Patrick Forgione, MSE’s Post

10 years of System Engineering, 6 months with Prompt Engineering - here's my take!" (The truth lies in the way you approach it and not the technique itself)   I worked a lot on the Engineering DuoSolver's prompt Stepping back, here is how i see Prompt Engineerring   Understanding Prompt and System Engineering - System engineering ensures components work efficiently together in a physical environment. - Prompt engineering combines words to instruct a Large language model (LLM). - System engineering not only predicts objects behaviors but considers its reactions. - Prompt engineering not only predict the next word but encapsulates a world model. Bridging both disciplines: - I needed to address Problem Solving, I opted for an augmentation. - I combined my own experience and AI using Prompt Engineering. - I used known system engineering frameworks for my prompt.     Here is the analogy:   I structured the prompt as an Engineering project:   - Mission & Context = Project Scope - Instructions = Work breakdown structure (WBS) - Rules = Requirements - Variables = Project Deliverables - Conversation Flow = Standard operating procedures (SOPs) - Chain of Thought Function = Project Team - Steps = Project Planning   I released the prompt with a System Engineering approach:   - Requirements and virtual design - Prompt prototypes of increasing relevance. - Experimental testing with iterative improvements. - Final evaluation and release.   Here are the limits: - This is an analogy, not an Engineering benchmark - LLMs are packed intelligence but our knowledge is key. - Prompt Engineering can guide LLMs but the engine is on their side. - Prompt Engineering is only a technique and not an absolute solution.     Final Thoughts: The power of LLMs or AI in general is undeniable, they are much more than just words. Advanced Prompt Engineering can provide robust project frameworks but it remains a single tool. LLMs are facilitators but our critical thinking is a must for informed decisions   My target: stacking AI skills (Prompt Engineering done) and use them as a leverage for my Engineering projects!      

LogicProgs Engineering has always been an integral part of our future. We rely on engineers to create the technologies, systems, and structures that will help our planet progress and become a better place to live. As technology continues to evolve, so too does the need for engineers to keep up with the latest developments in order to ensure our future is brighter. With this in mind, it is important to understand how LogicProgs can help engineers engineer a better future. This article will explore what LogicProgs are, their benefits, and how they can be used to help engineers create solutions to today’s complex problems. First, let’s define what LogicProgs are. LogicProgs are computer programs that utilize logic programming techniques to solve complex problems. In other words, a logic program is a series of instructions that can be used to solve a given problem. This can be done by breaking down the problem into smaller, more manageable pieces. LogicProgs are most commonly used in engineering and computer science. They can be used to develop and test algorithms, create simulations, and develop computer programs. They can also be used to analyze data and identify patterns and trends. One of the most important benefits of using LogicProgs is that they can help engineers engineer a better future. By utilizing these powerful tools, engineers can develop solutions for today’s complex problems more quickly and efficiently. This can help reduce costs associated with engineering projects and allow engineers to focus on the big picture. In addition, LogicProgs can help engineers develop solutions that are more reliable and accurate. By breaking down the problem into smaller pieces, engineers can test various solutions and identify which ones are most likely to work. This can help reduce the time and money spent on testing and debugging. Finally, LogicProgs can help engineers create solutions that are more efficient and cost-effective. By utilizing these powerful tools, engineers can develop solutions that are more efficient and require fewer resources. This can help reduce costs associated with engineering projects and allow engineers to focus on the big picture. Overall, LogicProgs are an invaluable tool for engineers. They can help engineers engineer a better future by providing them with powerful tools that can be used to develop and test algorithms, create simulations, and analyze data. By utilizing these tools, engineers can develop solutions that are more reliable and accurate, and that require fewer resources. This can help reduce costs associated with engineering projects and allow engineers to focus on the big picture.

LogicProgs is revolutionizing engineering in a way that has never been seen before. The company is making it easier for engineers to develop and deploy complex solutions faster and more efficiently than ever before. LogicProgs is an innovative software engineering platform that is designed to make the development process more efficient and easier to use. The platform focuses on giving engineers the tools they need to create and deploy solutions in a timely and cost-effective manner. It is a cloud-based platform that provides engineers with access to the latest technology and tools to develop complex engineering solutions. LogicProgs is designed to reduce the time and cost associated with engineering projects. It offers engineers the ability to work collaboratively with other engineers on a project. This allows for faster development and deployment of solutions. LogicProgs also allows engineers to access the latest technology and tools without having to invest in expensive hardware or software. This makes it easier for engineers to stay up to date with the latest technology and tools that are available. LogicProgs also provides engineers with access to a wide range of resources such as tutorials, videos, and support documents. This makes it easier for engineers to learn new skills and stay up to date with the latest technology and tools. LogicProgs is revolutionizing the engineering industry by making it easier for engineers to develop and deploy solutions faster and more efficiently. It is a revolutionary platform that is designed to make the development process more efficient and easier to use. LogicProgs is making engineering projects more efficient and cost-effective. It is making it easier for engineers to stay up to date with the latest technology and tools. It is also making it easier for engineers to collaborate with other engineers on projects. All of these features are making LogicProgs a revolutionary platform that is revolutionizing engineering.

Model-Based Systems Engineering (MBSE): It is an approach to systems engineering where graphical, mathematical, and textual models are used to define and analyze system requirements, design, and functionality. Unlike traditional methods, which often rely on documents and discrete sets of data, MBSE offers a more integrated and coherent representation of a system, which makes it easier to manage complexity and improve communication among stakeholders. MBSE has gained popularity due to Complexity Management in systems become increasingly complex, traditional document-based approaches struggle to manage intricacies and dependencies. MBSE provides a more coherent way to manage complex systems. It Improved the Communication, a unified model enhances understanding among various stakeholders, including engineers, designers, and managers, leading to better collaboration. The reuse of components and design elements within a model can significantly reduce development time and costs.Error Reduction by identifying issues early in the development process, It minimizes the risk of costly errors or rework later on, leading to higher quality products. Requirements, design elements, and functionalities can be easily traced within the model, ensuring compliance with regulations and making it easier to manage changes. It allows for robust simulation under different scenarios, providing valuable insights into system performance, reliability, and other attributes, which is often not possible in document-based methods. it is inherently suited for integrating multi-disciplinary efforts, such as mechanical, electrical, and software engineering, into a single coherent model.Given that all information is stored in a unified model, it's easier to adapt to changes in requirements or technologies. The use of standardized languages like SysML makes it easier to share models across different teams or even different organizations, fostering better collaboration and consistency. Supports the management of a system throughout its entire lifecycle, from initial conception through to decommissioning, making it easier to implement upgrades or modifications.Given these advantages, MBSE has become a go-to methodology for managing the lifecycle of complex systems. #mbse #systemsengineering #softwaredevelopment #modelbaseddesign

If you are working in an engineering team this post is for you. Write code which is monotonous in nature. Do you know why something is called monotonous? Because“it is predictable”. That's how your code should be “Predictable”. You should be able to predict file names, position of particular class, variables, the flow of the code. Predictability in the code saves a lot of time - it's a key contributor to improved engineering efficiency. - Searching code becomes easy - Writing code becomes easy - Code design become a lot more consistent - Helps to establish code guidelines across teams - Keeps technical debt to minimal What can make code predictable? - File names should be self explanatory, format should be consistently followed e.g For the home screen it's file can be HomeScreen and not MainScreen or PrimaryScreen - Follow defined guideline to position similar categories of variables and methods e.g all the private variables should be placed together - Follow standard design guidelines which are generally accepted across industries - Document code better What else do you implement to improve engineering efficiency? #engineeringbytes

Previously, I had a fixed mindset regarding how to tackle any system design question. Start with the functional and non-functional requirements, do some back-of-the-hand calculations to depict the scale of the system, discuss a few core functionalities, and start drawing boxes for application servers, load balancers, queues, and databases. While this approach works most of the time for cracking a few interview rounds, Arpit Bhayani's course forces you to ditch this conventional thought process and makes you dive deeper into systems and their actual implementations. This course definitely is a goldmine not only in terms of the content but most importantly, how it sparks curiosity within you to think of system designs beyond just interviews. 1. This course will teach you how to build a solution for any system from the ground up with the right intuition and thought process.  2. Arpit has very smartly covered almost all the fundamental systems out there so that any new system can be easily built on top of it. “Just mix and match”.  3. One particular thing I liked about the course was the prototypes he created to explain the concepts. I mean it’s one thing to know the concept and completely different to see it live in action. Kudos for putting in the effort to make the course more engaging.  4. If you were ever curious about how systems like the Flash sale, Cricbuzz commentary, and Cricket live feed (My favorite discussion) work, look no further because these discussions will literally make you admire how awesome engineering truly is. A course is only as good as the instructor and Surprise!! Surprise!! Arpit is very good at the teaching part as well. You can sense the enthusiasm and curiosity in his way of teaching. He would patiently answer all the questions asked even though the class duration was well past 4 hours. He is open to new ideas and solutions and doesn’t make you feel any lesser even for a bit. For any senior engineer looking to make an impact at their workplace or waiting for that engineering spark to be reignited again, this course is a must! Thank you for proving that true engineering is well beyond interviews. "SUPERB!"

🛠️ Celebrating Engineer's Day! 🛠️ On this special day, let's reflect on the essence of being an engineer. 🎉 Remember, knowledge should be a source of humility, not arrogance. 🧠 It's a tool to learn, grow, and innovate. 💡 And here's a delightful reminder that sometimes, the person across from you might just know a bit more. 🔄 Embrace it, for that's where true growth happens. 🌱 Case in point? An interaction where someone questioned UML knowledge, only to find out they were speaking to the *inventor*! 😲 Here's to the curiosity, the pursuit of knowledge, and the humbling journey of engineering. 🚀 Happy Engineer's Day! 🛠️🌟 #EngineersDay #Innovation #HumilityInEngineering #KeepLearning

🚀💡 Navigating the Complexities of Knowledge-Based Engineering (KBE) Challenges 💡🚀 Knowledge-Based Engineering (KBE) is an innovative field that has the potential to revolutionize engineering, but it's not without its share of hurdles. Let's delve into the challenges that illuminate the path to realizing KBE's transformative power: 🔍 **Knowledge Acquisition:** Harvesting and translating expert insights into machine-readable formats can be time-consuming and intricate, bridging the gap between human intuition and digital understanding. 🔗 **Integration of Diverse Data:** The challenge of harmonizing data from varied domains like engineering, manufacturing, and materials is amplified by differences in formats and interpretations. 🔄 **Maintaining Knowledge:** Sustaining a knowledge reservoir that remains current and pertinent demands a constant effort, as engineering evolves with new practices and technologies. 🎯 **Knowledge Representation:** Conveying intricate engineering wisdom in a manner accessible to automated systems is a puzzle, often requiring techniques like rule-based systems and object-oriented models. 🧩 **Siloed Data:** In some instances, isolated data pockets within different engineering departments can hinder the creation of a unified and comprehensive knowledge base. 🌐 **Interdisciplinary Nature:** Crafting a design often requires insights spanning multiple disciplines. Integrating this multidisciplinary knowledge into a cohesive whole is a challenge. ⚖️ **Scalability:** As designs grow in complexity, ensuring the KBE system remains efficient and scalable becomes crucial to sustained success. 🤝 **User Acceptance:** Gaining trust in automated systems among engineers, particularly when they don't fully grasp the system's decision-making process, can be a hurdle. 🔮 **Uncertainty Handling:** Incorporating uncertainties intrinsic to design processes into a knowledge-based system's decision-making can be intricate. 🔧 **Customization:** Designing a flexible KBE system that accommodates diverse methodologies and company-specific practices can be a demanding task. 🔍 **Validation and Verification:** Rigorously confirming that the KBE system outputs align with engineering standards requires robust validation and verification mechanisms. 🔬 **Ethical Considerations:** Automating design decisions raises questions of accountability and responsibility, especially in cases of errors or oversights made by the system. Overcoming these challenges necessitates a blend of technological solutions, interdisciplinary collaboration, and sustained research and development endeavors. 🌟 **Calling All Innovators:** We invite you to share your experiences and insights! What challenges have you encountered while working with KBE? Let's spark a conversation and collectively navigate the exciting journey towards a transformed engineering landscape. #KBEChallenges #EngineeringInnovation #KnowledgeBasedEngineering #FutureEngineering

The paper proposes "Seamless Digital Engineering" (SDE) as a new paradigm for #digitalengineering tooling. The goal is to create an integrated system of tools that guarantees model coherence and integrity through elegant interfaces and formal verification of the full stack down to the hardware level. Current digital engineering relies on integrating many disparate tools, which creates fragility and drains resources. There is no overarching #systemsengineering #architecture guiding tool integration. Seamless integration requires common data schemas, live object representations, and unified interfaces to remove the "seams" between tools. Formal verification of interfaces and behaviors is needed. SDE refines digital engineering by adding the requirement of "elegance" - the system should be robust, efficient, minimize unintended consequences, and have an intuitive interface. Five key architecture tenets of SDE are proposed: Seamless Models, Composable Data, Live Objects, Seamless Workflows, and Clean-slate Cybersecurity. Achieving SDE is a "grand challenge" requiring transdisciplinary collaboration and a clean-slate approach not bound by legacy computing constraints. The paper defines and characterizes SDE as a new research direction and paradigm for model-based digital engineering. Developing an integrated, formally verified system of modeling tools remains an open challenge. Authors James Wheaton - Systems engineer at Colorado State University's Department of Systems Engineering. Background in model-based systems engineering. Daniel R. Herber - Professor in Systems Engineering at Colorado State University. Published research on model-based systems engineering, SysML, and agile systems https://lnkd.in/ghFRS6c9

Designing systems requires a deep understanding of the problem statement and it is better to never write your first line of code unless you understand the context, input, expected output, and potential outcome well; because; Engineering is not about writing code, but about writing code that matters.