AI-Powered Solution Development Platform
Transforming how businesses build custom AI solutions through strategic design leadership
The Challenge
Businesses were forcing SaaS products to fit their needs instead of getting custom AI solutions. Our platform had all the pieces – Processes, Workflows, Apps, Forms, Data, and Document Generation – but they weren't working together to give AI the business context it needed.
Strategic Approach
1. Identifying the Market Opportunity
- Understood gap where businesses needed custom AI solutions
- Leveraged our platform's unique advantage: combining all capabilities to provide AI with rich business context
- Positioned us for competitive differentiation in AI-powered business solutions
2. Establishing Human-AI Partnership Principles
- Challenged industry assumption that "AI should do everything"
- Established principle: AI generates, humans guide
- Designed granular interaction patterns for different personas without cognitive overload
3. Leading Through Complexity
- Stakeholder Management: Guided C-suite presentations and provided real-time meeting direction
- Team Protection: Defended small, empowered teams to ensure streamlined leadership understanding and prevent scope creep
- Technical Partnership: Collaborated with engineering to ensure designs matched AI capabilities possible to deliver
- User Focus: Maintained continuous learning loop despite rapid AI technology changes
Design Process
Discovery & Alignment
- Built continuous feedback loop with internal and external users
- Balanced quick ideation for stakeholder alignment with engineering feasibility
- Created shared vision across multiple senior stakeholders
Strategy to Execution
- Elevated established senior designer to higher-visibility role, coaching them through executive presentations
- Championed designer's ideas and created space for them to focus wholly on AI exploration
- Mentored designer through executive stakeholder management, positioning them for promotion
- Set team workloads and negotiated scope with PM to shape realistic roadmaps
Key Design Decisions
- Adaptive AI interaction modes: Combined chat-style AI for open-ended exploration, inline AI for contextual assistance, and quick manual edits for finishing touches – matching users' mental models as projects evolve from ambiguous to refined
- Progressive personalization strategy: Created different entry points for technical vs. non-technical users, with plans for role-based prompts and customizable AI behavior to meet each persona where they are
- Human-in-the-loop validation: Designed preview and validation steps that mimic peer collaboration, allowing early error detection and correction to prevent hallucination cascades and maintain user confidence
Progressive interaction model aligning with user mental states throughout project lifecycle
Impact & Outcomes
AI Generates
Creates initial solutions based on business context
Humans Guide
Provide direction and validate outputs
Progressive Control
Increasing human input as project matures
Error Prevention
Early detection stops hallucination cascades
Core principles driving our AI design strategy across the platform
Business Impact
- Will shape platform product cohesion across all capabilities
- Informs AI asset generation strategy company-wide
- Fundamentally evolves how we communicate as an integrated platform
Team Development
- Elevated senior designer to executive-facing role, resulting in promotion trajectory
- Established design patterns now used across multiple teams
- Created framework for future AI feature development
- Built team capability in AI design through focused mentorship
Reflection
What I learned about leading AI design: The intersection of AI capabilities and human needs requires constant recalibration. Success came from protecting the team's focus while managing upward to keep stakeholders aligned.
What I'd do differently: Keep the team smaller and more focused from the start. Too many stakeholders got involved too early, making it hard to narrow scope and costing us valuable learning time through mid-development changes. Small, empowered teams with clear decision rights actually move faster.
Visual Design
Design completed under my coaching and direction by a Senior Designer who was promoted to Staff Designer.
AI-powered solution entry point: users describe their business problem in natural language
AI-generated personas and user stories based on business context
Progressive disclosure: showing users where they are in the AI generation process
Platform integration: connecting generated solutions to external systems for real-world implementation
Human-in-the-loop validation: reviewing AI-generated asset outlines before final generation