enterprise workflows with intelligent agents
AI Agents + Human Collaboration = Enterprise Acceleration
In a time-boxed solo challenge, I was tasked to conceptualize and prototype a B2B SaaS platform where AI agents and users collaborate to build products, from idea to delivery.
With no luxury of extended research or testing, I had to move fast, think clearly, and prioritize what matters most: transparency, adaptability, and user control.
My Role
Research, Strategy
Ideation, Visual Design
Timeline
One Day
Team
Solo Product Designer
Tools
Figma, Miro, AI LLMs
Strategic Goals: Clarity over Complexity
I have set clear, outcome-driven goals that align tightly with user and business needs:
With only 1 day to deliver, the key challenge included:
The task was to design a platform where users collaborate with intelligent agents to transform ideas into full-fledged product prototypes.
The Challenge: Designing Speed, Adaptability, and Collaboration
Studied enterprise workflow platforms for patterns in decision-making flows.
Referenced conversational UX models to humanize agent interactions.
Prioritized transparency and control to increase user trust.
Given the B2B SaaS context, I conducted focused secondary research:
Key Findings:
Research Insights: Enterprise Expectations & Agent UX
This map ensured I designed not just functional touchpoints, but a seamless experience from start to finish.
Starting from idea submission, users are guided by agents to clarify project goals.
During the requirements stage, they receive prompts to specify technical needs.
The BRD and prototype generation stages provide immediate, actionable outputs.
At every step, users can provide real-time feedback, ensuring iterative improvements.
The journey concludes with the Delivery Agent, finalizing and handing off the completed prototype.
To understand user experience holistically, I mapped out the end-to-end journey of a typical enterprise user interacting with the platform:
User Journey Overview
This modularity ensures scalability and responsiveness for enterprise teams.
Idea Agent: Guides scope definition.
Requirements Agent: Collects and compiles technical needs.
Specs Generation Agent: Generates business requirements documentation (BRD).
Prototyping Agent: Produces interactive prototypes.
Feedback Agent: Incorporates user revisions in real time.
Delivery Agent: Finalizes and delivers the completed prototype.
The platform design features modular agents that activate at relevant stages and handles specific tasks and provide real-time feedback and outputs.
Workflow Design
Dashboard Overview
Conversational Agent UI
Requirements Compilation
Prototype Iteration
Final Delivery
Select a feature
to unveil the prototype
The final prototype offers an intuitive, end-to-end experience:
Conversational Chat UI: Human-like interactions with AI agents.
Real-Time Feedback: Users can iterate and refine outputs instantly.
Progress Tracker: Visual stages of project flow for transparency.
Prototype Previews: Immediate visual validation before delivery.
Automated Handoff: Streamlined final delivery and confirmation.
Final Design:
Impact: UX & Business
Key Learnings
Working solo under a tight 1-day timeline sharpened my focus on core priorities:
This assignment reinforced that enterprise UX thrives on transparent systems, where users feel in control, even when automation is at the heart of the experience.
Modularity over complexity
Clarity over feature bloat
User empowerment over automation dependency
If this were a longer engagement or production-level task, I would:
The goal is to transform this output into an enterprise-wide solution that continuously evolves with user needs.
Next Steps
What I Learned from This 24-Hour Design Sprint
Reflections
In just 24 hours, I conceptualized and designed a collaborative SaaS platform powered by AI agents, transforming product development into an agile, guided workflow.
This wasn’t just about automation. It was about giving enterprise teams clarity, control, and confidence, even in the age of intelligent agents.
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© Karthik Anupindi 2025