AiListz: AI Content Creation Platform
My contribution · AiListz
AI content-creation platform
Designed the web platform’s content-generation, persona, plagiarism-checking and in-product guidance workflows.
What I owned
- Mapped first-use onboarding, brand-style setup, content generation and plagiarism-checking flows.
- Designed conversational help and in-context explanations for unfamiliar AI decisions.
- Used shared interaction patterns across the editor, personas and advanced controls.
Details
- Role: Product Designer for the web platform.
- Objective: Help content creators draft content, check for plagiarism, switch personas and use several AI tools without learning a different workflow for each one.
The validation focused on:
Make beta onboarding clearer for first-time users.
Reduce support demand through in-context guidance and clearer tool labels.
Test whether conversational guidance improved confidence without hiding user control.
User-Centric Research
I interviewed bloggers, marketers and developers about how they used AI tools and where the work became confusing.
- Onboarding: Technical language made many AI tools difficult for first-time users to understand.
- Disconnected tools: Features worked in isolation instead of supporting a complete content workflow.
- Unclear output: People could not always tell why the product made a recommendation.
The interface used guided prompts and conversation to introduce each tool while keeping settings and output controls visible.
Low-Fidelity Sketches
I mapped onboarding, brand-style setup, content generation and plagiarism checking.
The wireframes showed where people could become stuck, especially when switching between personas.
Usability Testing & Refinements
Small groups tested the product over several rounds. Their feedback led to clearer menu labels, shorter prompts and help choosing a template or persona.
Menu structure: Each tool, including image generation and speech-to-text, used the same naming and navigation pattern.
High-Fidelity Prototypes
I applied the visual system and rewrote placeholders in plain language.
A shared design system gave the plagiarism checker, persona switching and text editor the same interaction patterns.
Advanced controls sat inside collapsible sections so new users saw them only when needed.
Context & Challenge
Bloggers, marketers and developers often had to move between separate AI tools for drafting, plagiarism checks and persona changes. The product brought those jobs into one conversation-based interface while keeping the controls visible.
Primary Goals
- Guidance: Explain each tool at the point where a new user needs to make a decision.
- Shared patterns: Use the same interface structure as new tools such as image generation and speech-to-text are added.
- In-product help: Answer common questions beside the relevant setting or output.
AI Design Principles & Conversation Design
Show, Don’t Tell
Guided prompts and tooltips: Explanations appeared beside plagiarism checking, persona switching and other unfamiliar decisions.
Conversational UI
Chat interface: Users could ask for help in natural language and receive suggestions or a short feature demonstration instead of searching a long FAQ.
Transparency & User Control
- AI explanations: Short summaries showed why the product suggested content or flagged possible plagiarism.
- Personalisation: Users could set the brand voice, tone and style, then edit the generated result.
What changed in the beta
Onboarding: Guided prompts and clearer navigation made the beta easier to understand.
Testing showed that people could find the main tools with less explanation.
Support: In-product guidance answered common questions at the point of use.
The guidance and chat assistance were designed to resolve common questions before a support request was needed.
User control: Explanations and editable settings made the AI output easier to inspect and correct.
Survey responses were positive about the in-product guidance and explanations.
User Feedback: “It feels like I have a smart assistant guiding me, rather than wrestling with a confusing AI tool. I can see exactly what’s happening and why!”
Need this level of detail in your product?
Bring the hard product decision into the room early.
For a product team, that can mean a focused design, system or prototype project. For a hiring team, it is a closer look at how I work across research, interfaces and code.
