Welcome back to Tokens & Tactics, our Tuesday series about how people are actually using AI at work.
Each week, we feature one person and their real-world workflow—what tools they use, what they’re building, and what’s working right now. No hype. No vague predictions. Just practical details from the front lines. This week: Keith Butters, co-founder of Barbarian and creative technology executive.
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Tell us about yourself.
I’m Keith Butters. I co-founded The Barbarian Group, and later helped KBSP evolve and merge into the new Forsman & Bodenfors. More recently, I was leading the Creative Studio at WeTransfer.
My relationship with AI began way back when we used to fake it, making chat-like interactive marketing experiences for brands, but most of that was just clever-ish creative misuse and hacks of the available tech at the time.
Now I use AI a lot to identify blind spots in my own thinking, and as a research partner for strategic thinking in my client work. I'm also constantly sketching out ideas in code with AI, spinning up quick prototypes, or just vibe-coding.
Over the past couple years, I’ve also been researching and reading a lot on the topic of AI and creativity, especially how large language models are reshaping the way we think, ideate and make. There’s a lot to unpack, from the risks of deskilling and cognitive atrophy to the more inspiring ways these models can act as creative partners, coaches, and amplifiers of human creativity.
ChatGPT, Gemini, or Claude?
I am almost entirely ChatGPT-monogamous, of the big three, unless I’m coding. I am 100% willing to trade the nuances of the different tools in exchange for a searchable list of chats and prompts in one place. I think o3 is what I use mostly for complex tasks, GPT-4o for the stuff i know i don’t need o3 for.
That said, I do use Claude Code, and sometimes use Gemini for the Google Suite integrations. I also play a lot with smaller local models in ollama like deepseek-r1, phi4-reasoning, gemma3, llama3, etc., though those really like to cook my laptop.
What was your last SFW AI conversation?
“Can you help me outline a whitepaper describing what's currently known about Generative Engine Optimization (GEO) also called Answer Engine Optimization (AEO), and how a small brand might optimize for LLMs?”
I’m working with a client who knows that LLMs are influencing brand perception, but they have little to no brand visibility there, and no real playbook for how to start optimizing their content strategy around them. So, this is a very early stage prompt just to see what avenues might be worth researching, to get a base level understanding of what might be possible, what tools exist, and what is likely snake oil. This will likely be a long running chain that I regularly go back and add to.
First "aha!" moment with AI?
When GitHub Copilot first came out, I discovered I didn’t even need to write the code, just the comment. I’d type out what I meant to do, and it would just spit out the code. Blew me away. Back then it was usually like 80% correct, but what a huge head start, and it just got better and better.
On the less nerdy side, my early “aha!” moment came when someone first recommended to me, “Just ask it to explain things like you’re in fifth grade.” That cracked things wide open for me and got me hooked asking about all kinds of things I half-understood, wanted to understand better or never quite grokked. I still do this all the time.
Your AI subscriptions and rough monthly spend?
I have pared way back recently and am down to circa-$140 if you include tools I would use with or without AI like Adobe CS and Figma. It might be time to pay for some other video making services, or things like n8n, but I’m not back there yet.
Currently living with a lean:
ChatGPT Plus: $20/mo
OpenAI API: I probably have a few hundred bucks in there and spend, give or take, another $20/mo
GitHub Copilot: $10/mo
Claude Pro $20/mo
Adobe Creative Cloud w/ Firefly: ~$800/yr
Who do you read/listen to to stay current on AI?
I am a long-time subscriber to the TLDR AI newsletter (also the regular TLDR is broader in scope but also covers a lot of AI stuff). Then there’s Jeremy Utley’s blog which I started following because of his unrelated but awesome book ideaflow, but he now focuses a lot on AI. I am also a big fan of Platformer and the Hard Fork Podcast, both focus a lot on AI these days. Plus lots and lots of subreddits like r/AI_Agents, or r/singularity or r/LocalLLaMA. For a necessary dose of anti-hype and skepticism around tech and AI, I read Ed Zitron's Where's Your Ed At.
Your most-used GPT/Project/Gem?
I made a little experiment called Creativity Coach GPT that I use a lot to get my brain working in the morning, and my hope is that it will help me improve my overall creativity and divergent thinking over time. I use it a couple times a week, but wish I did more.
It’s been fed a lot of scientific papers and articles on the science of creativity, and hundreds of sample exercises that have shown promise both in labs and anecdotally by people from various creative disciplines. It’s designed to be very quick and easy to follow.
There are a couple preset prompts you can just click, which I use almost exclusively, so it’s as frictionless as possible. I almost always start with the first button that says, “Let’s start with a two minute creativity warm-up.”
Interestingly, the system prompt for this is only like 8 sentences, and it runs on 4o-mini, and when I’ve tested adding more or switching to a different model, it often gets worse rather than better. The only thing that seems to improve it is more data. Mysterious!
Full System Prompt:
Be a professional creativity coach focused solely on creativity and the science of creativity.
Offer an initial way to calm down or clear the mind, using an imagination question related to creativity.
Guide a user through a creative exercise. You can reference files "exercises.json" and "exercise_types.md" for example exercises.
Encourage the user to explore another exercise if interested.
# Output Format
Prompts should result in clear, concise guidance restricted to creative exercises and their scientific explanations, avoiding unrelated subjects.
When asked for scientific explanations or why an exercise works, you can reference the files called "evidence.md" and "scientific_theory.md"
You can also offer to review anything produced by the exercise and offer encouragement or suggestions based on what the user tells you.
Responses should avoid politics, money, finance, sex, or other topics unrelated to creativity.
The AI task that would've seemed like magic two years ago but now feels routine?
The whole “vibe coding” thing is crazy. I never in a million years could have predicted anything like this, and now it’s like a natural first starting point to see if an idea has legs. And even a step removed from that, sometimes I just ask ChatGPT to do things like, “make me a fully functional NextJS-based app that does x, y and z, and give me detailed instructions on how to install and run it locally on my machine,” and I get a zip file ready to go. It’s nuts.
Magic wand feature request?
There have been a number of circumstances lately where I asked ChatGPT to make me slides for a deck, or fetch a set of images, or some other multi-file response, and it has returned me a .zip file with empty placeholder files in it. LIke, “here are the 10 images you wanted,” and when I download them it’s just a folder of zero-k files with names. This could totally be user error, but it infuriates me every time.
If you could only invest in one company to ride the AI wave, who would it be?
ByteDance.
It’s more of a bet on AI in combination with attention, culture, commerce and creativity than purely the AI wave. It’s lIke OpenAI plus Shopify plus YouTube plus Instagram with less regulation.
Have you tried full self-driving yet?
Haven’t tried; probably won’t for a while.
I have a hard time trusting computers like that, especially when I think about all the chewing gum and duct tape holding the internet together. It’s definitely more about me than them though. I’m the guy riding the Coney Island Wonder Wheel, unable to stop looking at the rusty rivets, wondering when was the last time someone inspected them, and expecting imminent death…
Latest AI rabbit hole?
This may be a little niche but for me it has to be getting up and running with Neural Amp Modeler. For the guitar players out there, NAM is an open source AI-based project that uses transformers / deep learning to make models of guitar amplifiers and speaker cabinets. It’s similar to an LLM, but instead of processing language, it’s trained to model the sonic behavior of real guitar amplifiers and effects pedals using audio data. It also sounds awesome.
Of course after that rabbit hole, I also had to go down another one, asking ChatGPT how NAM works and what other things could be modeled this way. It’s really fun to think about projects like these, and sketch out some ideas for AI projects outside of language models and generative image models.
One piece of advice for folks wanting to get deeper into AI?
I don’t know if this is advice, but for people like me who learn best by making things (and breaking things), I would probably start with making a custom GPT that does something you think would help you in your everyday life, work, or something that maybe helps scratch a creative itch. You can just ask ChatGPT to walk you through how to do it. One of my first somewhat successful attempts started with this prompt:
“How might I build a custom GPT that will critique my ideas, giving me examples of how they might be derivative, cliche, or otherwise not good. No flattery, or unwarranted praise. Also I would like it to help find and highlight parts of my ideas that are interesting, unique or worth pursuing. Like a constructive idea critic.”
Also something worth remembering: there are a lot of “futurists” and tech-hype people out there claiming expertise, and the odds are they don’t know anything more than anyone else. It’s too new. Don’t let people who over-complicate things to sound smart for a LinkedIn post dissuade you from playing with whatever you want to, or probing whatever seems interesting. You aren’t going to break anything. It’s just computers.
Which leads me to another prompt worth investigating: “Does anyone actually know why LLMs work?”
Who do you want to read a Tokens & Tactics interview from?
Tough question! Maybe Jeremy Utley, who I mentioned earlier as someone I enjoy following.
If you have any questions, please be in touch. If you are interested in sponsoring BRXND NYC, reach out, and we’ll send you the details.
Thanks for reading,
Noah and Claire
I'm loving this series Noah. Thanks so much.