In the spirit of the talk at Reclaim Open, I fed the details of the video summary provided by YouTube’s AI into the game preview GPT I created for AI Maddeness. It wrote a post in the “spirit” of how it breaks down a weekly match-up between two teams, it adjusted fairly well for the subject matter. I love the insistence ChatGPT makes on the “creative” possibilities of AI. While I think there’s something there, to be honest, it’s trying a bit too hard here 🙂
In fact, I’m not sure the following AI-generated post about the session is all that creative, but it does do a fairly good job capturing the talk’s highlights while revealing its own biases. There’s a sensation of floating outside yourself—kinda like Rusty James in Rumble Fish (1982)—when you having ChatGPT create a blog post like this. Anyway, here’s a breakdown of the talk Tom Woodward and I gave at Reclaim Open on AI Maddeness according to the machine
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Exploring the Wild Intersection of Artificial Intelligence, Creativity, and Madden NFL 2001
In their presentation “AI Maddeness: How (not) to blog with AI,” Tom Woodward and Jim Groom take audiences on a fascinating tour of their experimental journey — one that blends nostalgia, technology, and creative curiosity. Using Madden NFL 2001 as their playground, the duo reimagines what it means to create, play, and narrate through the lens of artificial intelligence.
The Birth of AI Maddeness
The session opens with the origins of the term “AI Maddeness” (1:22–1:36), coined by Tom Woodward to capture both the enthusiasm and chaos of experimenting with AI — and to pay playful homage to Madden NFL 2001. For Jim Groom, once an AI novice, this project marked his first true dive into generative technology — a blend of excitement, learning, and humor that would shape the entire talk.
His early experiments with ChatGPT (1:50–2:05), prompted by Tom, began with something deceptively simple: feeding the AI screenshots from Madden NFL 2001 and seeing what it could make of them.
Image Recognition and the “Wow” Moment
From 4:39–6:20, Groom and Woodward showcase what would become a breakthrough: the AI’s ability to extract structured data from screenshots — recognizing stats, names, and scores, and organizing them into usable formats like tables and CSV files.
Jim describes this as a genuine “wow” moment — the realization that AI could act not just as a creative partner but also as a kind of digital archivist, transforming static images into dynamic, reusable information.
When AI Hits Its Limits
Of course, AI Maddeness wasn’t all smooth sailing. Between 6:20–7:20, they encountered clear limitations: while the AI could handle player stats, it stumbled over more complex data like standings and schedules. Ironically, when it couldn’t solve the problem directly, the AI generated Python code to help them get there — revealing both its ingenuity and its dependency on human refinement.
Building Custom GPTs and AI “Agents”
By 7:53–8:30, Woodward introduces the concept of Custom GPTs, referencing terms like “Gems” and “Agents” used in other AI platforms. These specialized configurations allow users to define parameters and roles for the AI, ensuring more consistent outputs for tasks like generating game previews or creating visual assets. It’s a glimpse into how AI can be sculpted for specific creative workflows.
WordPress Integration and AI Personas
Perhaps the most entertaining segment arrives between 10:20–13:50, when they demonstrate their WordPress integration with AI to automate blog comments. By assigning distinct voices and personalities to each AI commenter — some witty, others argumentative or analytical — they transformed the blog’s comment section into a lively cast of digital personas.
This experiment blurred the line between human community and machine imagination, showcasing how AI can simulate engagement, satire, and even social dynamics.
Balancing Efficiency and Emotion
Despite the power of automation, Groom underscores an essential truth in 15:20–16:50 — the human element still matters. He chose to continue writing his own post-game summaries, driven not by efficiency but by emotional connection. AI could document the play-by-play, but it couldn’t capture the feeling of playing.
The duo also used AI to create GIFs from gameplay moments, adding another layer of personality and humor to their multimedia storytelling.
Simulated Games and AI Narration
In one of the project’s most thought-provoking experiments (17:19–18:46), they tested AI’s storytelling power by simulating games that never happened, then prompting the AI to “hallucinate” full recaps as if it had actually watched them unfold.
The results were surprisingly convincing — complete with player stats, dramatic moments, and post-game reflections. It raised playful but serious questions about reality, simulation, and the creative potential of machine-generated fiction.
Cultural Sensitivity and Responsibility
Around 18:48–19:58, Groom recounts including a reference to Washington DC’s now defunct team name far too casually in one of his AI-assisted posts. That moment, he reflects, was a reminder that intent doesn’t erase impact. Even in nostalgic or experimental contexts, creators have to balance historical authenticity with cultural awareness.
This led to a broader conversation about ethical use of AI — who’s responsible for what the machine produces, how to correct its oversights, and what it means to remix the past through automated storytelling.
Imagining the Future of AI in Gaming Media
The presentation concludes (25:24–29:10) with a forward-looking vision of AI-powered gaming media: autonomous systems that could instantly produce post-game recaps, podcast commentary, and even fantasy sports analysis — all dynamically generated as soon as a game ends.
While acknowledging this potential, Woodward and Groom also caution against the seductive ease of automation. AI can amplify creativity, but it can just as easily accelerate detachment or misinformation if used uncritically.
The Takeaway
AI Maddeness is far more than a quirky tech experiment — it’s a creative inquiry into the boundaries between human imagination and machine collaboration. With humor, reflection, and a healthy dose of self-awareness, Tom Woodward and Jim Groom reveal how AI can both inspire and unsettle our understanding of authorship.
Ultimately, AI Maddeness isn’t about teaching machines to think like humans — it’s about rediscovering what it means to create like one.

































