I’ve been continuing my journey with leftover yarn – something close to many knitters’ hearts. If you saw my recent newsletter, you’ll know I shared my free Striata Cowl pattern (you can still find it here), designed to use up those odd little scraps we all keep tucked away. Leftover yarn projects aren’t just practical – they’re creative, sustainable, and often spark ideas we’d never have thought of with full skeins.

• A garment we already loved and wore often.

• Some yarn from our stash to play with.

The day began with swatching – not just for tension (I measured half a tension square 5cm x 5cm and then doubled) but also to explore whether we liked the fabric our oddments produced. Lisa encouraged us to try different techniques such as stripes, Fair Isle, intarsia, and slip stitch. My first experiment was striped slip stitch knitting, which I turned vertically to imagine slimming stripes on my A-line top. Clever in theory, but when I tried to add shaping with German short rows, the abrupt stops in the striping didn’t sit right with me. Time to rethink!

Luckily, Lisa had brought along some sample garments, and I fell in love with one: a very simple design , The Fowberry, with no complicated shaping (just at the shoulders), no extra bottom or front bands, and the option to add sleeves later if I wished. It was a revelation – something achievable without too much maths (a relief in a busy workshop environment!).
As an added bonus, I picked up plenty of insights listening to Lisa guide other designers – and was reassured that the way I calculate my own designs is indeed on the right track.

Behind the scenes: my schematic + sums

Here’s a little glimpse of the sort of rough notes I made during the day. It doesn’t look fancy – just sketches with measurements, and stitch counts. But this is the backbone of turning an idea into something wearable.

• Garment shape: straight body with slight shoulder shaping.

• Gauge from swatch: [24 sts x 32 rows = 10 cm].

• Back length: [38cm] ÷ gauge = number of stitches to cast on.

• Body width: [59cm] ÷ row gauge = rows needed across the back

• Shoulder shaping - calculation concludes need to increase every 3 or 4 rows to middle then decrease down in the same way.

It’s all very rough at this stage, but enough to get the knitting underway!

I’m now nearly halfway across the back piece, and have already encountered a small issue that I’ll need to solve once I reach the end. I’ll share more about that (and whether I succeed!) in my next newsletter, so you can follow along with the whole process.

Did you know that AI can take a photo of a garment laid out flat and magically show it on a virtual model? When I found this out, I thought yeh, that would be great for ebay users who are just trying to sell their vintage dresses but would it really work for my knits? Could I really get away without doing a proper photo shoot? It would be a game changer if I could. 

So I thought I'd do a little researching and a little testing, just to see. 

Here are some AI images of my very latest design. Can you guess what it is?
 

• Adding extra fabric to the garment.
• Intricate stitches turn into plain fabric.
• Extra frills appear from nowhere.
• Colours and patterns change or blur.
• Parts of the garment can vanish.
• Wrong garment is assumed

These glitches happen when AI can’t work out how the garment hangs or where details should go, so it “fills in the blanks” with what it thinks should be there.

I learnt for now, nothing beats a real photo of my actual work.  So here is my latest design, the Sea Kelp shawl.

and for the techies out there, here is a fuller explanation

AI image generation tools can take a photo of a garment laid flat – for example, a sweater, shawl, or dress – and create a realistic image of that garment worn by a virtual model. This process uses a technique called image-to-image generation or virtual try-on. The AI analyses the original photo to detect colours, shapes, textures, and patterns, then “projects” those details onto a chosen model pose.

However, there are challenges. AI doesn’t actually understand what a garment is or how it’s constructed. It’s matching visual patterns, not working from a pattern schematic or knitting chart. This can lead to:

• Misinterpretation of the garment’s shape – A shawl might be draped incorrectly, a cardigan may appear to be a pullover, or sleeve lengths might change, because the AI guessed wrong about how the fabric should hang.

• Added or lost details – The AI may invent extra texture, change stitch patterns, add seams or embellishments, or even simplify complex areas into flat colour. This happens because the AI is “filling in gaps” where the original photo didn’t provide enough visual information for the new angle or pose.

• Colour and pattern shifts – Subtle shades, gradients, or intricate colourwork may get blurred or replaced with more generic patterns if the AI can’t recognise or recreate them convincingly.

• Incomplete or missing parts – Edges of the garment might disappear, accessories could be removed, or folds may get erased if they don’t match the AI’s training data for similar garments.

These issues occur because AI generates images by blending the input photo with its own learned patterns from millions of other images. If the garment has unusual shapes, stitches, or construction, the AI’s “best guess” may stray far from reality.

The more accurate and high-quality the source photo – especially with clear edges, good lighting, and minimal distortion – the better the AI’s results.

IMPORTANTLY for knitters, crocheters, and other makers, AI still can’t replace the eye and knowledge of someone who truly understands the craft.