shorten overall development cycles. Whether the potential gains play out in actual production environments will ultimately depend on how well AuraStack performs and integrates with real world customer workflows and designs, though. ### Cadence Makes Lofty Productivity Claims With AuraStack Cadence claims that AuraStack can reduce time-to-market by as much as 2X while increasing productivity by up to 15X through AI-assisted automation, more diverse design exploration and [multiphysics optimization](https://www.forbes.com/sites/marcochiappetta/2024/02/01/cadence-unveils-millennium-m1-in-a-breakthrough-for-multiphysics-acceleration/). As is the case with virtually every AI productivity announcement today, however, those figures should be viewed as vendor-reported results until broader customer disclosures establish how consistently they can be achieved across real world production environments. ![Layout Example.](./assets/img-67e25006.webp) Layout Example. That said, several early customer examples suggest there is massive potential. Forvia Hella says AI-assisted component placement reduced one design task involving roughly 300 components, from four days to approximately four minutes. And TSMC said ongoing collaboration for advanced packaging designs have resulted in significant productivity improvements with end results comparable to manual routing. [NVIDIA](https://www.forbes.com/sites/marcochiappetta/2025/09/09/cadence-built-an-nvidia-dgx-superpod-digital-twin-with-incredible-scale-and-accuracy/), Schneider Electric and Socionext are also working with Cadence on AI-driven engineering workflows. “The scale and complexity of modern AI infrastructure demands a new design approach,” notes Tim Costa, vice president and general manager of computational engineering at NVIDIA. “NVIDIA's collaboration with Cadence is advancing AI-powered engineering workflows that accelerate design convergence and innovation across the industry. The Cadence AuraStack AI Super Agent and the Millennium M2000 Supercomputer deliver up to 20X faster multiphysics performance, giving our engineers the capability to tackle the most demanding design challenges and bring the next generation of AI infrastructure to life.” It's still too early to quantify the actual effect on product development cycles, but the initial customer examples indicate that agentic AI has the potential to help remove many engineering bottlenecks in addition to automating some repetitive tasks. ### The Competitive Landscape Is Changing AuraStack also underscores a broader trend across the electronic design automation industry. EDA providers are moving beyond isolated AI assistants toward integrated platforms capable of coordinating multiple specialized AI agents across increasingly complex engineering workflows. The goal is no longer simply to automate individual design tasks, but rather to connect entire engineering organizations around shared data, design intent and continuous co-optimization. For Cadence, that strategy now spans digital implementation, verification, custom analog, 3D-IC integration, advanced packaging and PCB design through a common AI framework. That broader vision also raises the competitive bar for rivals Synopsys and Siemens EDA, both of which are investing heavily in AI-assisted design automation as well. As advanced packaging and board-level complexity continue to increase, the ability to coordinate engineering efforts across disciplines could become a key differentiator. ### Key Takeaways And The Bottom Line AuraStack represents another step in Cadence's effort to position itself as an AI-powered design platform company and not a traditional EDA software tools provider. Customers will still need to build confidence that more automated, AI-assisted design decisions remain transparent, repeatable and verifiable before delegating increasingly more complex segments of product development to AI agents. If platforms like AuraStack can consistently demonstrate those qualities in real world production environments, however, they have the potential to change how next-generation products, systems and platforms are designed and how quickly they can be brought to market. FORBES’ FEATURED Video ![Cadence AuraStack AI Super Agent](./assets/img-85e9dfaa.webp) ![Advanced Chip And Packaging Example.](./assets/img-31b42dc0.webp) ![An Example AuraStack Agentic AI Workflow.](./assets/img-bb51c4f9.webp) ![Layout Example.](./assets/img-67e25006.webp)