It’s been close to 6 months at Genloop as a Product Designer and I wanted to share my journey so far in building something from the ground up in an exciting domain. While I started with limited knowledge, I believe this field will become one of the most important differentiators for organizations.
I have touched upon these topics so feel free to jump on to the section you are most interested in:
Key projects overview I have worked on in Genloop
My process of designing and building a product from the ground up
Insights in the trends of GenAI progression in the industry
My journey towards becoming an AI Designer
Starting off with some initial context, I am a product designer at Genloop, an early-stage startup that aims to empower enterprises to adopt GenAI with zero development effort.
We had worked on multiple iterations before landing on the tagline that encompasses almost everything we aim to do :)
Some of my projects at Genloop included:
Designing the platform experience where an enterprise could create, maintain, and improve the Private LLMs, customized for their specific needs.
Building an online presence through a website.
Laying down initial components of overall brand design language like brand colors, typography, logo, and social media assets.
Working on SEO and content strategy.
Each task was bundled with a great learning experience for me and for the scope of this blog, I would love to touch briefly on the first one.
Chapter 1: Designing the Platform Experience
This is our most critical and active project at Genloop, central to our overall value proposition. Ayush, Genloop’s founder, brought a clear vision for the platform’s initial features, backed by an MVP that had already validated the functionality using real enterprise data.
My goal was to transform these ideas into a functional platform experience for enterprises. Here are the key steps I took:
Initial Discovery & PRD Creation
I began by developing a clear understanding of our why, what, and target audience. Through team discussions, I documented key learnings and insights to create our first Product Requirement Document (PRD). This foundation ensured the entire team stayed aligned throughout product development.
Competitive Research
Before diving into Figma, I researched how other companies in this space design interfaces for creating private LLMs. This helped me understand common patterns and heuristics while gaining insight into the various stages of the LLM development cycle.
My Reference board with inspirations from competitors, insights and wireframe ideas for each feature on the platform
Interface Design Process
After documenting my learnings and gathering inspiration, I began designing the interfaces. Working in a small team and building from scratch had both advantages and challenges. While it was easy to gather feedback and iterate quickly, we often had to rely on intuition rather than extensive research for flows, screens, and UI elements. I focused on balancing functionality and UI design for our initial version — creating something polished enough to bring to market and attract our first clients, while leaving room for future improvements.
Prototyping & Initial Validation
I involved iterative prototyping of flows as they were being designed, which helped me gain valuable insights about the platform. This approach allowed the team to provide feedback to me on actual working prototypes rather than just conceptual designs. I ensured the UI elements were designed using real data for all scenarios, not just for aesthetic appeal. As an added benefit, we could showcase these functional prototypes to potential clients before development was complete, gathering essential feedback from our target audience.
Design Handoff
After completing all screens and creating an end-to-end prototype, I handed over my designs to the developers for implementation. My understanding of development helped me communicate design decisions and resolve issues efficiently. During the design process, I was careful to include detailed notes about interactions and UI elements that might otherwise be unclear.
These were the essential steps that I took in designing the platform, of course, there were many things that I had to abstract out and would like to add in a proper design case study.
For the platform design part, I was majorly going as per the founder’s ideas & perspective of how a product would look and function which led me to need to have a deeper understanding of the subject and industry of GenAI so that I could contribute with my ideas and understand the requirements of enterprises in a better way.
Chapter 2: Gaining GenAI Insights
Just a short disclaimer, I am very new to the very vast field of ML & data science and my current objective is to understand how things work in the LLM world so that I can create an overall better product that aims to create personalized LLMs.
It’s pretty evident that enterprises are adopting GenAI and it will only increase in the coming time. Here is one resource that helped me to understand market trends, and get an idea of where the industry is heading. It is called State of Data + AI by Databricks.
Companies started with the most readily available LLMs including SaaS LLMs (e.g., OpenAI). However, companies are beginning to take more control over their LLMs and build tools specific to their needs.
So, this creates a need for enterprises to enable them to build their private LLMs that are tailored as per their specific needs and trained on their proprietary data.
One great insight I found was the amount of growth in the number of companies logging experiments to create their model and using registered models in the production setup. Also, this shows the increase in efficiency which means how quickly a model becomes production-ready.
Insight from the Databricks report about the experiments logged and registered
So, why as Designers should we even care about this?
Moving on the path of becoming an AI Designer
As more companies intend to create custom models, more solutions in the market would emerge that would help them achieve this, one being Genloop.
But, on a bigger level, this creates new opportunities for Enterprises and product teams to focus on how:
These LLMs and models can help to perform certain functions of their existing workflows better
Create standalone applications in a more efficient way.
This also demands building clarity among Designers and other teams to define what exactly they want models to do for them.
I really loved the article by Nick Hobbs where he gave an idea about AI Designers and how in the era of these powerful technologies of LLMs and Models we as Designers have an essential role to play.
A quote from the article which is by Steve Jobs really resonated with me:
“Most people make the mistake of thinking design is what it looks like. People think it’s this veneer — that the designers are handed this box and told, ‘Make it look good!’ That’s not what we think design is. It’s not just what it looks like and feels like. Design is how it works.”
I do see a lot of fluff including new AI applications every day but a lot of impactful work is also being done on enterprise-level applications that is optimizing the workflows and changing the dynamics of how current tasks are being done.
I do believe AI progression would affect our role as a designer but rather than being scared of it or turning back towards it, we should upskill ourselves with building curiosity around these progressions.
I look forward to sharing my journey and learnings as an “AI Designer” and would love to hear about your experiences and insights in building for this emerging era. Always up for an interesting chat ✨, feel free to drop a DM on LinkedIn or Instagram.
