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Building a layered approach with AI

We have made significant strides in the evolution of design. It is crucial for us to recognize that disruptive technologies have always been the catalyst for change, shaping the way we design and communicate. In an era before the printing press, people painstakingly wrote books by hand. Similarly, the emergence of mobile phones, computers, and the internet has changed everything.

Embracing these changes and adapting to newer technologies is essential for staying relevant in the field of design. There are designers who use Adobe Dreamweaver and Photoshop to create website UI. It feels like a different era since the introduction of more recent software such as Figma, and Adobe XD. However, the core principle remains the same: staying pertinent requires adaptability as the times change.

While there’s an ongoing discussion about AI potentially replacing design jobs, my personal perspective is that we should not fear it but rather leverage it to our advantage since AI is an execution tool. AI is poised to simplify our lives. When you consider the broader picture, your value as a designer in the upcoming years will be determined by your ability to synthesize innovative ideas to solve problems. Let me elaborate on how, as designers, we must strengthen our problem-solving muscles.

How the layered approach works:

Tools like Midjourney are designed for image-specific tasks, enabling the creation of visually appealing images. Chat GPT on the other hand is a text-based AI model, although now with the incorporation of DALL-E inside Chat GPT, it gives image outputs too.

I want you to imagine for a second, what if you used Chat GPT to create nuanced prompts for Midjourney.

This is layering software on top of another software to receive your desired output. For this to work, you have to first train your Chat GPT agent on Midjourney’s functionality and then prompt using a basic framework.

The framework works like this:

First, you inform Chat GPT about your desired role or objective and define your approach or task. For example, ‘I am a skilled graphic designer who designs illustrations for top brands in India. You need to provide me with ideas for designing a coffee shop logo, along with some links for inspiration.’

Then, you specify your timeframe or any restrictions. For instance, ‘I can’t spend more than 30 minutes looking at inspiration, so please only provide the best ones you find that you believe would be most helpful.’

Finally, after training your agent, request Chat GPT to provide a prompt for Midjourney.

The key thing to remember while implementing this approach is to churn out a nuanced prompt that will serve as a base for your creative design process later. That’s it—two layers of software, and the pivotal layer comes into play once you’ve received the output: your creativity. You make AI as Robin to your Batman. Consider this as no longer needing to begin from a starting point. With AI tools such as these, people who have the potential to think clearly to formulate ideas would flourish. I encourage you to use these AI tools in your daily life to learn and become the best in your respective fields. 

There are many more tools that have come into the market such as for UI, a single line prompt can generate a whole app’s UI screens with tools like Uizard. Builder.io is a tool that uses AI to convert Figma design files into code. Recent developments also suggest that AI can help with user research for large organizations, potentially marking a paradigm shift in the UX industry, as these AI models have been trained on human behaviors, this has been put forth by fantasy.co. There is so much more to come, the least we can do is be prepared for it. 

I hope you had a good read and this article gave you a sense of what is waiting in our future.

About the Author: 

Shivani Shukla is a Senior UI & UX designer at Mantra Labs. Updating her knowledge and staying up to date with the current trends has always been her priority.

Further Readings:

Design and Technology Fusion Shaping the Future of Innovation

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Platform Engineering: Accelerating Development and Deployment

The software development landscape is evolving rapidly, demanding unprecedented levels of speed, quality, and efficiency. To keep pace, organizations are turning to platform engineering. This innovative approach empowers development teams by providing a self-service platform that automates and streamlines infrastructure provisioning, deployment pipelines, and security. By bridging the gap between development and operations, platform engineering fosters standardization, and collaboration, accelerates time-to-market, and ensures the delivery of secure and high-quality software products. Let’s dive into how platform engineering can revolutionize your software delivery lifecycle.

The Rise of Platform Engineering

The rise of DevOps marked a significant shift in software development, bringing together development and operations teams for faster and more reliable deployments. As the complexity of applications and infrastructure grew, DevOps teams often found themselves overwhelmed with managing both code and infrastructure.

Platform engineering offers a solution by creating a dedicated team focused on building and maintaining a self-service platform for application development. By standardizing tools and processes, it reduces cognitive overload, improves efficiency, and accelerates time-to-market.  

Platform engineers are the architects of the developer experience. They curate a set of tools and best practices, such as Kubernetes, Jenkins, Terraform, and cloud platforms, to create a self-service environment. This empowers developers to innovate while ensuring adherence to security and compliance standards.

Role of DevOps and Cloud Engineers

Platform engineering reshapes the traditional development landscape. While platform teams focus on building and managing self-service infrastructure, application teams handle the development of software. To bridge this gap and optimize workflows, DevOps engineers become essential on both sides.

Platform and cloud engineering are distinct but complementary disciplines. Cloud engineers are the architects of cloud infrastructure, managing services, migrations, and cost optimization. On the other hand, platform engineers build upon this foundation, crafting internal developer platforms that abstract away cloud complexity.

Key Features of Platform Engineering:

Let’s dissect the core features that make platform engineering a game-changer for software development:

Abstraction and User-Friendly Platforms: 

An internal developer platform (IDP) is a one-stop shop for developers. This platform provides a user-friendly interface that abstracts away the complexities of the underlying infrastructure. Developers can focus on their core strength – building great applications – instead of wrestling with arcane tools. 

But it gets better. Platform engineering empowers teams through self-service capabilities.This not only reduces dependency on other teams but also accelerates workflows and boosts overall developer productivity.

Collaboration and Standardization

Close collaboration with application teams helps identify bottlenecks and smooth integration and fosters a trust-based environment where communication flows freely.

Standardization takes center stage here. Equipping teams with a consistent set of tools for automation, deployment, and secret management ensures consistency and security. 

Identifying the Current State

Before building a platform, it’s crucial to understand the existing technology landscape used by product teams. This involves performing a thorough audit of the tools currently in use, analyzing how teams leverage them, and identifying gaps where new solutions are needed. This ensures the platform we build addresses real-world needs effectively.

Security

Platform engineering prioritizes security by implementing mechanisms for managing secrets such as encrypted storage solutions. The platform adheres to industry best practices, including regular security audits, continuous vulnerability monitoring, and enforcing strict access controls. This relentless vigilance ensures all tools and processes are secure and compliant.

The Platform Engineer’s Toolkit For Building Better Software Delivery Pipelines

Platform engineering is all about streamlining and automating critical processes to empower your development teams. But how exactly does it achieve this? Let’s explore the essential tools that platform engineers rely on:

Building Automation Powerhouses:

Infrastructure as Code (IaC):

CI/CD Pipelines:

Tools like Jenkins and GitLab CI/CD are essential for automating testing and deployment processes, ensuring applications are built, tested, and delivered with speed and reliability.

Maintaining Observability:

Monitoring and Alerting:

Prometheus and Grafana is a powerful duo that provides comprehensive monitoring capabilities. Prometheus scrapes applications for valuable metrics, while Grafana transforms this data into easy-to-understand visualizations for troubleshooting and performance analysis.

All-in-one Monitoring Solutions:

Tools like New Relic and Datadog offer a broader feature set, including application performance monitoring (APM), log management, and real-time analytics. These platforms help teams to identify and resolve issues before they impact users proactively.

Site Reliability Tools To Ensure High Availability and Scalability:

Container Orchestration:

Kubernetes orchestrates and manages container deployments, guaranteeing high availability and seamless scaling for your applications.

Log Management and Analysis:

The ELK Stack (Elasticsearch, Logstash, Kibana) is the go-to tool for log aggregation and analysis. It provides valuable insights into system behavior and performance, allowing teams to maintain consistent and reliable operations.

Managing Infrastructure

Secret Management:

HashiCorp Vault protects secretes, centralizes, and manages sensitive data like passwords and API keys, ensuring security and compliance within your infrastructure.

Cloud Resource Management:

Tools like AWS CloudFormation and Azure Resource Manager streamline cloud deployments. They automate the creation and management of cloud resources, keeping your infrastructure scalable, secure, and easy to manage. These tools collectively ensure that platform engineering can handle automation scripts, monitor applications, maintain site reliability, and manage infrastructure smoothly.

The Future is AI-Powered:

The platform engineering landscape is constantly evolving, and AI is rapidly transforming how we build and manage software delivery pipelines. The tools like Terraform, Kubecost, Jenkins X, and New Relic AI facilitate AI capabilities like:

  • Enhance security
  • Predict infrastructure requirements
  • Optimize resource security 
  • Predictive maintenance
  • Optimize monitoring process and cost

Conclusion

Platform engineering is becoming the cornerstone of modern software development. Gartner estimates that by 2026, 80% of development companies will have internal platform services and teams to improve development efficiency. This surge underscores the critical role platform engineering plays in accelerating software delivery and gaining a competitive edge.

With a strong foundation in platform engineering, organizations can achieve greater agility, scalability, and efficiency in the ever-changing software landscape. Are you ready to embark on your platform engineering journey?

Building a robust platform requires careful planning, collaboration, and a deep understanding of your team’s needs. At Mantra Labs, we can help you accelerate your software delivery. Connect with us to know more. 

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