KeepSimple.ai Knowledge Base / 2024
Product Design, End-to-end Design
KeepSimple.ai is an AI agent development platform, enabling its users to leverage LLMOps to build and deploy customised applications with low-code tools. The platform introduces Knowledge Base as one of its core features, which allows users to connect both external and internal data sources to enhance their AI solutions.
As the Melbourne-based startup prepared for its upcoming MVP launch in a few months, the existing Knowledge Base experience could no longer meet the evolving use cases and growing expectations for the demo.
In response, working closely with a product owner and a dev team, I led the comprehensive redesign of crucial features and user flows, including file adding, group actions, and filters, delivering a scalable solution that facilitated improved value proposition and user engagement for a successful launch.
The Context
problem space
A legacy design lagging behind, and more complexities to find.
KeepSimple.ai was gearing up for its MVP launch in a few months. While the backend of the Knowledge Base was in place, its design had been left behind. The interface remained primitive and outdated — a patchwork of functions and elements that felt disconnected. It wasn't built to last.
As a product design intern at KeepSimple, I was asked to lead a swift design update to modernise the existing Knowledge Base experience. Yet, this wasn't a simple refresh; it came with a pile-up of constraints and challenges:
A blurry brief at the outset. No one really had a clear vision of what a "modernised" design should look like. Go figure.
Everything was running against the clock. The project must be delivered within weeks and ready for handover ASAP.
Limited research and testing. As an early-stage startup, we had minimal access to user feedback or behaviour data, making it extra challenging to inform and validate design decisions.
Make it scalable. The updated Knowledge Base needed to be intuitive enough for early users while also flexible enough to evolve with future growth. Striking this balance for MVP requires careful prioritisation of features.
The only "design guy". Working alongside a tech-savvy team, yet I was the sole designer in the mix. I had to drive the design process on my own.
Design for business impact.
This wasn't just another routine dashboard update you see every day — it was a strategic overhaul with some far-reaching business goals:
Enhance Value Proposition
A successful MVP launch wasn’t just about shipping a product; it was about proving KeepSimple.ai’s value. By modernising the Knowledge Base, we aimed to support a strong debut and fuel appetite among investors and early adopters with enhanced functionality and quality.
Boost User Engagement
Users shouldn’t have to wrestle with a complicated interface just to manage their knowledge. The redesign transformed a fragmented, outdated system into a seamless, intuitive experience—one that made interacting with AI-driven data feel effortless.
Drive Future Growth
This wasn’t just about fixing what was broken. The new design laid the groundwork for the future, ensuring the Knowledge Base could scale with AI advancements, evolving needs, and the company’s growing ambitions.
Leveraging what we have and what's out there.
Feedback loops were immediate around here in the startup.
A team of technical folks with a deep understanding of AI products and know-hows.
Drawing insights from the industry best practices and leading open-sourced AI agent platforms.
Design Process
Designing at a startup has been a delight, with its own unique rhythm in problem-solving. Through many struggles and lessons along the way, I was able to grasp the nuances and embrace an unorthodox design approach in this project: think and act, then retrospect.
Step o1: Be brave to think.
Understand the problem
With an unfinished legacy interface and a blurry vision, where do you even start going about redesigning a feature from the ground up? I had no clue either, so I did a lot of research at first, trying to understand how others were tackling the design on similar features.
Standing on the shoulders of giants was helpful. It made me realised that it was more of filling in the gap rather than inventing from scratch. The Knowledge Base was not a new concept in the world of AI products. The key was to build upon what already existed in the industry and pivot where necessary.
Understand the users
The Knowledge Base is for both tech-savvy experts and non-technical AI enthusiasts. It's a space that lets both user groups easily add, view and manage their "pieces of knowledge" as the building blocks of their AI agent development process.
The challenge was to shape the space to feel intuitive for everyone—something that just clicks and flows naturally and effortlessly. Meanwhile, it needed a touch of depth, offering geeks to explore and customise.
What it led to design
By walking through some of the most powerful AI agent platforms on the market, it has shed a light on the design direction, clearing the fog for a "modernised" Knowledge Base:
clarity
Clean and flat interface designs that deliver clear and concise information.
Flexibility
Allows for customisations and advanced control, so users can manage their knowledge more freely.
Efficiency
Informative and straight-forward workflows that streamline the experience.
Step 02: Be fast and decisive to act.
Pressing the fast-forward button
Rapid prototyping & iterations. Instead of full-fledged user testing, I relied on quick prototyping and multi-version iterations, allowing me to gather internal feedback at each stage to refine designs progressively, making targeted updates step by step.
Once the design direction was made clear with the product owner and the team, everything started to move quickly. It's like pressing the fast-forward button: go and get it done. Working in a crowd of startup minds can really fuel you to put nose to the grindstone and keep things moving.
I started off with wireframes to map the skeleton for a new Knowledge Base, and in the next second, before I knew it, feedback from the product owner was already rolling in. With communications, I turned wireframes into prototypes, prototypes then turned into refined flows, and each iteration brought the redesigned feature closer to life. The pace was intense, but the momentum was a beauty.
Align on scope, with the team
There are countless moving pieces in a startup and sometimes you have to battle for resources. My trick? Feedback loops were immediate around here, and I made sure to leverage them to the fullest. I spearheaded meetings to regularly sync my designs with the product owner and the team, ensuring we were all aligned on the scope and direction.
I jumped between iterations and standups, shaping pixels to meet the functional specs. In the meantime, I kept updating with these go-getters and grounded my designs in what the business needed, what the development could handle.
Step 03: Be conscious to retrospect.
Rounds of rapid prototyping have made the Knowledge Base experience more refreshing and functional than ever.
But a voice within reminded me that the sprint wasn't endless. I took a step back to review my designs, and that's when the pace started to slow down, giving me the space to identify any blind spots.
Is the journey intuitive enough? Have I provided users with clear cues for interactions? Are the users empowered with flexibility of controls? Is the design scalable? Have I covered all potential use cases? Is there any more features we can add to the current designs?
It's a race against time, and a marathon for quality.
Final Design
Takeaways
Be ready to fail.
I have learned so much by actually doing this process, and grow so much as a designer and a thinker without realising it. Don't be afraid about having failures, instead dive headfirst into them and use it to learn.
Design system matters.
I will write a note and make sure I start with building a design system, if I could do the project again. A design system is a common language for everyone in your team. It provides framework for consistency while also allows enough flexibility to address task-specific design challenges. Having a unified framework from the outset would streamline the design process so much more, and help scale the product more efficiently as it evolves.