Jane Friedman's Blog: Jane Friedman, page 3

Australian publisher launches children’s imprint

Smith Street Books, an independent publisher of nonfiction, has launched a children’s imprint, Little Smith.

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New DK imprint: Paper Sailor

UK-based DK is launching a lifestyle imprint with a focus on nonfiction categories such as cooking, crafts, gardens, and nature.

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Extraordinary Books launches in the US

The publisher splits profits with authors after costs are recovered and invests equal resources in every title published.

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Knit One, Revise Two: What Being a Knitter Taught Me About Writing

Photo by Markus Spiske

Today’s post is by author, editor, and book coach Nita Collins (@nitacollinswriter).

I was staring at my draft the other day, contemplating a scene I loved but that didn’t quite fit the storyline. As I debated whether to fix it or ignore it, a post from my knitting friend Dee popped up in my feed. “I screwed the pattern up,” she’d written in the caption under the photo of a partially finished pink scarf, “and I don’t know how to fix it without making it worse. Do I ignore it and hope it doesn’t show too much?” Suddenly, the connection between knitting and writing couldn’t have been clearer.

Writers and knitters have more in common than you might expect, because creative work, whether in words or in wool, rarely happens in a straight line from beginning to end. Creative work loops back on itself, gets all tangled up, and sometimes requires you to undo hours of effort before you can move forward again. Accepting this truth has been one of the hardest lessons for me as both a writer and a knitter, but also the most valuable.

Whether knitting or writing, new projects always start in the same exciting rush of possibility. I open a fresh Scrivener file, full of a story idea, certain that this will be the one to get me a literary agent and a publishing deal. My friend Dee falls in love with a scarf pattern, buys the yarn and casts on, visualizing the way she’ll look draped in perfectly knitted pink mohair.

We both get to work. Everything is flowing along smoothly until suddenly it isn’t.

Somewhere between casting on and binding off, between Chapter One and The End, we each realize we have a problem. Dee’s scarf has developed a mysterious hole. So has my novel. We’re each staring at wonkiness with no idea how it got there. Or how to fix it.

In these moments, the temptation to ignore what’s wrong in hopes it will disappear into the larger story fabric is strong. Even though we know the issues will simply compound themselves, Dee and I still carry on, hoping for the best. Hoping that when we get to the end, the problems will have magically sorted themselves out.

For both of us, this bit of magical thinking arises from the same fear: “What if I have to chuck it out the window and start all over?”

As human beings, we are fixated on the idea that progress should be visibly measurable. For a writer, forward motion is seen and measured in word count, number of pages, how many hours spent bum-in-chair, your novel in the airport bookstore. And since the act of undoing work means erasing visible evidence of forward motion, starting over can feel like sliding backwards. Negative progress. That’s why, when Dee has knitted 20 inches of lace or I’ve written 80,000 words, the thought of ripping back to the beginning is agony. “All that work!” we cry, feeling like complete failures.

The truth is that knitters drop stitches, and writers drop secondary plot lines, and even though it stings like heck, nobody—nobody at all—gets away without continually finding themselves on a skills-building learning curve.

Thankfully, one of the biggest things that being a knitter has taught me is that learning a new skill isn’t a pass/fail exercise; it’s more like climbing a spiral staircase. You go around and around, but each time when you come back to the same place, you’re a rung higher up with a clearer, more objective perspective as a result. Eventually, what used to feel like failure simply becomes fixing.

As a knitter who carefully tinks back stitch by stitch in order to correct a mistake, I’m not incompetent because I messed the pattern up in the first place, I am being attentive to my craft, learning as I go. When I finish a draft of my novel knowing that I will need to go back and make adjustments, I am doing the exact same thing. I am being attentive to my craft, and respectful of both my manuscript and my readers.

Still, it doesn’t always come easy, especially when I’m not sure what’s wrong in the first place, let alone what to do about it.

Which brings me to the next thing that knitting has taught me about being a writer in revision: Asking for help doesn’t make me any less the author of my own work.

When Dee encountered a problem she couldn’t resolve that day, her instinct was to reach out to other knitters for advice. Dee is still 100% the knitter of her scarf, even though someone else showed her how to fix that hole. The same goes for writers. When I lean on support, I’m not giving up authority; I’m gaining perspective and insight.

Perspective and insight bring with them something that every creative person needs in order to succeed, and that is: trust in the parts of the process that are not visually measurable.

Progress isn’t always linear, and it can’t always be measured visually, but it is cumulative. Every revision sends you another turn around that spiral staircase, teaching you something you’ll carry forward into the next project.

Knitting and writing both teach us that mistakes aren’t just inevitable, they’re instructive. Every dropped stitch, every tangled subplot is an invitation to learn. The willingness to stop, rework, apply what you learned, and keep going is what transforms a skein of mohair into a scarf, and my rough draft into a polished novel.

So if you find yourself staring at your manuscript with the same worried question my friend Dee had, “Do I fix it, or do I hope nobody notices?” choose the fix. Yes, it may mean ripping out a few rows. Yes, it may mean slowing down or even starting over, but the time and care you put into the process will be visible in your scarf’s smooth stitches and your novel’s clear arc.

So knit one, revise two. And trust that your story—and your skill—will be stronger for it.

New agent at Rosecliff

Arizona Bell has joined as an agent, specializing in nonfiction that tackles resilience, belief, and the human spirit under pressure.

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New agent at Susanna Lea Associates

This marks a return to agenting for Laura Mamelok; she was previously with Susanna Lea for a decade.

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New online magazine: Alderbrink

Adam Morgan, founder of Chicago Review of Books, has launched an online magazine dedicated to fine press books, including reviews and news.

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New streaming service from Scholastic

You can download the app and start streaming more than 400 hours of ad-supported content if you have a Roku or Amazon Fire TV.

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Links of Interest: September 24, 2025

The latest in bestsellers, trends, accessibility, culture & politics, and AI.

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How Creativity Survives in an AI Monoculture

Photo by Johnny Briggs on Unsplash

Today’s post is excerpted from Quiver, Don’t Quake: How Creativity Can Embrace AI by Nadim Sadek, founder and CEO of Shimmr AI, an AI-powered advertising platform.

I met Sadek in person at NYU’s Publishing Institute in January, and found him a warm, self-aware, and very human founder of an AI startup. His latest book tries to balance an optimistic take on how creative people can use AI, with a lucid assessment of its risks. For my readership, I’ve chosen to excerpt a portion about the risks.

In 2023, Manhattan attorney Steven A. Schwartz filed a federal court brief citing six judicial decisions, each seemingly perfect for his case. But every one of them was fictitious, hallucinated by ChatGPT, complete with plausible names, dates, and legal reasoning. When the deception was uncovered, the court sanctioned Schwartz and fined him $5,000. The incident became a landmark cautionary tale about the dangers of relying on generative AI without verification, particularly in fields where factual integrity is of paramount importance.

The first and most immediate set of dangers we all face regarding AI are practical ones. They’re the gremlins that live inside the current generation of AI models, the bugs in the system that can have serious real-world consequences.

The most famous of these is what’s termed hallucination. It’s what we identify when an AI confidently and articulately invents facts. It spits out nonsense. Because an LLM’s primary function is to generate statistically probable text, not to verify truth, it has no internal concept of what’s real and what isn’t. If it doesn’t have the correct information in its training data, it won’t say “I don’t know.” Instead, it’ll often generate a plausible-sounding answer that’s entirely fictitious. This has moved from a humorous quirk to a serious problem.

When I wrote an earlier book, I remember asking AI to do some research—to find other authors with a similar thesis to mine. Crestfallen, I looked at a long list of titles which seemed to occupy very much the same space I was in. Then I looked at their publication dates—all in the future! For any creator using AI for research—a journalist, a historian, a non-fiction author—the danger is clear. The AI is a brilliant research assistant, but a terrible fact-checker. Every piece of information it provides must be treated with suspicion and verified independently.

The second gremlin is bias amplification. At my company Shimmr AI, where we produce autonomous advertising using AI, I remember reproaching our Chief Product Officer about why our nascent video-forms were always much more convincing when the protagonist was a woman. She chided me. “Where do you think video generators have learned to produce credible renditions of women moving?” Well, the answer is from browsing the internet and capturing all the videos it can find. Pornography accounts for much of that. And it’s mainly women who populate pornography.

AI has learned to render women in videos much more convincingly than men largely because that’s what it’s found to train on. AI reflects the totality of its training data. The problem is that our digital world isn’t an unbiased utopia; it’s a reflection of our flawed, unequal societies. An AI trained on the internet will inevitably learn and reproduce the biases it finds there. If historical data shows that most CEOs are men, an image generator prompted with “a picture of a CEO” will overwhelmingly produce images of men. If online texts more frequently associate certain ethnicities with crime, the AI will learn that toxic correlation.

The danger isn’t just that the AI reflects our biases, but that it amplifies them, laundering them through the seemingly objective voice of a machine and presenting them as neutral fact. This can entrench stereotypes, poison public discourse, and cause real harm. It’s one reason why I advocate for everything we’ve ever created and produced—properly recognized and remunerated—to be included in AI training. We have an active role to play in producing ethical AI.

The next set of dangers are more subtle, but perhaps more corrosive in the long run. They concern what might happen to us, the human creators, as we become more and more reliant on our sophisticated new partner.

A friend recounted to me that she watched her son, 20 years old and bright as a button, working on a university assignment. He’d typed a prompt into ChatGPT: “Write a short essay about how HR can fail a corporation.” The AI delivered five perfectly structured paragraphs. He tweaked a sentence here, added a date there, and submitted it. Time elapsed: twelve minutes. Understanding gained: zero.

Many of us fear the dereliction of committed learning that is an obvious risk in the era of easy-AI.  Every tool that makes a task easier carries with it the risk that we forget how to do the task ourselves. We use calculators and our ability to do mental arithmetic fades. We use GPS and our innate sense of direction withers. The fear is that a generation of creators who grow up with AI as a constant companion won’t develop the foundational skills of their craft. Will a writer who’s always used an AI to structure their arguments ever learn how to build a narrative from the ground up? Will a musician who’s always used an AI to generate chord progressions ever learn the fundamentals of music theory?

This isn’t a Luddite argument against using new tools but a caution about the potential for our intuitive capabilities to atrophy. Creativity is a dance between our intuitive, associative spark and our analytical, structuring work. If we outsource all of the structuring, the editing, the refining to the AI, what happens to our own analytical capabilities? More importantly, what happens to the crucial interplay between the two? The process of wrestling with structure, of hitting a dead end and having to rethink your argument, is often what forces the most interesting intuitive insights to the surface. By taking away the friction, we risk taking away the fire.

This leads to a related fear: the homogenization of culture. What happens when millions of creators, from students writing essays to marketers creating ad campaigns to artists generating images, all start using the same handful of AI models? There’s a real danger that the output begins to converge on a bland, generic, AI-inflected mean. We may see the emergence of a new monoculture, where art, writing, and music all share the same statistically-probable, algorithmically-smoothed-out feel. The unique, the quirky, the truly original voice—the very things we value most in art—could be drowned out in a sea of competent but soulless content.

Bookshop • Amazon

Would a neural net have produced Being John Malkovich, a film about a portal into an actor’s consciousness hidden behind an office filing cabinet? Or Eraserhead, David Lynch’s surreal debut about parenthood, dread, and an oozing mutant baby? Almost certainly not. These works are weird, jagged, and defiantly human. They were born of obsessions, neuroses, and vision that no probability model would prioritize.

My belief is that the antidote to this AI slop (as some have been calling it) is that we’re endlessly eccentric, each human being communicating and manifesting in unique fashions. AIs respond to inputs—prompts—and so long as we each allow our intuitive side full rein, then the interactions produced in collaborating with AI will always result in idiosyncratic, unique outputs. We must continue to be us.

Note from Jane: If you enjoyed this article, check out Nadim Sadek’s new book Quiver, Don’t Quake: How Creativity Can Embrace AI.