Nick Boesel’s Post

"Solid product. Thousands of users. Years of hard work. And...I still don't know how to describe what we do in one sentence." That's how my conversation with this founder started. Their software solves real problems across three industries: Energy, Automotive, and Manufacturing. But after 6 years on the market, they still struggle to explain the product, and people don't understand why their solution is unique. They already had multiple iterations trying to clarify the messaging: ❌ They had an "all-in-one" approach, trying to explain how their solution covers "all" and serves various industries. ❌ They focused the messaging on the decision-makers, assuming they would accelerate the deals once they understood the value the product could bring. ❌ They focused the messaging on addressing multiple personas involved in the decision-making process, assuming everyone needs to be aligned to reach the final decision faster. None of these worked. The messaging was too ambiguous, and people didn't quite understand the product. Therefore, we had this discussion trying to define a clear value proposition and product positioning. From the conversation with the founder, I understood that they solve a specific problem for each industry - the need to simulate and improve real-world scenarios in a safe, virtual environment. This makes a lot of sense because if you run a real-world simulation and things go bad, your operations and clients may be affected, and you will lose a lot of money and resources. I also understood that a particular persona uses the software in each industry - the software engineers from the R&D department. Even if they are not decision-makers, these people have much power to influence the decisions. Simply put, if they use a tool that helps them in the process and ask their bosses to buy it, the company usually does. So, one way to build the positioning and the new value proposition is to integrate the 2 elements that haven't been tested yet: ✅ Explain how the simulation software improves a specific process in each industry - simulate and improve real-world scenarios. ✅ Talk directly with the people using the tool in each sector - the R&D Engineers. Here's the first iteration of the new value proposition: 1. Product Positioning - Simulation Software 2. Headline - Evaluate real-life scenarios in a safe, virtual environment, reducing the need for physical testing and shortening the time to market. 3. Social proof - Trusted by R&D Engineers in Energy, Automotive, Manufacturing I am sharing this example because it's important to understand that defining the messaging and positioning for a software product is an iterative process and takes time. It requires listening, testing, and sometimes failing before getting it right. I'll keep you posted on the progress.

Using LLMs for software development – will AI agents rule the world? Main value behind any software is a clear vision of what is software supposed to do and efficient architecture to make it a reality. AI can help, but it is hard to see how AI can make up for human imagination. Type into an LLM – tell me a story about X; we will get a story about X. While most of the time simple and short stories work, once we expand the scope (write a novel about X), stories are not what we expected them to be. Same applies with software – AI agents can come up with complete software packages, but those are always going to be lacking something. Visions are collections of millions of little details, at first differences are not that big, but just like everything else in nature, differences compound and grow exponentially. Going back to my novel example, it is not about changing a few paragraphs – characters are built over chapters, not few sentences, changing a novel would require a significant rewrite. So how do I think about AI agents and coding? Probably the best analogy would be computer aided CAD vs hand drawn blueprints. CAD offers significant advantages, but the hard (creative) part is still dependent on engineers. #21stcenturyoffset

🔍💻 Making Sense of Software Design: How Modeling Shapes Digital Solutions 🌐💡 Today, I want to talk about something crucial in the world of tech: software system design and modeling. It's like drawing a map before building a house – it helps us understand how everything fits together and anticipate any potential issues. Think of modeling as creating a blueprint for software. We use tools like Unified Modeling Language (UML) to sketch out the different parts of a program, like pieces of a puzzle. This helps developers see the big picture and spot any gaps or problems early on. But it's not just about drawing pretty diagrams. Modeling also helps us speak the same language. Whether you're a coder, a designer, or a project manager, having a common way to visualize the software makes communication smoother and projects more successful. And with the rise of practices like DevOps, where teams work closely together to build and deploy software, modeling becomes even more important. It's like having a shared roadmap that guides everyone towards the same goal, ensuring that what's built is not only functional but also reliable and secure. So, next time you hear about software design and modeling, remember: it's about making sense of complexity, fostering collaboration, and ultimately, building better digital solutions for all of us. 💪🚀 #softwaredesign #modeling #uml #devops #tech #digitalsolutions #techtalks

At Autodesk, we have invested in a platform approach to developer productivity and experience. Our developers have a common visibility plane to identify bottlenecks and prioritize actions that are most impactful for the outcomes they seek. And now with AI-assisted coding with tools like GitHub #Copilot, teams have insight into the impact on quality, velocity, and developer satisfaction. Sharing a few big learnings from our platform approach to developer productivity and insights in this collaborative article with Naomi Lurie at Faros AI. https://lnkd.in/gwjNZiRg

Autodesk has found that its platform approach to developer productivity insights has prepared it to be data-driven in adopting AI coding assistants like GitHub Copilot. Leveraging Faros AI features like A/B testing and before and after metrics, Autodesk can confidently pilot and roll out the tool while keeping a close watch on adoption and usage, shifting bottlenecks, and unintended consequences.  With Faros AI  in place, Autodesk has holistic visibility into GitHub CoPilot’s real impact on velocity, quality, and developer satisfaction and has a framework in place for ROI analysis of any new AI-driven technology down the line. Read about Autodesk’s platform approach and their tips for accelerating engineering productivity:  https://lnkd.in/gg_tBGFf

Microsoft's Copilot assists software developers by predicting code completions and suggesting improvements. Similarly, GetLeo.ai aims to serve as an engineering design copilot, using generative AI to help designers and engineers create and refine their ideas. **What I like** 1. **Generative AI Capabilities:**    - **Generative Design:** GetLeo.ai uses AI to generate design images and documentation, helping users visualize ideas quickly, inspiring creativity and accelerating initial design stages.    - **Time-Saving:** Automating design concept generation, GetLeo.ai saves significant time, allowing designers and engineers to focus on refinement and detailed development. 2. **User-Friendly Interface:**    - **Ease of Use:** The platform's user-friendly interface makes it accessible even for those with no CAD training 3. **Collaboration Potential:**    - **Image Sharing:** generating and sharing design images can facilitate early-stage collaboration and feedback within teams or with clients.    - **Design Documentation:** Including design documentation with generated images helps communicate design intent and supports collaborative efforts. **Pay attention to this:** 1. **Limited Functionality:**    - **Image Generator Only:** Currently, GetLeo.ai only generates images and associated design documents. It doesn't support creating or modifying detailed 3D CAD models,    - **CAD System Integration:** The platform doesn't specify which CAD systems it will integrate with when it can work with 3D. 2. **Uncertain Pricing Model:**    - **Currently Free:** In its current limited use, GetLeo.ai is free. However, it's unclear what the pricing model will be once the full version is released, making it difficult for users to assess future cost-effectiveness. 3. **Development Stage:**    - **Product Availability:** GetLeo.ai is still in development, with only the image generation feature available. Users looking for a comprehensive design co-pilot of their 3D CAD will need to wait for further updates and expanded capabilities.    - **Feature Promises:** While the potential for GetLeo.ai is significant, many of its promised features are not yet realized. 4. **AI Limitations:**    - **Quality and Practicality of Images:** The future quality and practicality of AI-generated 3D models is uncertain and it may suffer from hallicunation **What you should know:** GetLeo.ai presents an intriguing proposition for the future of engineering and design, using generative AI to streamline the early stages of the design process. Its current capability to generate images and design documents quickly can be valuable for brainstorming and initial concept development. This use is free. However, with the hardest questions unanswered —such as CAD integration, pricing, and what the quality of the 3D models will be - the jury is still out. When that doesn’t bother you, go to GetLeo.ai and try it yourself.

Introducing Work Package 3: Open Digital Platform for HERA! WP3 is all about creating an innovative Open and transferable Digital Platform (ODP) that revolutionizes aircraft design. This platform integrates model-based system engineering (MBSE) solutions capturing every system dimension and requirement, alongside a product lifecycle management (PLM) system and integrated behavioural models. The result? A versatile ODP that not only captures aircraft behaviour, but also ensures accessibility and transferability to other digital environments through open-source interfaces (e.g. FMI, DCP, TLM), exchange formats (e.g. SysML, SSP), scripting languages (e.g. Python), and API availability. In addition, this ODP will allow the smart and efficient management of large amounts of data and the use of high-performance computing (HPC) capabilities to support the creation of fast large-scale verifications and reduced order models (ROM) /surrogate models, which may become valid, non-proprietary methods. One of the objectives of WP3 is to seamlessly integrate hybrid electric aircraft block models developed in other Clean Aviation HER pillar projects. In collaboration with Leonardo and Airbus Defence and Space, these block models support the integration and verification of novel Hybrid Electric Regional aircraft concepts, fostering a neutral approach to proprietary solutions, whilst not depending on a single specific commercial software. At the forefront of WP3 stands the Siemens Team, comprising the Siemens Technology department and the Headquarter of the Simulation and Testing Solutions (STS) business unit of Siemens Digital Industries. With a track record in developing industrial digitalized engineering platforms (ranging from PLM, SDM, optimization, simulation, MBSE up to physical testing) and fostering open and competitive software ecosystems, the Siemens Team enriches WP3 with expertise and resources. Leading the charge in WP3 is Philippe Barabinot, who has a background in Mathematics (Numerical Analysis) and Physics from the University of Paris VI. Philippe's journey in research engineering spans over 25 years, with extensive experience in Simulation within the Aerospace domain. As the work package leader, Philippe brings immense expertise to the table to guide the development of the ODP. Stay tuned for more updates as we delve deeper into the intricacies of WP4 in two weeks time and take a look at our first application case. 

The importance of systems engineering in product design; build platforms not products.   The road to making a product is a long and winding path. It is unlikely that changes in direction don’t occur. As we start the process of understanding the needs of the user, we problem solve user need but also manufacturing needs, as in most cases, things need to be manufactured.   If we build and understand the systems we are creating, it allows us to design according to an overall platform requirement, this has some important benefits:   1.    The designs can be broken down to very functional elements; this allows us to evaluate solutions, when problems occur, with future development in mind. 2.    Risk in every part of the design and manufacturing process can be evaluated at much earlier stages, which aids point 1. 3.    Revisions and next generation products are easier and cheaper to develop as these systems can be easily designed and integrated with this in mind from the start.   Expanding on point 3 – MVP (minimum viable product) can sometimes be taken as the cheapest and easiest way to launch a product. In reality, it should be a platform suitable to meet the users needs that has not been taken further down the development stages yet.   Happy Friday everyone, it’s the first day of summer here in Bristol Pictures, because who doesn’t like looking at stuff; The images are prompts from PlaygroundAI. I used prompt “platform engineering product design”, the left image is using AI to expand the prompt and the right image is using just my 4-word prompt. The AI world vs what AI thinks the world is.   I love testing systems, and testing AI is such an interesting process. As much as they are machine learning, it’s great to learn from them too.

5 Essential Engineer Apps to Boost Productivity 🚀⁣ ⁣ Juggling multiple projects, meeting deadlines, and staying ahead of the curve can be a daunting task for any engineer. ⁣ ⁣ But with the right tools, you can streamline your workflow, boost productivity, and achieve remarkable results. ⁣ ⁣ __ _⁣ Here are 5 must-have apps that will transform your engineering journey:⁣ ⁣ 1. Evernote⁣ Capture ideas, organize notes, and collaborate with teams seamlessly.⁣ ⁣ 2. Onshape⁣ Create, edit, and share 3D models in real-time with cloud-based CAD.⁣ ⁣ 3. Jira⁣ Plan, track, and manage projects efficiently using agile methodologies.⁣ ⁣ 4. GitHub⁣ Store, manage, and share code securely while collaborating with teams using Git.⁣ ⁣ 5. Wolfram Mathematica⁣ Perform complex mathematical computations, visualize data, and automate tasks with ease.⁣ ⁣ __ _⁣ Empower Your Engineering Career:⁣ ⁣ These powerful apps will not only elevate your productivity but also open doors to new possibilities in your engineering career. ⁣ ⁣ Download them today and experience the difference!⁣ ⁣ __ _⁣ 🏗 Find all your industrial engineering needs in one place! Visit Now!⁣ 👉 drsengineering.ae⁣ ⁣ ✅ Let’s Follow Us & Innovate Together!⁣ 🔁 Repost to share with your Network!⁣ ⁣ #engineeringjobs #engineeringcareer #learnengineering #studyengineering #engineeringapplication

The premium version of RapidGPT, now available, includes a host of advanced features designed to enhance the hardware design experience: More Accurate Answers Integrated Third-Party IP Catalog with Conversational Documentation AutoCheck™: Automated HDL Syntax Auditor AutoFix™: AI-Based HDL Syntax Correction AutoDoc™: AI-Powered Documentation and Source Code Annotation Priority Access to New Features and Improvements Priority Support “RapidGPT is not just a tool; it's a game-changer for hardware engineers,” said Prof. Pierre-Emmanuel Gaillardon, CEO of PrimisAI. “With these new features, we are not only enhancing accuracy but providing a more intuitive and efficient design journey for our users.” “The world has not witnessed this level of automation in the last decade,” added Dr. Naveed Sherwani, Chairman of PrimisAI. “RapidGPT is set to revolutionize hardware design, offering improvements such as enhanced accuracy, streamlined workflows, and accelerated time-to-market. This marks a significant leap forward in hardware engineering.” PrimisAI, the premier destination for cutting-edge hardware design automation, ensures an unparalleled hardware design experience. With RapidGPT at the forefront, the company continues to revolutionize the EDA landscape, making it an indispensable tool in every engineer's toolbox. For more information about PrimisAI, please visit www.primis.ai.