Experimented a bit today with Krea and image generation for a case study I’m putting together around AI EarPods connected to OpenAI.
The focus has been on creating fashion-forward product imagery and art directing a world that feels specific to the identity, rather than just generating nice-looking AI images.
The trickiest part has been product consistency. Especially getting the EarPods to actually sit snug in the ear. If you’ve worked through this process, you probably know the struggle 😅
Simply telling AI to “make it fit more snug or in the ear” doesn’t always work. It loves to reinterpret the product every time.
Still experimenting, but getting closer. If anyone has found a good workflow for keeping products consistent across AI-generated shoots, I’d love to hear it!
Some quick mockups for Relay, an AI infrastructure platform concept built around model routing, observability, and performance.
Exploring what a mobile command center could look like for teams managing multiple AI models, with a focus on clear data, fast decisions, and a developer-first UX.
Product design, mobile UI, AI tools, and a little systems thinking all in one.
I built an AI-powered client enquiry automation workflow using Zapier, Google Forms, Google Sheets, AI by Zapier, Gmail, and Google Calendar.
The goal was to automate the initial handling of client enquiries from receiving the enquiry to understanding the client's needs, sending an acknowledgement, and creating a follow-up task.
The Problem:
Managing client enquiries manually can be repetitive and time-consuming. Each new enquiry needs to be reviewed, categorized, summarized, responded to, and followed up.
Without a structured process, it's easy for enquiries to be delayed or follow-ups to be missed.
The Solution:
I designed a workflow that automates these repetitive administrative tasks while using AI to analyze the information provided by the client.
The automation follows this process:
Client submits enquiry
↓
Google Sheets captures the enquiry
↓
AI analyzes the enquiry
↓
Gmail sends an acknowledgement
↓
Google Calendar creates a follow-up
How It Works:
1. Enquiry Collection.
The client submits their details and enquiry through a Google Form. The information is automatically recorded in Google Sheets.
2. AI Analysis.
AI by Zapier reviews the enquiry and extracts key information such as the service category, priority, concise summary of the client's needs, and recommended next action.
This eliminates the need to manually review every enquiry just to determine what it is about and how it should be handled.
3. Automated Client Response.
After the enquiry is processed, Gmail automatically sends the client an acknowledgement, ensuring they receive a timely response.
4. Follow-Up Management.
The workflow creates a Google Calendar follow-up, helping ensure that the enquiry doesn't get lost after the initial response.
Result:
The completed workflow turns a manual enquiry process into a structured automated system:
Capture → Analyze → Respond → Follow Up
The key improvement is the use of AI as a decision-making layer, rather than simply moving information from one application to another.
This demonstrates how AI automation can reduce repetitive administrative work, improve response consistency, and help businesses stay organized with client enquiries.
Tools Used:
Zapier | AI by Zapier | Google Forms | Google Sheets | Gmail | Google Calendar
Skills Demonstrated:
AI Automation • Workflow Design • Administrative Automation • AI Prompting • Client Enquiry Management • Email Automation • Calendar Automation • Process Optimization
Really clean workflow, Ann. The Capture → Analyze → Respond → Follow Up structure makes the business value immediately clear. One useful next layer could be an exception route for urgent or low-confidence enquiries, so AI handles the routine cases while anything uncertain...