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Nicole Nehrig's With Her Own Hands: Women Weaving Their Stories is so good!  I also found it unexpectedly emotionally affecting and even therapeutic to read.

The book is a tribute to the resilience, creativity, and wisdom of women across cultures and generations. Through personal narratives, Nehrig invites readers into the intimate spaces where women have shaped their identities and communities—often through the literal and metaphorical act of weaving, but also knitting, lacemaking, quilting, & other textile arts. The book is both a celebration of craft and a reminder of the stories embedded in textiles.

Nehrig blends memoir, oral history, and cultural commentary, including each woman’s voice while maintaining a cohesive narrative arc. The stories are diverse in origin and experience, yet they share common threads of empowerment and transformation. I was moved by the honesty and vulnerability in these accounts, which range from quiet moments of reflection to bold acts of defiance and creativity.

Nehrig’s background in textile arts enriches the book with a deep appreciation for the physical and symbolic significance of the diverse crafts. Her descriptions of materials, techniques, and traditions are vivid and accessible. The inclusion of photographs and illustrations adds another layer of depth, allowing readers to visually engage with the work and its makers.

Notes I made as I was reading, for an idea of how wide-ranging the book is:

Weaving fabric as Peruvian cultural legacyRediscovering heritage natural dye recipesSu Hui’s embroidered kanji poem “Star Gauge”Connection between complex weave structures & computersCrocheting hyperbolic geometry & the coral reef project Leonora CarringtonCrazy quilt deep dive

With Her Own Hands serves as a valuable resource for educators, historians, and scholars interested in textile art & women’s studies. Nehrig’s commitment to honoring marginalized voices and preserving cultural heritage is evident throughout the book. It encourages readers to consider the ways in which storytelling and craft intersect, and how these practices can be used to foster healing, connection, and social change.

With Her Own Hands is a heartfelt and inspiring work that uplifts the voices of women and the traditions they carry. Nicole Nehrig has created a book that is not only informative and visually stunning but also deeply moving. It is a must-read for anyone who values the power of memory and story, the beauty of craft, and the enduring strength of women’s voices.

On a personal note, my aunt Mary was a quilter and a textile artist. She would have loved this book and I would have loved giving her a copy and hopefully discussing it with her someday. I felt like she was reading over my shoulder the whole time.

 

This book is a brilliant, much needed resource on the construction of underpinnings, support garment structures that help to create silhouettes of historical fashion. 
The author Mandy Barrington studied several extent pieces at historical clothing collections around the UK. The author teaches in a college program for historical costume, & tested out the methods and instructions with her own students. The book is accessible for even novice stitchers, although not for a complete neophyte. If you’ve ever sewn a garment from a pattern, you’ll be able to follow along.
It covers the tools and materials required, the vocabulary used, and the methods of pattern drafting and construction for underpinning garments from the 16th to the 19th centuries. The text is clear and concise, the photos are beautiful and illustrative, and handy diagrams are included for pattern layout & construction.
Highly highly recommend, an invaluable new resource!

Disclosure: this author once led a workshop at the school where I teach. I did not meet her and was not contacted to provide this review, but I am obliquely connected to her.

 

My cat Clea amazed that a smart litter box cleans itself

I’ve written a draft of an AI policy for the costume shop at the theater where I work. I'm sharing it here in case you’d like to use it as a template to craft your own policy or just see what language is used by a peer organization.

The costume shop does not use generative AI tools (LLMs or image-generators) in creating necessary paperwork for producing and tracking show costumes.

We respect the privacy of our performers, the ownership rights of their faces and biometric data, the licensing rights of script publishers, and the intellectual property rights of playwrights, photographers, and costume designers.

We prohibit uploading or inputting documents and imagery created by and for the shop, including (but not limited to) tracking documents, notes, cast lists, contact lists, fitting photos, headshots, research images, scripts, design renderings, etc. into any generative AI tool.

I wrote an initial draft then shared it with colleagues at other theatres for feedback and suggestions. After incorporating some of those suggestions, I shared it with my colleagues in my own department to get their opinions and input, made some more changes, and then our costume director shared it with other leadership. 

We’re posting it in our fitting room & on the main bulletin board in the costume shop, and the text will go into our handbook and the syllabi for practicum classes. 

This policy applies only to the costume workroom—whether the theatre itself or drama department adopts a policy that applies to student or professional designers remains to be decided and is outside the scope of this policy. 

Does your theater or costume shop have AI policy language you’d be willing to share in a comment? I would love to see examples of others.

An area of my work that I don't often discuss is commissions from kink clients.

People involved in kink have specific custom clothing, accessories, and equipment they want to have made and a costume production artist's skill set can be a good match for a creative, discreet, and open-minded maker. 

Many of the people who do this kind of work are involved in their local kink social scene, but some encounter it serendipitously. I first got involved doing these kinds of commissions when I lived in Boston. New England has a large and diverse kink community, and at the time, one of my coworkers at a regional theater costume shop had a second job working at a retail store that was a combination sex shop/leather gear purveyor. 

When his side-hustle employer Black Laboratories was looking to expand and prototype corsetry styles, they hired me and one of my coworkers as patternmakers. 

We both continued to work there even after the corsetry line launched, because the projects we worked on were creatively fulfilling. With us involved, the business could now offer a wider range of custom leather options beyond their stock styles of custom chaps, vests, and pants.

We made copies of patterns taken from existing pieces to replicate them in leather, and drafted patterns for one-of-a-kind commissions, like a leather French maid uniform and a leather baby bonnet and diaper cover for an adult wearer. 

Discretion is key with these clients and most of the time I offer a strict non-disclosure agreement—I don’t document my work, I won’t reproduce it for other clients, & I don’t keep records of the work that include a client’s legal name or other info that might link back to their identity. 

Many of these clients don’t want any record of the transaction to exist, so they are often barter/trade transactions—I have received compensation in auto and home repair services and goods like home-cooked food or fresh garden produce.

In a rare circumstance, I have permission from a client to share images and discuss elements of the construction of a custom piece, a leather blindfold with a locking buckle.

A locking buckle has a loop on the tongue for a padlock

😍 inspired custom leather blindfold
Here you can see the elongated strap holes (slots) that accommodate a locking buckle
Black faux fur lining



The blindfold in use illustrating the functionality of locking buckles
This piece was built to integrate with the client’s existing sensory-deprivation hood.  

I’m so excited for this new book, Costumers at Work, by Madeline Taylor. 

This book is an ethnographic analysis of the processes by which professional theatre costumes are created, but arguably also sociological and philosophical analysis contribute to the work. I admit upfront that I am not well-versed in the fields of ethnography, sociology, and philosophy, but I have worked in the field of costume production for professional entertainment for nearly 30 years, so that’s the standpoint from which I speak about this title.
The book has an Australian focus and a global scope. As an American and an author who has published in the field of contemporary costume production, I found this a thrilling read, and how frequently the author cited works by colleagues, people I know, and groups I am a part of such as Costume Professionals for Wage Equity.
This is not a quick read. Every chapter has citations within the text and an endnote bibliography of worka cited. The information is fascinating but dense, and thankfully, the chapters are divided into subsections. I read it very slowly, one or maybe two subsections a day. If you are a visual person, it has excellent Infographics & photographs to augment the text. 
I am excited because it contributes to scholarship beyond the insular world of theater and illuminates aspects of our craft that I can say, as someone who practices it, we frequently bemoan that people don’t know about or understand what we do on a granular level.

The American Association of University Professors is a union representing teachers at universities across the US. They have released a report, Artificial Intelligence and Academic Professions, which analyses campus attitudes on uptake of AI technologies, and provides some recommendations for faculty. 

You can read the entire report here, but it’s long. It leads with a concise summary that, if you’re reading it on a desktop/laptop fills one screen, and is only a 4-swipe scroll on a phone. 

Here are a few of the takeaways that stood out to me:

Faculty and staff widely use ed-tech tools, many of which incorporate AI, often unknowingly.Untested AI technologies are being adopted without sufficient scrutiny, raising concerns about reliability and educational value.AI initiatives are largely driven by administrations with minimal input from faculty, staff, or students.AI is contributing to work intensification, especially in undervalued academic tasks like plagiarism detection and course material creation.AI implementation often worsens outcomes in areas like job enthusiasm, academic freedom, and student success.Intellectual property and privacy protections are insufficiently addressed.

The report calls for labor standards that prevent deskilling, wage reduction, and erosion of faculty governance.Faculty should have the right to challenge harmful technologies and participate in decisions about their use.

In short, there’s a lot of food for thought here, and it’s good to read an inquisitive and critical perspective from a national vantage point, considering academic uptake of AI technologies.

Because I’ve had the most success generating images with Google Gemini, I decided to try to get it to generate something like the design I drew for the character of “Queen Victoria” in the show Shipwrecked! An Entertainment. 

First I asked it if I uploaded four sketches, could it generate a fifth one of Queen Victoria in mourning?

It replied:

I understand you'd like me to generate a fifth costume design rendering of Queen Victoria in a black dress, in the same style as four others you'd provide.

Unfortunately, I cannot directly "see" or "ingest" images you upload, nor can I replicate a specific artistic style from those images to generate a new one. My capabilities are primarily text-based.

To help you, you could try describing the style of your four renderings in detail. For example, you could tell me about:

The artistic medium: Are they sketches, paintings, digital art, etc.?

The level of detail: Are they highly realistic, stylized, abstract?

The color palette: Are they vibrant, muted, monochromatic?

The overall mood or aesthetic: Are they whimsical, dramatic, elegant, minimalist?

Any specific techniques or characteristics: Do they feature particular brushstrokes, textures, or linework?

With a detailed description of the style, I might be able to generate a textual description of a fifth rendering that aligns with your vision. However, I wouldn't be able to produce the visual image itself.

So I answered with all the parameters that it wanted to know to generate a description, it did so, and then I asked it to generate an image of that description. Despite having said it would not be able to produce an image, here’s what it created:

.
Not bad, given here’s my original sketch:

It’s worth mentioning that in the show, there are only three performers and this role was played by the one who was a 6’2” tall man on his knees (hence the bustle style to hide his legs) and he had a 30-second quick change into it. Throughout the series of renderings, I drew consistent features for each of the players when rendering costumes for the many roles they played.
But those are factors that make it unlikely that generative AI will become agile enough and manipulable enough to be helpful in the field of costume design in the development of final designs. But the future may prove me wrong. As an initial sketch illustrating how I envisioned the character of “Queen Victoria,” setting aside the fact that we would have to figure out how the part would be played by the 6’2” actor, the Gemini sketch is acceptable.
Just on a lark, I asked Gemini to generate another version of a Queen Victoria costume design rendering in the style of Erté & got this:

Meanwhile, Microsoft Copilot struggled with this because Queen Victoria is a real historical figure, an actual human who existed, and the license code of ethics prevented it from generating an image specifically mentioning her in the prompt, so I revised the language, asking for a sketch of a Victorian queen in mourning attire, and got these:
. .


Every time I think I have figured out something about how this technology works, I get an unexpected and surprising result causing me to question everything I thought I knew. In general, I feel like I’m past the point of diminishing returns with respect to image generating applicability in my discipline. The potentiality for clerical helpfulness with large language models feels more viable. .

 A mood board is a useful design tool. When I was an undergraduate in the 1990s, we made these as collages using stacks of old magazines, scissors, & glue. Those became digital Photoshop collages, then Pinterest boards, then Canva collages. 

Basically you create a composite of imagery that evokes the mood you’re cultivating. This is not where you’re doing research—I remember a classmate made a great mood board that included photos of fried chicken, corn, and opulent pearl necklaces. Wish I could remember what show it was for. 

The Pinterest board linked in my post on color palette generation began as a mood board pinboard. As the conceptual discussions progressed, I weeded the images included on that board to create the final color palette board in its current incarnation. I found this process more efficient and streamlined than the old-school paste-up collage method, which was fun but difficult to revise without creating an all new board, nevermind the difficulty of sharing it with other creative team members, even living in the same town.

Mood board generation is something I keep coming across suggested as a “delegatable” project AI could do, which feels like a suggestion from someone who has no idea the purpose a mood board is supposed to serve (at least in this context), and who has never created one themself.

Nevertheless, I decided to give it a go. A mood board is specifically helpful with visualizing complex production concepts, like the “Bollywood Jane Austen” example mentioned in that color palette post. I decided I would try a similar kind of aesthetic mashup, “manga kink Molière.”

Copilot generated these mood boards for me:

They’re compelling, but are peppered with odd elements like grids and pies of what would be swatches of colors, prints, or textures.. 

Also, the content appears to all be AI-generated images, rather than pulled from actual manga, actual kink media, or any literal historical imagery like paintings from Molière‘s era, Or related visual references, like images of Commedia dell’Arte characters/masks.

The argument could be made that my prompt needs to be refined to include more specific information about what the mood board should contain, but honestly, I think I would just import these graphics into Canva, erase the superfluous elements, and paste anything I found aesthetically appealing into a mood board I created as a digital collage from other research images I would’ve had to track down as well.

On a related note, I would absolutely love to work on a show with this concept. I’ve been part of the team on several Molière plays & made some cool costumes for them, but generally found the source material out of touch and frivolous. If those comedic, patriarchical plots and stock characters were placed within the context of a kink scene, it would all make so much more sense.

In a recent AI training offered by my university, the advice was given to start prompts by defining a role for Copilot, giving it a task, and specifying the format you’d like the output to be produced in. So I’ve begun to write my prompts telling it, “I am a costume designer and you are my research assistant,” or assistant illustrator, or clerical assistant, etc., depending on what I’m prompting it to do.

Whatever the output I’m looking for, it often suggests that it could assist me further by putting together a color palette.

In a costume design context, this is often not a case of simply picking a few colors I like. If the play is set in a specific time & place, it can involve researching colors that appear in that context. 

It can be more complex than that, such as for example, a show concept like “Bollywood Jane Austen” where the setting is Regency England but filtered through 1990s Indian cinema, but this is not a post about a deep dive on thematic color palette philosophy.

I wanted to test generative AI on the kind of visual research a costume designer needs to do and see whether it could synthesize that research into a useful color palette.

As a test project, I used a show I actually designed the costumes for in 2012, and created a color palette for, It’s a Wonderful Life the Radio Play. The show takes place in 1946, and the premise is that the cast are voice actors performing It’s a Wonderful Life as a radio play in a sound studio.

At the time, I created a Pinterest board of my visual research that informed the color palette for the costumes of that show, which I shared with the rest of the creative team and refined as the design process proceeded. It was an excellent way to share visual research with creative team members who might be located anywhere in the country. 

I gather Pinterest is no longer a good platform for this kind of visual research, because of its inundation with AI slop. Unfortunate, because it was so useful and helpful in costume design.

Here’s a screenshot of a section of that IAWLTRP color palette inspo pinboard, which gives you a good idea of the broad scope of the visual research:

At the time, there was an online digital tool that would take images you uploaded or linked to, pull a selection of the colors, and generate a color palette grid: 

I’m sure this tool was powered by machine learning, in the same way that the early versions of the Pantone app would pull Pantone colors out of a photograph or a digital image of an artwork and allow you to assemble a color palette. 
When you compare this color palette grid with the visual research on the pinboard, you can see that it worked well. 
Now let’s take a look at the color palettes Microsoft Copilot provided when I asked it to do some visual research from 1946 and provide me with two color palettes for gendered fashion of the time..

They’re not awful, they’re actually pretty decent but no matter how many different ways I phrased the prompt, I couldn’t get it to integrate these into a single 25-swatch block. Not necessary, they’re fine like they are, I just would prefer the information in a different format that it refused to acknowledge and provide.
So I find this application acceptable, but not superior to prior ways of doing it with simpler and more controllable digital tools. I acknowledge that this is a matter of personal preference, and I can imagine a designer who felt differently and preferred to use Copilot for this purpose.
I decided to fiddle around with the Pantone app (which I’m sure has integrated AI capabilities now) and I suspect this might be a better way to work with color extraction and color palette creation. Take a look at the screenshot from a composite analysis of the two palettes Copilot generated and my original palette grid:

Full disclosure: I haven’t used the Pantone app in months and it has updated since I last did—this is a screenshot of me futzing around trying to alter the automatic color palette (the row at the top). 
I also have the Canva app, which has a color picker and palette creation capabilities. I did not experiment with that, however, because I find it to be a less intuitively structured app. I’m sure it would work fine.
Conclusion: It’s not that Microsoft Copilot is incapable of this kind of task, it’s that there are specialized tools designed for working with images and color control that allow for more finesse.

If students can use AI to cheat on assignments, we must reimagine the assignments. 

The Chronicle of Higher Education released a special report recently, “Adapting to AI,”  about the impact AI is having and will have on institutions of higher learning.You can get a copy here if you’d like to read the whole thing. Much like with the fashion industry 2025 AI report, I read it and compiled this summary.

The report reveals that most colleges are still in the early stages of adapting to AI. A majority of administrators report feeling unprepared for AI-related changes; skepticism and resistance are high among faculty. However, some departments and institutions are taking initiative—developing guidelines, forming cross-functional committees, and piloting AI literacy programs.
Spotlight features address topics like how staff and non-academic administrative departments are using it, advice on developing guidelines for different campus populations, and a now-outdated section on securing government grants for R&D. 
The report offers some general advice to faculty across the board, particularly those teaching in creative fields:Engage with the Tools: Experiment with generative AI to understand its capabilities and limitations. I can say from firsthand experience that this is enormously important—in working with it, I quickly discovered its shortcomings and vulnerabilities. Foster Critical Literacy: Help students develop the skills to use AI responsibly and ethically [1]. This includes understanding how AI works, recognizing its biases, and evaluating its outputs critically. I would argue that this also includes educating students about its obscene ecological impacts and the lack of consent intrinsic to its training data. Advocate for Thoughtful Policy: If your institution lacks clear guidelines on AI use, consider advocating for policies that protect academic freedom & integrity while promoting ethical standards. And proactively craft course-specific AI policy for your syllabi. Collaborate Across Disciplines: Theater educators bring a unique perspective to conversations about creativity, authorship, and interpretation. Our voices are essential in shaping how AI is integrated into the arts and humanities, on our campuses and in the world. AI is a structural shift in how knowledge is produced, shared, and evaluated. As educators, we have a responsibility to engage with these technologies so we are informed about how our students may be using them, and perhaps not only to protect our disciplines but to enrich them. 
The arts have always been at the forefront of cultural transformation. This is another such moment. By approaching AI with curiosity, caution, and creativity, theater educators can help ensure that these technologies serve our students, our institutions, and the broader goals of education.


[1] Since this report is aimed at educators, I assume they are talking about Ethics in academic integrity here. I’m not sure generative AI can be used ethically when considered through the lens of consent in training data, or sustainability.

Ok, that’s the end of my report summary and it’s time for my Real Talk. 
I’ve been reading up on and experimenting with generative AI since the theatre season ended, because it was clear with the campus-wide rollout of Copilot across the university’s Microsoft Office suite of tools, our institution was going all-in for generative AI. 
No matter how I might feel about it, my students now would have access to it with its use facilitated and encouraged by the institution, so I felt I needed to develop an informed perspective on it and how students and peers might use it. 
Many colleagues within my own college and globally advocate a ban on AI in their courses & departments. I empathize with that impulse. Is it realistic, at a campus that has integrated AI access into our very email client? And this CoHE report has an extensive section about the fallibility of so-called “AI detectors.” 
If students can use AI to cheat on assignments, we must reimagine the assignments. 
I’ve decided to teach my students about what generative AI is, how it works and where at least some of the pitfalls are, and let them decide when, where, how, and if they want to use it. And if so, how to disclose & cite it.

For costume educators interested in reading more about how I’ve been experimenting with generative AI in our area of specialty, check out the posts with this blog’s “AI” tag.

Also, I’d love to read a think-piece by a dramaturg about theatre as the original analog diffusion model. Or attend a panel discussion on the topic.