Recently, I’ve noticed a trend on LinkedIn where many designers are rebranding themselves as Computational Designers, Engineers or Specialists. It seems that after creating just one Grasshopper or Python script, some believe they have transitioned into programmers within the AEC industry. In this article, I’ll dive deeper into who a Computational Designer really is, the skills needed to excel in this role, the main challenges faced, and how you can jump on this career path.
Table of Contents
1. Who Is a Computational Designer?
A Computational Designer is basically a designer who understands how computers can solve tough problems in their field. They use computer-based methods to handle engineering challenges more effectively. They gain an edge over regular designers by using the latest technologies in their area of interest.
There’s not much difference between a Computational Designer, a Specialist, and an Engineer. The main difference is in how they solve problems and sometimes the specific field they work in.
The role of a Computational Designer is becoming more common, and its importance in the future is huge. As technology keeps advancing, the need for experts who can connect design with computation will keep rising. Especially in the AI field, where programming skills might not be as crucial as they are today. So, what skills will be needed if not programming?
2. Essential Skills for a Computational Specialists
Many believe that creating a single Grasshopper script qualifies them as a Computational Designer. However, the truth is that being a Computational Designer is not about mastering specific tools; it’s about developing a specific set of skills.
- Problem-Solving: This involves breaking down large problems into manageable pieces, devising step-by-step solutions, addressing issues that arise, and testing different approaches to find the best outcome.
- Critical Thinking: A Computational Designer must question assumptions, make informed decisions based on reliable data, and meticulously verify results to ensure accuracy.
- Data Analysis and Interpretation: This skill involves collecting, cleaning, and analyzing data to extract meaningful patterns or insights. It’s not just about handling data but interpreting it to inform design decisions.
3. The Role of Tools in Computational Design
While tools are important, they are secondary to the skills mentioned above. Even something as simple as using Excel for complex simulations or advanced data analysis can qualify as computational work. The key is not the tool itself but how effectively it is used to solve engineering problems. However, thanks to programming you can easily gain skills in Problem-Solving and Critical Thinking.
Visual Programming
Tools like Grasshopper and Dynamo offer an excellent entry point into programming. Visual programming is becoming increasingly popular, even being introduced to children in schools because of its intuitive, low-code approach. These tools allow designers to see the immediate impact of their programming efforts, which is both motivating and rewarding. The instant feedback provided by visual programming helps designers understand the power of computation quickly and effectively.
Text-Based Programming
As projects grow in complexity, visual scripts can become cumbersome and difficult to manage. This often necessitates a shift to text-based programming, where more advanced functionalities can be accessed, such as creating custom components or interfacing directly with software APIs.
I once believed that visual programming would suffice for all my needs within the AEC industry. I was wrong. As I delved deeper into computational design, I realized that learning a text-based language was essential. But which language should you choose?
Both Python and C# are popular in the AEC industry, each with its own strengths and weaknesses. Choosing the right one depends on your specific needs and the community support available for each language.
Join this fun and useful workshop to discover which programming language is best for you –Â REGISTER HERE.
4. Challenges in Becoming a Computational Designer
Becoming skilled in computational design takes a lot of time and effort. Many companies are hesitant to invest in research and development because the benefits of computational design aren’t instantly clear. It takes time to apply these methods and see cost savings, which requires patience—a quality not everyone has.
Another challenge is the fast pace of technology. Keeping up with new tools, software, and techniques can be tough, and some people may find it hard to stay updated, which can make them fall behind or lose confidence in their skills.
Another challenge is the pull of other industries. Once engineers or architects build their computational skills and feel confident, they might be tempted to move to industries where their skills are more in demand and better paid. The AEC industry often finds it hard to match the IT sector’s salaries, leading to a loss of talent.
5. Do Engineers Need Programming Skills at all?
With the rise of AI, learning programming isn’t always necessary—AI can create code in any language you need. It can even translate code from one language to another with a simple command, a process called prompt engineering.
However, creating good prompts isn’t just a matter of chance; it’s a skill that needs to be developed. When you learn programming, you gain insight into the Computational Thinking Process, which is essential for prompt engineering. As we shift toward using natural language to guide AI, understanding how computers solve problems becomes more and more important.
While AI can assist with coding, having a foundation in programming is invaluable. It equips you with the computational thinking skills necessary to write effective prompts and understand how to structure problems for computer-based solutions. So, can you become a great prompt engineer without programming skills? It’s possible, but having those skills certainly gives you a significant advantage.
6. Where to Start?
Your starting point depends on your current skill level.
If you’re new to programming, I recommend starting with Grasshopper.
It’s versatile and compatible with many software platforms, making it an excellent first step. I’ve prepared a free guide that covers all the basics you need to get started, along with free materials to help you learn: Download 5 Steps to Learn Grasshopper.
Later, you can join the waiting list for my upcoming training to join more than 700 students from around the world who have become engineers without any prior experience.
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If you’re already familiar with visual programming, it’s time to step up your game and dive into text-based programming. Learn from the best experts and take an active part in revolutionizing the AEC industry.
Start a new, exciting career path as a Computational Designer—get better job offers and stand out in the industry. Unlock powerful features of AEC software with Open API—do more with your software and create your own tools. Break free from the limits of visual programming—solve harder problems and make cooler things.
Sign up for the waiting list to get the best offer at ProgrammingInAEC.com.
