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Designing AI Experiences
Tenetic
AI-Powered Sales Presentation Platform
Certain details have been omitted or abstracted in compliance with a non-disclosure agreement. All visuals are reproduced with permission from the client. The work shown reflects my individual contribution as the sole product designer on the engagement.
Project Overview
An AI platform for enterprise
sales teams to build data-ready presentations
Tenetic is an AI data intelligence platform designed to help enterprise sales representatives transform raw data into compelling, client-ready presentations, in minutes rather than hours. I was brought on as the sole product designer to take the platform from concept to launch across two structured phases.
Phase 01
Creative Discovery
Research, user analysis, and UX strategy to define what the product needed to become. Deliverables included personas, journey maps, happy path flows, information architecture, and feature prioritization.
Phase 02
Implementation
Sprint-by-sprint execution of the full Tenetic platform, from a design system and core navigation through the AI Story Builder engine, file management, and final presentation workflows.
Phase 01
Creative Discovery
Before designing a single screen, I needed to understand who this product was truly for, what was breaking in their current workflow, and what the simplest path to value looked like. Phase 01 was entirely research and strategy.
The Challenge
Designing a 0-to-1 AI product
under aggressive timelines
Enterprise sales teams at Tenetic's target clients were spending enormous amounts of time manually pulling data, assembling slides, and reformatting decks for each client, a process rife with handoffs, rework, and inconsistency.
My mandate was to design the platform from scratch: no existing design system, no prior design files, unclear user needs, and a compressed sprint cadence. Every design decision had to be grounded in real user insight.
Key Insight
Initial assumptions pointed to data access as the primary friction. Research revealed something different entirely.
"The pain point was not data access, but the effort required to structure a compelling story."
Primary Persona
Meet Ali Walton
Through stakeholder interviews and synthesized research, I defined the primary user: a senior sales representative navigating high-stakes client meetings with limited time and technical support.
Goals
- Quickly assemble impressive, tailored client presentations
- Make data feel like a story, not a spreadsheet
- Spend more time selling and less time formatting
- Impress stakeholders with polished, on-brand output
Frustrations
- Manual data pulls from multiple sources take hours
- Decks feel generic and not tailored to specific clients
- Rework cycles after every new data point or change
- No single tool to handle data + story + design together
"If you can't explain it simply, you don't understand it well enough."
Bill Gates (Ali's guiding principle)Current State Journey Map
Mapping the pain in the current workflow
I mapped Ali's end-to-end experience preparing a client presentation today, from initial data request to final delivery. Three systemic failure modes emerged across the journey.
Manual handoffs between systems. Sales reps switch between 4–6 disparate tools to gather data, build context, and format output, creating constant context-switching and data integrity risk.
Heavy rework cycles. Every client change, data update, or stakeholder revision requires starting over. There is no live feedback loop between the data source and the presentation output.
Emotional friction at scale. The manual nature of the process creates anxiety, especially before high-stakes meetings. Reps lose confidence when they can't verify whether their data is current.
Current state journey map: annotating emotional highs and lows across the presentation preparation workflow.
Ideal Happy Path
Designing the frictionless flow
Once I understood where the existing journey broke down, I mapped the ideal happy path: the simplest, most direct route from intent to a complete, client-ready presentation. Every sprint would be held accountable to this flow.
Happy Path · Ideal User Journey
Feature Prioritization
Five KPI feature areas
to define the product scope
Based on the happy path and research synthesis, I identified five key performance indicator feature areas. These became the organizing framework for all sprint planning and stakeholder alignment.
01
AI Prompt
Natural language input that initiates the presentation generation workflow.
02
Generating & Modifying Output
Live feedback loops for refining AI-generated slide content and structure.
03
File Management
Dashboard for organizing, locating, and downloading completed presentations.
04
Client Management
Lightweight CRM layer for tracking client context and presentation history.
05
Loyalty & Gamification
Engagement mechanics to drive retention and platform habit formation.
Information Architecture
Structuring the product skeleton
With personas, journeys, and feature scope defined, I built the information architecture to establish the complete navigational and functional framework for the platform. This IA became the blueprint for every sprint that followed.
Full information architecture: mapping the complete product hierarchy from navigation to feature-level flows.
Phase 02
Implementation
With the strategic foundation set, Phase 02 was execution. Four sprints, each focused on a specific layer of the platform, from foundational navigation and file systems through the core AI Story Builder engine that defines Tenetic's value proposition.
Sprint Timeline
12-week sprint roadmap: four focused sprints from foundation to full AI engine delivery.
Sprint One
Foundation · Navigation & File System
Sprint 1 established the structural backbone of the platform: the menu bar, brand system, files dashboard, and the first core user flows. With no existing design system, I built components from scratch, grounding every decision in the defined IA and user research.
Primary brand color palette
Secondary color system
Brand system established in Sprint 1: primary and secondary palettes informed all component and UI decisions across subsequent sprints.
Side navigation and typography specifications: the component foundation for all subsequent screens.
Sprint 1 · Annotated Mockup
Annotated wireframe from Sprint 1: core layout decisions documented for engineer handoff.
Sprint Two
Files & Organization System
Sprint 2 built out the complete file management experience, the system users would rely on daily to find, organize, and manage their presentations. Two view paradigms (grid and list) and folder organization were designed with progressive disclosure in mind, so power users could navigate quickly while new users weren't overwhelmed.
Sprint 2 · Annotated Screen Flows
Sprint 2 full annotation set: AI Chat interface and Storybuilder Inputs with 5 annotated interaction decisions. Grid and list view toggle, folder move flow, and contextual file actions are documented for handoff.
Sprint Three
The AI Story Builder Engine
Sprint 3 was the most complex and highest-impact sprint of the engagement, focused on the design of Tenetic's core differentiator: the AI Story Builder. Users move through a structured workflow that transforms an initial prompt into a fully generated, editable presentation. The design challenge was making this feel effortless without hiding the AI's reasoning.
Two modes were designed for the input phase: an AI Chat mode for users who prefer to describe their presentation in natural language, and a Storybuilder Inputs mode for users who want structured control over sections, tone, and data sources. Both paths converge at the same outline review and template selection flow.
Sprint 3 · Story Builder Flows
Sprint 3 complete annotation set, covering the full AI Story Builder workflow: Storybuilder Inputs (5 annotated decisions), Template Selection, Generating state, and Slide States with real-time editing capability.
Sprint Four
Outline, Slide States & Final Review
Sprint 4 completed the Story Builder loop: the Outline view and its two states (initial and edited), slide-level controls, and the final presentation review experience. The guiding principle for this sprint was human oversight: every AI-generated decision should be editable, auditable, and reversible without breaking the user's sense of flow.
Sprint 4 · Outline & Slide States
Sprint 4 annotated screens: Outline view (both initial and edited states), slide state annotations, and the complete presentation review interface.
Outcomes
What we shipped
and what it meant
Over 12 weeks, the engagement delivered a production-ready product design for Tenetic's full platform, from brand system to AI engine. Four outcomes defined the work.
Complete Design System from Zero
Built a full component library and brand system in Sprint 1 that scaled across all four sprints without rework, enabling rapid, consistent delivery under tight timelines.
Frictionless AI Input Paradigm
Designed two complementary AI input modes, conversational chat and structured Storybuilder Inputs, so users could choose the level of control that matched their workflow.
End-to-End Story Builder Workflow
Delivered the full generation loop: prompt → outline → template → presentation → export. Every step was annotated and handed off to engineering with full interaction documentation.
Human Oversight at Every Step
Every AI-generated decision, including section titles, data selections, and slide structure, was designed to be editable and reversible, ensuring users remained in control without breaking flow.
"The Story Builder workflow reduced what used to take a full afternoon into a single, guided session, with the AI doing the heavy lifting while the sales rep stays in the driver's seat."Design Rationale, Tenetic Sprint 3 Review
This engagement reinforced a core principle of designing for AI: the goal is not to replace human judgment, but to eliminate the mechanical labor that gets in its way. Tenetic gave sales teams back their time, and with it, the space to focus on the work that actually moves deals forward.