𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗗𝗲𝘀𝗶𝗴𝗻 𝗶𝘀 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗮 𝘀𝗲𝘁 𝗼𝗳 𝘁𝗼𝗼𝗹𝘀 - 𝗶𝘁'𝘀 𝗮 𝗺𝗶𝗻𝗱𝘀𝗲𝘁! 🧠

From early CAD software to generative AI; 𝗖𝗗 𝗼𝗿 𝗖𝗼𝗗𝗲 encompasses a wide variety of computational strategies for aiding better design processes.

As a computational designer, it's imperative to nurture a deep understanding of computer science and an intuition for solving design problems with intelligent computation.

🕰️Between the late 1950s to early 2000s, CAD software revolutionized the AEC industry giving rise to the emergence of BIM and CD. Within the first decade of the 21st century, manual hand drafting had become largely obsolete for anything beyond the schematic design stages. And by 2020, many studios sought to adopt BIM and other technologies to further streamline their business operations.

Reputed architects like Zaha Hadid Architects and Frank Gehry pioneered and promoted the use of tools like Grasshopper (2007) and Autodesk Dynamo (2011) for architectural design. However, this also led to the incorrect perception that CD is only useful for the rationalization of complex curvaceous designs. While it's still not as ubiquitously in use as CAD or BIM, the benefits offered by CD at every stage of the design process and for every project scale are undeniable.

The visual programming interface of CD tools led to an increased agency with computer programming, computational geometry and machine learning. Generative design, genetic algorithms and now artificial intelligence are being used in studios to supercharge design workflows.

♾️As it continues to evolve, CD has blurred the lines between CAD, BIM, XR, AI and other technologies. Enabling better interoperability between tools, building more streamlined workflows and improving collaboration on design - it provides the reigns for better harnessing these technologies.

Even for the simplest of projects, CD can add immense value at every step - from optimizing building mass to analyzing building performance. Design rationalization and digital fabrication are just a small part of what CD has to offer. And with new tools like McNeel Europe Grasshopper2, Autodesk Forma and others, the future of this field is very bright.

CD is the cement between the various software and hardware blocks used in the AEC industry - 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗔𝗘𝗖𝗧𝗲𝗰𝗵. Teams that employ CD strategies are far more effective and efficient; saving on time, effort and cost in delivering high quality results.

𝗧𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗔𝗘𝗖 𝗶𝘀 𝗵𝗶𝗴𝗵𝗹𝘆 𝗰𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹.

Pairing talented designers with powerful tools has historically led to the most success, and the same continues to apply here. One without the other is simply useless! And as the tools evolve, so must the designers using them.

C# vs. Python for AECTech

⚠️𝗖# is the programming language you should learn for a successful career as a computational designer. 𝗡𝗼𝘁 𝗣𝘆𝘁𝗵𝗼𝗻.

1. 🥷🏽𝗩𝗲𝗿𝘀𝗮𝘁𝗶𝗹𝗶𝘁𝘆: Unity3D, Blazor WebAssembly,, Xamarin, WPF, Grasshopper3D/Rhino, Dynamo/Revit - these are just some of the popular platforms that support C#. That's games, web apps, plugins and more - C# can be used directly in a variety of domains across nearly all hardware platforms natively. For a multidisciplinary professional, this versatility is priceless!

2. 🛟𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆: C# is the language used to build most production-ready software - if a software package is to be built for public use, most developers will prefer using C# rather than Python. It's strict syntax and type system enforces safety and prevents errors at compile time. Python is only ever used for in-house prototyping or quick automation solutions. In fact, many software tools today have a lifecycle that looks like this: Internal/first prototype using Python ➔ Rebuilt for public/reliable use with C# ➔ Wrapped in a web application for scaling up. eg. Ladybug Tools ➔ Pollination Cloud

3. 🦾𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀: C# is a more verbose and complete low-level language which runs on the cross-platform .NET standard. It compiles and runs objectively faster than Python in most scenarios. Even the most optimized Python libraries leverage C or C++ to achieve better performance. In practice as well, you will start seeing the limitations of using Python for development fairly quickly as the complexity of your application increases.

4. ⭐𝗗𝗲𝗺𝗮𝗻𝗱: Sadly, C# developers are a rare breed. While there are increasingly more job openings that require C# experience, there aren't nearly enough candidates to fulfill the market needs. Moreover, C# developers generally find it much easier to learn and use other programming languages like JavaScript and Rust, which are also high-demand languages.

Of course, this doesn't mean that Python doesn't have it's merits!

💫Python is far easier to learn. For a beginner who is new to programming, it offers a quick start especially if your job does not require programming frequently. If you don't intend to specialize in computational design, this may be sufficient for the occasional script or two. It's much more legible and quick to run with; like an actual Python 🐍 - minimal, but agile and powerful. But in that analogy, C# is like a dragon! 🐉

If short-term accessibility is important to you, stick to Python. But if you want to dive deeper into computational design and tool development as a career specialization, it's never too late to start learning!

𝗙𝘂𝗻 𝗳𝗮𝗰𝘁: C# is a newer language than Python - it was first released in 2000, while Python has been available since 1991!