How I use ChatGPT to speed up Fashion Product Development

Last month, I was stuck. I needed fresh, innovative ideas for an upcoming collection, but my mood boards felt repetitive, and my usual creative process wasn't sparking anything new. Then, I came across a thought-provoking LinkedIn post by Arik Shimansky titled Product Development with ChatGPT that completely shifted my perspective.

In his article, Arik cuts through the AI hype with a refreshingly practical approach. He described ChatGPT not as a magic oracle, but as a powerful business tool - one that could systematically accelerate product development when used with clear processes. What struck me most was his two-step method:

• Breaking down business objectives into concrete steps
• Converting these steps into targeted ChatGPT prompts

His real-world example of developing a product from scratch - complete with market research, opportunity assessment, and go-to-market strategy - made me wonder: Could this same structured approach work for fashion product development?

I decided to test Arik's methodology in my own workflow - and the results were transformative. What began as an experiment evolved into a game-changing approach that now touches every stage of my design process. ChatGPT has become more than a chatbot; it's like having an on-demand creative director, trend forecaster, and production assistant all in one.

Here's exactly how I applied Arik's framework to fashion development - and how you can too.

Trend forecasting

I was racing against a deadline for our new collection, but traditional trend forecasting methods were slowing me down. Waiting for WGSN reports? Expensive. Scrolling through endless trade show photos? Time-consuming. As an independent designer, I didn’t have the budget for premium trend services.

How ChatGPT Helped?

I asked:

Analyze emerging color trends for Spring/Summer 2025

The Results:

• ChatGPT identified that nature-inspired colors like leafy greens and sky blues are popular for their calming feel. Warm earth tones like terracotta are being used too. For those who want bold looks, bright reds and oranges stand out, along with eye-catching pinks and teals. Soft pastel colors got an update - think baby blue but fresher. Classic neutrals like gray and navy remain wardrobe staples. Some designers are bringing back 60s-inspired shades like lavender for a retro touch. Pantone noted these colors work well across seasons, making them extra useful for designers.

• It also gave me a pantone page source along with other sources.

Pro Tip: Refine prompts for better results:

Suggest 3 ways to incorporate these colors into a capsule collection.

The tool then asked me if I wanted help with creating a mockup or visual guide. So, I tested it out and here is the result!

While not perfect, these results give me solid starting points with credible sources - saving hours of manual research. It's like having a research assistant who quickly pulls together key trends and references from Pantone, Vogue, and industry reports. See my raw ChatGPT thread here.

For anyone looking to streamline their trend forecasting, here are 3 useful prompts to try with any AI tool:

Give me the top 5 emerging color trends for [season/year], along with their Pantone codes and which fashion brands are using them.

Show me a comparison of streetwear vs. luxury trends for [upcoming season] with specific fabric and silhouette examples.

Create a mood board description for [target audience, e.g. Gen Z professionals] including colors, materials, and key influences for next season.

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Sketching & design

ChatGPT had just handed me Spring/Summer 2025’s key color trends: earthy greens, juicy tangerine, and dreamy pastel tones. Gorgeous—but now came the real challenge.

How was I supposed to make these feel fresh and still sellable? How do you design a capsule that speaks to both minimalists who live in black and white—and the maximalists who want to wear the rainbow?

With just a few days left before my client pitch, I needed designs that looked polished and production-ready. Fast. There was no time to spend hours sketching endless silhouettes from scratch. I needed a smarter, faster way to bring this vision to life.

How ChatGPT Helped?

Before diving into silhouettes, I had to get the colors to work together. If the palette isn’t balanced, the whole collection can feel off—too loud, too soft, or just not cohesive enough to hold together. I knew I needed a mix that felt intentional: enough versatility for different customer tastes, but still tight enough to tell one clear story. So, I started with the following step.

Step 1: Building the color architecture

I asked ChatGPT:

Create a balanced color ratio for a 12-piece capsule for my design collection using:
- 60s sorbet pastels (lavender, cornflower blue)
- Earthy mid-tones (terracotta, ochre)
-1–2 vibrant pops (hot pink, tangerine)

The Results:

ChatGPT suggested a 12-piece capsule collection with a balanced mix of retro pastels, earthy tones, and bold accents.

It also suggested tips for color mixing:

Step 2: From palette to product

Now, I wasn’t looking to start from scratch—honestly, who has the time? Sketching every look by hand would’ve taken me forever, and I was on a tight deadline. I needed to move fast, without compromising on originality or style.

So, I asked ChatGPT:

I’d like to visualize these designs quickly without creating everything from scratch. Is there a tool where I can drag and drop garment elements, apply these color combinations, and build out design concepts efficiently for tech pack development?

The results:

ChatGPT recommended tools to quickly visualize garments, apply color palettes, and build tech packs.

It even suggested me a workflow:

But here’s the reality check: While CLO 3D is industry-standard for 3D, it has a steep learning curve. Techpacker is great for specs but lacks design features. RepSketch? It surprised me.

Step 3: Inside My RepSketch Workflow

First Impressions:

I landed on RepSketch’s homepage and immediately noticed:

• Pre-made vector sketch library: 500+ editable vector flats (clothing, bags, footwear and accessories)

• Community sketches: fully editable real designers’ sketches which you can "re-purpose".

• Mood Board (hidden gem!): fully editable, pre-curated by trend

From blank page to design in 15 minutes, here are the steps I followed:

1. Selected a base template.
2. Color Application: Used hex codes from ChatGPT’s palette
3. Mixed & Matched: Swapped in components from the component’s library

I found this really intuitive video of how Repsketch gives an option to turn 2D sketches to 3D photorealistic images.

So, I tested it out and here's the result I got:

But at the same time I wanted to test it on another app, so I asked ChatGPT and it suggested me to use DALL·E (via ChatGPT), and here's the result:

Between DALL·E and RepSketch, I’m still figuring out which one works best for me. DALL·E definitely gives you more realistic-looking images right out of the box, while RepSketch feels a bit more basic when it comes to 3D visuals. That said, RepSketch offers something super useful that DALL·E doesn’t, especially if you need to make changes later on.

Here’s a quick breakdown of how they compare:

• DALL·E gives better visual quality: The images look more realistic and polished, which is great if you just need a strong visual reference or moodboard-style output.
• RepSketch’s 3D feature is still developing: It shows the garment structure and details accurately, but the final image isn’t quite as lifelike. It’s still early-stage tech, and I’m hoping it improves over time.
• RepSketch is great for customization: Unlike DALL·E, RepSketch gives you editable vector files. That means you can go in and tweak every detail—silhouettes, trims, stitching—you name it. This is super helpful if you’re working on tech packs or need to keep updating your designs.
• More practical for real workflows: If you care less about perfect visuals and more about having a working file you can reuse, RepSketch fits better into a design workflow.

My take? Try both. Use DALL·E when you need visuals that impress, and RepSketch when you need files that actually work.

Sourcing

ChatGPT just helped me finalize an amazing collection that I want to make as sustainable as possible by sourcing organic cotton. But now came the real nightmare:

• My usual Turkish supplier suddenly doubled their prices
• The client demanded OEKO-TEX certification (which my backup vendor didn’t have)
• With the deadline fast approaching, I found myself staring at:
  - $3,000 for a rushed WGSN sourcing report
  - Endless Alibaba scams from my last desperate search

How ChatGPT Helped?

As an independent designer, I needed affordable, ethical suppliers FAST – without flying to Istanbul.

Step 1: The supplier hunt

I asked ChatGPT:

Find 5 organic cotton suppliers in Turkey with:
- OEKO-TEX and GOTS certifications
- MOQ under 500 meters
- Carbon-neutral shipping options
Include direct contact emails and sample policies.

The results:

ChatGPT shortlisted five GOTS-certified Turkish suppliers for organic cotton, each with potential for low-MOQ orders.

• Parko Textile – GOTS & OEKO-TEX. MOQ: 2,500m (flexible on request). Ideal for bulk woven orders.
• Effa Textile – GOTS & OEKO-TEX. MOQ not listed; may suit smaller brands.
• Calico – GOTS. Focuses on babywear; likely open to small orders.
• Simurg Tekstil – GOTS. Babywear supplier with possible low MOQs.
• Beşler Tekstil – GOTS & OEKO-TEX. Yarn supplier; MOQ likely flexible.

Carbon-neutral shipping and sample policies not specified—contact directly for details.

I then asked it to create a comparison table for all 5 suppliers for me to help me decide better, and here are the results:

And suggested, "If MOQ is a critical factor, Parko Textile seems the most transparent, with the option to request flexibility."

I wanted to authenticate my suppliers before reaching out to them.

So, I asked ChatGPT:

Can you provide a toolkit or list of tools, platforms, and methods I can use to authenticate suppliers—especially those claiming GOTS, OEKO-TEX, or other sustainability certifications? I’m looking for a practical checklist that includes websites, databases, red flags to watch for, and steps to verify credentials, legal registration, and online presence.

The result:

Here's the summary of the results along with red flags to watch for:

I asked for a downloadable checklist template, and ChatGPT provided a DOCX version of the Supplier Authentication Toolkit, with an option to request it in PDF or Excel format as well.

Step 2: The negotiation battle

To negotiate confidently with the supplier, I first needed to understand the current market rate.

So, I asked ChatGPT:

I’m planning to negotiate with suppliers for organic cotton fabric. Can you provide the current average market rates (per meter or per kg) for organic cotton (finished fabric) in Turkey? Include any recent pricing trends, quality variations (e.g., GOTS-certified, combed, or woven), and factors that typically affect pricing.

The result:

Here's the summary of the result including the current market rates along with negotiating recommendations:

I then went to drafting my email to the supplier.

So, I asked ChatGPT:

Draft a short email to negotiate fabric prices. Tone: Friendly but firm. Key points:
- Reference my 3-year design brand growth
- Mention competing quote of $3.80/m
- Request $3.65/m with prepayment offer

The result:

The Supplier Countered: $3.90/m with 30% prepayment

My chatGPT fact-check:

Is 30% prepayment standard for Turkey?

The result:

Here's the summary of the result including the answer along with recommendation:

Checkout the below 3 email templates that get replies:

• The bluff (when they ignore you):

“Subject: Urgent – Order Going to [Competitor] Tomorrow”
“Hi [Name], I’m ready to place 400m order but need confirmation by 5 PM CET. Attached: Tech pack with your fabric specs.”

• The audit demand:

“Please share your most recent social compliance audit (SGS/BV/Intertek) for our records.”

• The sample follow-up:

“Following up on sample #456 – our team noticed inconsistent stitching (photo attached). Can you confirm this won’t happen in production?”

Manufacturing

With my SS25 color palette finalized and RepSketch designs approved, reality hit:

• No factory locked in (most required tech packs before quoting)
• Client deadline: Just a few days to submit production-ready samples
• Budget panic: My usual factory increased their rates

How ChatGPT Helped?

Step 1: Finding factories FAST

Traditional methods failed me:
Alibaba: "Organic cotton specialists" kept shipping polyester blends
Trade shows: Too slow (next one in 3 months)
Referrals: My network’s factories were booked solid

I ask ChatGPT:

Find 5 ethical factories in China specializing in womenswear with:
- MOQ <200 units
- OEKO-TEX certified
Format as a table with contact emails.

The results:

I also ask ChatGPT:

How can I quickly verify these? Can you suggest some tools/apps/websites? Also, it'd be great if you can provide a checklist.

The result:

Here are the results including a verification checklist and tools/websites to use:

Step 2: Tech Pack Chaos

My "organized" system was anything but:
Designs: Buried in 3 different Google Drives
Comments: Spread across various emails
Artwork: Trapped in outdated Illustrator files
Version Control: "Final_v3_updated_REALLYFINAL.ai"

When my factory requested digital tech packs, I nearly cried.

So, I aksed ChatGPT:

I’m a fashion designer and my product development workflow is a mess. My designs are scattered across multiple Google Drives, feedback is buried in email threads, and my artwork is stuck in outdated Illustrator files. Version control is a nightmare — I'm dealing with files like "Final_v3_updated_REALLYFINAL.ai". Now my factory is asking for digital tech packs, and I feel totally overwhelmed. Is there a tool that can help me centralize everything, manage versions properly, and create professional tech packs easily?

And the result:

Then ChatGPT gives a full rundown of how Techpacker could help.

I also asked ChatGPT:

And I was seriously impressed. Check out the raw ChatGPT convo here. I used this to streamline and speed up my tech pack creation on Techpacker.

Step 3: Inside my Techpacker workflow

I landed on Techpacker's landing page, click on "Try for Free" and sign-up.

Instead of starting from scratch, I'll edit one of the free templates.

Copy it to a new folder and start editing. I'll start with replacing the sketches.

Similarly, update all other details like - material and measurements.

I can also, add comments for my team members here:

Once, my techpack is ready, I can translate it to Chinese for my manufacturers. So, no more “lost in translation”.

And share it across from Techpacker itself:

What started as a factory nightmare turned into a streamlined process—AI-powered sourcing, centralized tech packs, and real-time collaboration made sure my samples arrived right the first time. Now, with production running smoothly, it’s time for the next challenge: making sure these designs actually sell.

Marketing

We had a beautiful collection—biodegradable fabrics, perfect fits, ethical production—but our marketing felt generic. My junior copywriter kept recycling the same buzzwords ("sustainable," "eco-friendly," "conscious"), and our engagement was flatlining. I needed content that actually connected with our audience—without hiring an expensive agency.

How ChatGPT Helped?

Step 1: Breaking the "Sustainability Cliché"

The prompt that changed everything, I asked:

Write an Instagram caption for our sustainable womenswear collection. Tone: Like a cool older sister giving advice, not a lecture. Avoid words like ‘sustainable’ and ‘eco-friendly.’

And the results:

Why It Worked:

• Relatable, not preachy
• Playful tone matched our brand’s personality
• No jargon → felt like a friend texting you

Step 2: Fixing Our "Forgettable" Product Descriptions

I asked ChatGPT:

I'm rewriting some boring fashion product descriptions to make them more engaging, memorable, and brand-worthy. Here's an example of the old version and an improved version:
Old Description: "This jacket is made from recycled materials, perfect for eco-conscious consumers."
AI Upgrade: “Meet your new adventure partner: a jacket that hugs you back. Made from 12 upcycled plastic bottles (yes, really), because saving the planet shouldn’t mean sacrificing style.”
Can you give me 3–5 more AI-style upgraded descriptions for fashion products made from sustainable materials? Make them punchy, creative, and emotionally engaging.

The result:

Key shift:

• Storytelling over specs
• Unexpected details (12 bottles = memorable)
• Emotional hook ("hugs you back" and "self care")

Step 3: Turning Customers into Creators

Our UGC (user-generated content) was sparse—just a few bland mirror selfies.

I asked ChatGPT:

Give me 5 creative ways customers can style our convertible pants for TikTok.

Here we have 3 of the answers:

Lesson: AI didn’t replace creativity—it unlocked it.

LLMs comparison

I’ve explored a few different AI tools to help speed up my fashion product development workflow — from creating tech packs to writing supplier emails and organizing cost sheets. While ChatGPT is my main tool, others like Claude, Gemini, and DeepSeek each have their own strengths depending on the task.

Some are great at writing, others are better with long documents, visuals, or spreadsheet data. Here's a quick comparison of the most useful LLMs I’ve tried, tailored specifically for fashion use cases:

Conclusion

When I first tried ChatGPT for product development, I was skeptical. Could a chatbot really help me design collections, negotiate with factories, and write better marketing copy? Turns out—yes, but only if you use it right.

Here’s what I learned:

1. AI Won’t Replace You—It Will Speed You Up

• Trend forecasting went from weeks of research to hours.
• Design roadblocks got solved with fresh perspectives (even if 30% of AI ideas were unusable).
• Manufacturing chaos became manageable with real-time translations and error-proof tech packs.

2. The Best Results Come From AI + Human Collaboration

• ChatGPT gave me 5 caption ideas → I picked the one that felt most like our brand.
• AI suggested suppliers → I verified them with old-school LinkedIn stalking.
• Tools like RepSketch and Techpacker turned AI concepts into production-ready files.

3. Start Small, Then Scale

You don’t need to overhaul your entire process overnight. Try just one thing:

• Replace your next product description with an AI draft (then tweak it).
• Use one prompt to brainstorm design details (“How would Phoebe Philo style this sleeve?”).
• Let AI handle one tedious task (like translating tech packs).

AI isn’t magic—it’s a power tool. And just like a sewing machine, you’ll get better results once you learn its quirks.

Try this today:
“ChatGPT, help me solve [your biggest headache] in my design process.” Then adapt its answer to fit your brand.

A year ago, I was drowning in spreadsheets and missed deadlines. Now? I’ve cut my development time in half—and actually enjoy the creative process again. If I can do it, you can too.

Now go make something awesome!

"AI won’t steal your job—but designers who use it might steal your clients."