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How to increase your Design Efficiency by 50%?

In the fast-paced world of design, efficiency is crucial to stay ahead of the competition and deliver exceptional results. Fortunately, modern design tools like Figma offer a plethora of features that can significantly enhance your productivity.

Over the past few days, our team has been buzzing with excitement ever since Figma released its most significant update yet. We can’t stop discussing the amazing new updates and features that have made our work easier than ever before. For designers, Figma is an indispensable tool for day-to-day operations and their workflow revolves around Figma. In this article, we will share the top 3 features that have significantly improved our lives as designers and given our workflow a much-needed boost. So, without further ado, let’s jump right in! �� 

Auto Layout

New Auto Layout Wrap

The auto layout was very powerful before but with the latest update, Figma added a new wrap feature into it which makes it more powerful than ever. Let me explain this feature with an example. Let’s say you have tags that scroll.

Now when you make responsive variants of this mobile screen you have to reframe those components and rearrange them again but with this wrap feature you just have to resize the parent frame and that’s it! Boom �� your responsive tag component is ready, how awesome is this? 

Auto Layout also has Min-Width and Max-Width options in Height and Weight which helps you to set min and max width to any component which means less than min-width you can set the component to look to any responsive screen. This way you have a fully responsive component that is ready to use in any size of art-board. 

If you use Auto Layout more frequently it saves you so much time in situations when you are making changes in design eg, when you change content or update content, because of Auto Layout, it adjusts itself accordingly and you don’t have to change the layout manually again according to content which is a huge time saver and ultimately boosts your workflow. 

Variables

Variables

Variables Design tokens: Variables in Figma works awesome.  

Now you might be wondering what is all so special about variables. They are just placeholders that hold value and you can use them anywhere but in design, it’s more than that. Let’s understand the power of variables with an example. 

Assume that you are working on a Design system that has Light and Dark modes. Now traditionally you will work on both designs but with Figma, you can now create variables of colors for both Light and Dark modes and assign colors to a component. Once this is done, you just need to change the Art-board parent variable to dark and your dark mode design is done. 

Variables can be used anywhere- in width, height, colorcode, and Text style. It will help you in prototyping which will be covered later. Variables will change your Design and Prototyping game to the next level for sure. 

Dev Mode

Dev Mode

Dev mode is built for developers but it also helps the designers when you give design handoff to them. With the latest updates, it has become more powerful than ever which makes the handoff process very easy. Let’s learn more about Dev Mode.

If you click on the frame menu in Figma, with the Frame and Slice tool you can now see one more tool called section which is very much similar to the art-board tool but it’s for Developers. How? 

When you create a new section and add your developer-ready art-boards into them (Drag and Drop will work) set the status to Mark as ready for Dev which is a small button just beside the section title. As a designer, you are pretty much done now even though your Figma file has hundreds of artboards, but only the developer will be able to work on those artboards in the developer-ready section. 

Now you must be thinking about how it boosts a designer’s workflow. Post development, support is also a part of the designer workflow which means this feature will not only save your time in development. 

Dev Mode Features: 

1. Track design history: This simply means now the developer can see the changes you made between 2 or more designs and also compare them. This feature will help them track product improvement over time and better collaboration. 

2. Dev Resources: You can also mention your developer links to the developers to help them better understand and build a component. 

3. Code Section: This will remind you of the tool Zeplin which is very similar but more powerful and has a code layout that looks like the Chrome dev tool layout version. It shows the Margin, Border, Padding, Width, and Height information of a selected component or object. Under these, we have layout and style sections that generate CSS code for that selected thing. The code section also has Units (Px, rem, custom scale) options and also has a dropdown that generates IOS(SwiftUI, UIKit), Android(Compose, XML), and CSS code which is useful for all kinds of developers. 

The rest of the features are the same like colours and Assets and Export which helps in development. 

One more thing that helps the developers to work is the new Figma for VSCode plugin which now can be installed in VSCode.

So basically you can Open any Figma Document in the VSCode editor and see the Side-by-side view of your Design on the left side while you are writing the code for it.

Figma for VS Code

Conclusion:

In conclusion, embracing these three powerful features can supercharge your design efficiency by up to 50%, meet tight deadlines with ease, and wow your clients with exceptional designs, whether you are a seasoned designer looking to enhance your skills or a newcomer eager to make an impact.

Want to read more on designing?

Check out our latest blog: Response Biases in User Research: A Guide for Culturally and Behaviorally Relevant Insights

About the Author: Akshay Vinchurkar is a lead designer at Mantra Labs with 5 years of experience in Design. He is also an active Member of the Figma Community and loves to write about Open source and Design.

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Will AI Be the Future’s Definition of Sustainable Manufacturing?

Governments worldwide are implementing strict energy and emission policies to drive sustainability and efficiency in industries:

  • China’s Dual Control Policy (since 2016) enforces strict limits on energy intensity and usage to regulate industrial consumption.
  • The EU’s Fit for 55 Package mandates industries to adopt circular economy practices and cut emissions by at least 55% by 2030.
  • Japan’s Green Growth Strategy incentivizes manufacturers to implement energy-efficient technologies through targeted tax benefits.
  • India’s Perform, Achieve, and Trade (PAT) Scheme encourages energy-intensive industries to improve efficiency, rewarding those who exceed targets with tradable energy-saving certificates.

These policies reflect a global push toward sustainability, urging industries to innovate, reduce carbon footprints, and embrace energy efficiency.

What’s driving the world to impose these mandates in manufacturing?

This is because the manufacturing industry is at a crossroads. With environmental concerns mounting, the sector faces some stark realities. Annually, it generates 9.2 billion tonnes of industrial waste—enough to fill 3.7 million Olympic-sized swimming pools or cover the entire city of Manhattan in a 340-foot layer of waste. Manufacturing also consumes 54% of the world’s energy resources, roughly equal to the total energy usage of India, Japan, and Germany combined. And with the sector contributing around 25% of global greenhouse gas emissions, it outpaces emissions from all passenger vehicles worldwide.

These regulations are ambitious and necessary. But here’s the question: Can industries meet these demands without sacrificing profitability?

Yes, sustainability initiatives are not a recent phenomenon. They have traditionally been driven by the emergence of smart technologies like the Internet of Things (IoT), which laid the groundwork for more efficient and responsible manufacturing practices.

Today, most enterprises are turning to AI in manufacturing to further drive efficiencies, lower costs while staying compliant with regulations. Here’s how AI-driven manufacturing is enhancing energy efficiency, waste reduction, and sustainable supply chain practices across the manufacturing landscape.

How Does AI Help in Building a Sustainable Future for Manufacturing?

1. Energy Efficiency

Energy consumption is a major contributor to manufacturing emissions. AI-powered systems help optimize energy usage by analyzing production data, monitoring equipment performance, and identifying inefficiencies.

  • Siemens has implemented AI in its manufacturing facilities to optimize energy usage in real-time. By analyzing historical data and predicting energy demand, Siemens reduced energy consumption by 10% across its plants. 
  • In China, manufacturers are leveraging AI-driven energy management platforms to comply with the Dual Control Policy. These systems forecast energy consumption patterns and recommend adjustments to stay within mandated limits.

Impact: AI-driven energy management systems not only reduce costs but also ensure compliance with stringent energy caps, proving that sustainability and profitability can go hand in hand.

2. Waste Reduction

Manufacturing waste is a double-edged sword—it pollutes the environment and represents inefficiencies in production. AI helps manufacturers minimize waste by enhancing production accuracy and enabling circular practices like recycling and reuse.

  • Procter & Gamble (P&G) uses AI-powered vision systems to detect defects in manufacturing lines, reducing waste caused by faulty products. This not only ensures higher quality but also significantly reduces raw material usage.
  • The European Union‘s circular economy mandates have inspired manufacturers in the steel and cement industries to adopt AI-driven waste recovery systems. For example, AI algorithms are used to identify recyclable materials from production waste streams, enabling closed-loop systems. 

Impact: AI helps companies cut down on waste while complying with mandates like the EU’s Fit for 55 package, making sustainability an operational advantage.

3. Sustainable Supply Chains

Supply chains in manufacturing are vast and complex, often contributing significantly to carbon footprints. AI-powered analytics enable manufacturers to monitor and optimize supply chain operations, from sourcing raw materials to final delivery.

  • Unilever uses AI to track and reduce the carbon emissions of its suppliers. By analyzing data across the supply chain, the company ensures that partners comply with sustainability standards, reducing overall emissions.
  • In Japan, automotive manufacturers are leveraging AI for supply chain optimization. AI algorithms optimize delivery routes and load capacities, cutting fuel usage and emissions while benefiting from tax incentives under Japan’s Green Growth Strategy.

Impact: By making supply chains more efficient, AI not only reduces emissions but also builds resilience, helping manufacturers adapt to global disruptions while staying sustainable.

4. Predictive Maintenance

Industrial machinery is a significant source of emissions and waste when it operates inefficiently or breaks down. AI-driven predictive maintenance ensures that equipment is operating at peak performance, reducing energy consumption and downtime.

  • General Electric (GE) uses AI-powered sensors to monitor the health of manufacturing equipment. These systems predict failures before they happen, allowing timely maintenance and reducing energy waste.
  • AI-enabled predictive tools are also being adopted under India’s PAT scheme, where energy-intensive industries leverage real-time equipment monitoring to enhance efficiency. (Source)

Impact: Predictive maintenance not only extends the lifespan of machinery but also ensures that energy-intensive equipment operates within sustainable parameters.

The Road Ahead

AI is no longer just a tool—it’s a critical partner in achieving sustainability. By addressing challenges in energy usage, waste management, and supply chain optimization, AI helps manufacturers not just comply with global mandates but thrive in a world increasingly focused on sustainability.

As countries continue to tighten regulations and push for decarbonization, manufacturers that embrace AI stand to gain a competitive edge while contributing to a cleaner, greener future.

Mantra Labs helps manufacturers achieve sustainable outcomes—driving efficiencies across the shop floor to operational excellence, lowering costs, and enabling them to hit ESG targets. By integrating AI-driven solutions, manufacturers can turn sustainability challenges into opportunities for innovation and growth, building a more resilient and responsible industry for the future.

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