To stay aligned with evolving user needs and ensure the product’s effectiveness, I adopted Teresa Torres’ Continuous Discovery Habits throughout the project. This approach involved ongoing interviews, frequent snapshots of user feedback, and iterative adjustments. By continuously validating our decisions with stakeholders, we ensured that each phase of the design and development aligned closely with user requirements and business goals, fostering a responsive and user-centered process even under tight timelines.

To fast-track the development, I organized a design sprint with cross-functional teams, including the Product Trio, AI engineers, programmers, and chatbot specialists. Our process included:
▪ Expert Interviews and Mapping: Understanding core motivations
▪ Goal Setting and Risk Assessment
▪ Brainstorming (‘How Might We’): Generating creative solutions
▪ Prioritization Voting: Selecting critical features and naming conventions:
- Content Intelligence: New AI feature name
- Classification Intelligence: Original model reference
- Knowledge Base: Domain-specific content storage

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With our core decisions established, I developed wireframes to map out the product’s flow and functionality. These initial layouts were shared with stakeholders to validate user paths and gather early feedback. Based on their input, I refined the structure, particularly by creating a clearer separation between Knowledge Base creation and query management. This improved navigation and usability for our diverse user base.

Leveraging Weni’s design system, Unnic, I crafted high-fidelity prototypes to ensure visual consistency and gather targeted feedback. The prototypes allowed for quick iteration and helped stakeholders experience the design’s look and feel. These prototypes served as a crucial tool in aligning our vision with user expectations and prepared the team for usability testing.

Through three rounds of usability testing (3 sessions with 3 users each), we validated the product’s accessibility and ease of use. Employing Sauro and Lewis’s Quantifying the User Experience methodology, I prioritized issues based on:

▪ Frequency = occurrences / number of participants

▪ Criticality to business objectives (from 1 to 4)

▪ Impact to task completion (from 1 to 5)

▪ Severity = Criticality + Impact + Frequency

The Product Trio then reviewed and acted upon these prioritized issues to streamline the user experience further.

During development, our team encountered a temporary staffing shortage. To keep the project on schedule, I proposed a no-code approach, which enabled us to maintain core functionality while working within reduced resources. Though the solution had limitations, it met the essential needs of our clients, allowing us to deliver the product on time.

▪ Quantitative Analysis of user engagement and behavior patterns

▪ UI Enhancements to optimize mobile compatibility

▪ A/B Testing to refine features, particularly in the Knowledge Base interface

This project exemplified the power of adaptable, user-centered design in high-stakes scenarios, reinforcing Weni’s leadership in AI chatbot solutions. Despite the constraints, the launch was timely, impactful, and provided immediate value, setting a new standard for Weni’s product offerings.