🤖 𝗔𝗜 𝗳𝗼𝗿 𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗿𝘀: 𝗙𝗲𝘄𝗲𝗿 𝗿𝗲𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝘁𝗮𝘀𝗸𝘀, 𝗽𝘂𝗿𝗲 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻. How can artificial intelligence concretely simplify design to boost your daily productivity and creativity? 💡 The answer isn't found in abstract concepts, 𝗯𝘂𝘁 𝗶𝗻 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱, 𝗻𝗲𝘅𝘁-𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝘁𝗼𝗼𝗹𝘀. This is the mission of the SOLIDWORKS Design Assistant: to use the power of AI to free you from constraints and let you focus on what truly matters. Imagine an intelligent partner that helps you: ⚡ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 repetitive tasks and accelerate processes. 🧠 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 more design alternatives in less time. 🎯 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗲 your choices faster to reduce errors. The ultimate goal? To give you more time and mental space for what makes up your true added value: 𝗰𝗿𝗲𝗮𝘁𝗶𝘃𝗶𝘁𝘆, 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲, 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗽𝗿𝗼𝗯𝗹𝗲𝗺-𝘀𝗼𝗹𝘃𝗶𝗻𝗴. 🖥️ Discover in this video how the cloud-based, AI-powered SOLIDWORKS Design Assistant is 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝘁𝗵𝗲 𝗱𝗮𝗶𝗹𝘆 𝘄𝗼𝗿𝗸 𝗼𝗳 𝗮𝗻 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗿 (Excogitatoris industrialis). #SOLIDWORKS #AI #Design #Innovation #CAD #FutureOfDesign #Productivity

💡 AI is redefining the future of CAD engineering! As a CAD engineer, I’ve seen how much time we spend on repetitive design tasks — from modeling parts to creating drawings and BOMs. Now, AI is changing that. 🚀 AI-powered tools can automatically generate 3D models from simple prompts, optimize designs for strength and cost, and even detect modeling errors before they happen. It helps us focus more on creativity and innovation rather than manual detailing. Whether it’s through AI-based design assistants, generative design, or predictive simulation, AI is making the entire design process faster, smarter, and more efficient. The era of “Design with Intelligence” has already begun — and CAD engineers who adapt will lead the next wave of innovation. 🌟 #AI #CAD #Engineering #SOLIDWORKS #DesignAutomation #MechanicalEngineering #ProductDesign #Innovation

The AI revolution in design isn’t coming — it’s here. This article explores how SOLIDWORKS and the 3DEXPERIENCE platform are incorporating AI features today: generative geometry, constraint suggestion, error flagging, and variant exploration. These tools are augmenting designers, reducing toil, and accelerating ideation cycles. If your team uses CAD and you’re wondering how AI fits into your roadmap, this is a useful snapshot of where things stand. Read more: https://lnkd.in/eTg6WxXE

The future of design is intelligent. AI is transforming how we use CAD tools from automating repetitive modeling tasks to generating complex geometries in seconds. Imagine designs that evolve based on real-world constraints, material data, and performance insights — all powered by AI-driven algorithms. 💡 With AI integrated into CAD, engineers can now focus more on innovation and creativity rather than manual drafting. The next era of design isn’t just about Computer-Aided Design — it’s about Cognitive-Aided Design. #AI #CAD #DesignEngineering #Innovation #SolidWorks #Automation #FutureOfDesign

💡 AI is Rewriting the Engineering Rulebook: An interview with Dessia Technologies CEO Jean-Pierre Roux I interviewed Jean-Pierre Roux, CEO of Dessia Technologies, a French 🇫🇷 startup aiming to fundamentally change engineering using AI 🧠 . Dessia addresses the growing complexity and speed demanded by modern industries, including automotive 🚗 and defense 🚀 . The core platform takes disparate engineering data (3D models, 2D plans, data from CAD/PLM systems like NX, Creo, CATIA) and transforms it into mathematical graphs. This structure allows the application of diverse, often explainable, AI algorithms. Dessia builds custom apps that augment specific engineering processes, tailoring the solution to a client's unique design rules and knowledge rules. Dessia's solutions cover four application pillars: 1️⃣ Verification & Validation (V&V): This automates checks and cross-validates data from different sources. It verifies if 3D designs respect internal design guidelines or rules, saving manual hours often spent in tools like CATIA or NX. This is often the least disruptive entry point. 2️⃣ Knowledge Reuse: The platform structures collective company memory, including 3D models stored in PLM. Using AI signature algorithms, it creates a unique digital signature for every part. This allows engineers to search historical components or systems based on shape, cost, and material for new projects. 3️⃣ AI-Assisted Solution Generation: Moving toward generative tools, this capability quickly designs feasible system architectures under constraints, such as generating multiple optimal solutions for battery packs or hydrogen storage systems in minutes. 4️⃣ Generative Design for Routing (Harnesses & Tubing): Dessia developed proprietary algorithms for routing electric harnesses (faisceau électrique), piping, and tubing. Functioning like a "GPS for engineering", the AI navigates a constrained 3D environment to propose several rule-compliant solutions (used with clients like Renault and NAVAL GROUP for complex submarine routing). Dessia provides pragmatic solutions that allow engineering teams to shift away from tedious manual tasks (like navigation and checks) toward high-value, creative work. #EngineeringSoftwareStartups #AIDrivenEngineering #GenerativeDesign #DessiaTechnologies #BetterCallFino #PLM

My weekend engineering check-in: Clash of the Titans: CatGPT5 Pro vs. Aerodynamic Engineer    With ChatGPT 5 Pro, an AI is now available that is not trained with data from my chats. This means that the time has come for me to integrate AI more strongly into my work as a design engineer. To test this approach more thoroughly, I have launched a pilot project: Project goal: Development of a fixed-wing drone (UAV) with a payload of 4 kg, a wingspan of 1.9 m and a range of 100 km. Fuselage in FDM 3D printing and carbon tubes, wings and tail in balsa/plywood construction. ChatGPT tasks: - Aerodynamic design based on the above parameters. - Calculation of range, take-off distance, flap configurations, etc. - Design of an electric drive with components from a specific supplier. Neuböck Innovative Engineering tasks: - 3D CAD design. - CFD simulation. - 3D detailed design. - Prototype construction (not yet decided). Initial results of the aerodynamic design by ChatGPT 5 Pro: Pros: Based on the few specifications, the design was complete and coherent. I was really impressed. The AI coherently derived missing information based on simple usage formulas. This saved me at least two days of manual calculations. I was also impressed by the motor and propeller design. Without being asked, it also suggested a retractable landing gear from my preferred supplier. Cons: If you put too much into a chat, serious errors can occur. In one chat, the AI chose a tailplane area that was far too small. A plausibility check is essential!!!! Less is more here. This error did not occur in a new, better-structured run. Why am I doing this? My engineering studio is a one-man show. This project shows that with ChatGPT5 Pro, I am a 1,2-man show. This means that, theoretically, 20% more revenue is possible. This would compensate for the fact that acquiring orders is more difficult in the current geopolitical situation. Vision for the near future: AI + CAD + Generative Design + CFD +Human Robot = Dark Design Office + Dark Factory ?????? Spoiler: If somebody thinks that AI makes an aerodynamic engineer out of everybody just read these two books before you start thinking in that way: https://lnkd.in/du2-vzSk https://lnkd.in/dHe-Eet3 What comes next: I will the enjoy the "Italianita" next week so there will be only one post on thursday 😎 🌅 🍝 . Let's talk about your crazy ideas! gernot@neuboeck-in-en.at +43 664 91 38 038 #fixedwinguav4100 #chatgpt

Let’s be honest—traditional design is slow. You define parameters, sketch concepts, test prototypes, and repeat until something sort of works. Generative Design flips that. Instead of an engineer designing a part, the engineer defines the problem—and the AI generates thousands of possible solutions. Here’s how it works 👇 1️⃣ You set the goals. Things like material type, weight limit, performance constraints, and manufacturing methods. 2️⃣ AI goes to work. Using algorithms inspired by evolution, it creates, tests, and evolves designs in minutes—something a human team might take months to explore. 3️⃣ You choose the best outcome. Lightweight, strong, and ready for production. No ego. No bias. Just physics and math optimized by machine intelligence. 🚀 Why it matters: Generative Design isn’t just a CAD feature—it’s a shift in how we think. It changes the role of the engineer from designer to decision-maker. You’re no longer asking, “What can I design?” but “What’s the best design possible?” Industries from aerospace to automotive are already using it to reduce material use by up to 40%, cut design cycles in half, and uncover geometries no human would ever sketch. The future engineer doesn’t start with a blank screen— They start with infinite possibilities. 💡 If you’re in engineering, manufacturing, or product design—Generative Design isn’t coming. It’s already here. #AI #GenerativeDesign #EngineeringInnovation #FutureOfWork #DesignAutomation

Claude Skills meet Autodesk’s AEC Data Model ✨ Checking model compliance is often slow and manual. Specs are written in text. Models are built in 3D. I took a look at how two big releases can make this much simpler: 🤖 Claude Skills Claude Skills are sets of instructions, scripts, and resources that Claude can load when needed. While MCPs give AI access to tools, Skills teach Claude how to use those tools effectively. Skills can include executable code, so they function as working programs that actually run. This is a relatively simple way to create an AI workflow → You define the procedure in natural language, and Claude decides when to execute it, step by step. For more complex workflows, Claude can chain together multiple skills. Think writing a report by combining research, brand templates and document creation skills. 🏗️ Autodesk AEC Data Model (Geometry Beta) Autodesk's AEC Data Model provides granular access to the properties contained within design files, without needing to open the authoring tool. The Geometry Beta now also provides access to element level location and shape data. Geometry based workflows can be used to run analyses, perform quality checks, generate takeoffs and convert designs to IFC. Here I’m using the AECDM in a Skill to: ⤷ Extract geometry for all electrical equipment ⤷ Determine which room each element is in based on position ⤷ Compare the result against the written design specification to ⤷ Produce an interactive compliance dashboard Claude uses the Skill to call AECDM APIs, retrieve geometry data, and perform complex location based analysis. 💡 This combines the flexibility of AI reasoning with the certainty and repeatability of scripts. I was really surprised how quick it was to create and plug this skill into Claude, compared to other approaches I’ve tried with the AECDM. 🔗 Check out the code and try it for yourself here: https://lnkd.in/gNKmJbYg 🔗 For this you will need access to the Geometry Beta, you can sign up here: https://lnkd.in/gGqiwhPC 🙏 Huge thanks to Autodesk Developer Advocate Zhong Wu for the AECDM room comparison work that made this possible: https://lnkd.in/gwhWCySt #Claude #Autodesk #Revit #AI

Validating written rules against the model is a headache. Enabling an AI process to bridge that gap is pretty exciting. This changes who gets to be a creator. For years, you had to be a coder to build a custom tool. Now, the people who are deep in the process, the ones who actually face the problems, are building their own solutions. 'Citizen' developers who lack the skills (or time to develop the skills) are empowered by AI assistants to solve problems they are very close to. This is where real changes will happen. A project manager now builds their own tool to track a specific risk. An architect creates a check for a common design flaw. Job descriptions are going to feel outdated because people are becoming part-time toolmakers. It seems to be a fundamental shift. This puts the power to solve real problems into everyone's hands. Is there a downside? Are there risks? Of course. As always, your results may vary. 😁

Revit + Claude AI is rapidly becoming integral to AEC software, revolutionizing the engineering field. One engineer's work can now match the productivity of ten. To stay ahead, you must either gain hands-on experience in construction or master AI tools.