And every year we came to the same conclusion. Designs look more realistic, adoption gets better but bottom line the business impact is disappointing. We don’t see shorter calendars, less inventory or significantly better margins.

This simple rule applies every time: New tools x Old process = same old outcomes. Tech alone is not going to change fashion.

That’s when I came across the work of Polish artist Edward Krasiński, who spent decades connecting shapes, spaces and objects with a single roll of blue tape. Six centimetres wide, always at the same height. By connecting things that didn’t belong together, he created something entirely new. It wasn’t about the tape. It was about the connection. That felt right. I called the project Edward.

I decided to stop chasing better tools. Instead I started asking a different question. Not how do we digitise what we have been doing. But with all of the tech and skills we have today, what if we could redesign the way fashion is made. From scratch. What would it look like? What if we stop being obsessed with new tech and shift the focus to how we could reshape the process.

Not slow and gentle, but redesign from the ground up for a new generation of fashion.

I interviewed a new generation of professionals in our industry. Designers, manufacturers, merchandisers. People with a career in fashion and apparel. The outcome of that research was not that they needed more tech. They betted on systemic change. They saw the biggest hurdles being our legacy processes and habits as the main slowdown of change.

Instead of designing what we think we can sell twelve months out, estimating volumes, committing to production, then doing whatever it takes to shift inventory, what if we flipped it?

Design - Sell - Make

Use technology to unlock creativity, stay closely connected to the market and manufacturing, and start selling ideas before you commit to the volumes that turn into waste and liability.

It is now 5 years later. Shein showed you can produce closer to market in smaller batches. With the right use of AI we can generate any type of product and make it look commercial before it is even made. The tools to change the sequence exist.

At EnhanceThat we’re convinced this is the next step for fashion. New tech × new process = business model change. We’re building it.

In the coming weeks we’ll share here the steps we’re taking, from design to manufacturing, and how we’re making digital-first selling a reality with Stieglitz.

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Making it scale across a team, a company, or a season that’s where the hard work begins.

The question is how do you make it follow brand consistency without burying your team in an endless maze of prompts. How do you turn AI from a tool into a workflow.

And honestly, this is nothing new. We’ve been here before with 3D, and before that with setting up the Adobe suite. We all want to believe we can skip the structure and go wild. And to some extent you can. AI turns every detailed instruction, design direction, or reference image into something beautiful.

The question is how do you make it follow brand consistency without burying your team in an endless maze of prompts. How do you turn AI from a tool into a workflow.

Manual prompting alone breaks

Prompting feels productive because the first results are surprising.

The trap is that it doesn’t scale. As soon as ideas become product it need refinement and control. Doing that with manual prompting can take hours and makes you want to pull your hair out.

Multiply that across a season and you don’t have a workflow and you have a very expensive digital photoshoot with an unpredictable timeline and unpredictable outcomes.

After running multiple rounds of ecom AI delivery for brands, we kept hitting the same wall. Not every brand had good structured input. No fit library, no material library, no label references. And the design input - usually an Illustrator file - made things worse. Those outlines were never set up as AI input. They’re artist impressions with drawn-on shadows and decorative details that confuse the model and distort the whole process.

What we realised is that AI needs structured data to work consistently. We started to call it Brand DNA. A mix of design library, dev library and brand guidelines, structured for AI use.

A Brand DNA layer fixes this by removing the part of the process that currently lives inside someone’s head. The brand becomes structured input, not a prompt users have to remember.

How we set up the Brand DNA

The funny thing, in most cases the Brand DNA already exists. It’s just not structured yet.

Almost every fashion brand is sitting on the main input layer they need. Their ecom images. Thousands of frames, shot to a tight standard, season after season. The lighting, the framing, the labels, the finishing, the fit. The small consistencies that make a product read, instantly, as yours.

Instead of treating it as output, we use it as input to build the Brand DNA structure.

We’re currently building this for one brand, Stieglitz. It’s early work, but what we’re learning is already changing how we think about AI input. We look at their existing imagery, identify the repeatable patterns - the ones a human eye recognises without thinking. The ones a model needs spelled out and wire them in as the input layer for their AI workflow. We’re now turning this process into a repeatable workflow so we can bring it to every brand we work with.

Consistent Brand DNA input gives us the data to generate consistent output. It’s not perfect yet, but with every model improvement, including the latest OpenAI image generation, the dataset becomes more valuable.

The point is not to make AI generate one good image. The point is to make it generate the hundredth one without anyone starting from zero.

That’s the difference between a tool and a workflow. A tool gives you an output. A workflow gives you consistency.

Build the structured input layer first. Then plug in whatever AI tool you like, we have no stake in any of them. We work with what you’ve got.