generative AI

Vibe Coding and the Return of Personal Software

Vintage styled computer terminal with the text "What will you build today?" displayed on screen

The Echo of Early Personal Computing

There was a brief, electric moment in the history of computing—roughly the late 1970s through the mid-1980s—when ordinary people could sit down at a keyboard and make a machine do something it hadn't done before. The Commodore 64, the BBC Micro, the Apple II: these were limited, clunky, and profoundly empowering. For a generation, they opened the door to a kind of creative agency that felt almost magical.

That door closed, gradually, as software became professionalized. The gap between what you could imagine and what you could build widened into a canyon. If you wanted a tool that didn't exist, you needed a developer—or you went without.

Vibe coding is reopening that door.

The term refers to the practice of describing what you want in natural language and letting a generative AI—tools like Claude, ChatGPT, or Copilot—write the code for you. No syntax to memorize. No debugging by hand. You describe your intent, and working software comes back in seconds.

In this episode of Modem Futura, we explore what this shift means—not just technically, but humanly. I demonstrates tools he built from single prompts (also referred to as a a ‘one-shot’): a horizon-scanning app for futures research and a two-by-two uncertainty matrix used in strategic foresight. Both were functional on the first attempt. Both took less time to create than it takes to describe them.

The Inherited Power Problem

But the episode resists the temptation to treat this as a simple good-news story. The hosts dig into the real tensions: AI-generated code that no one fully understands, security vulnerabilities baked into apps that reach market before anyone reviews them, the new threat landscape of prompt injection, and the philosophical question of wielding power you haven't earned the literacy to evaluate—what the hosts call "inherited power."

There are also rich implications for education. Rather than relying on off-the-shelf apps that never quite fit, instructors and students alike can now build purpose-specific tools—and in doing so, develop a more grounded understanding of what these AI systems can and cannot do.

The deeper question the episode surfaces is less about code and more about agency. For decades, software was something done to us—platforms we adapted to, interfaces we learned, ecosystems we bought into. Vibe coding hints at a possible reversal: software shaped by the individual, for the individual, in the moment they need it.

Whether that future is liberating or reckless—or both—depends on the kind of literacy, caution, and imagination we bring to it.

Listen to the full conversation on Modem Futura.

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🎧 Apple Podcast: https://apple.co/4rbOr9r

🎧 Spotify: https://open.spotify.com/episode/28DMXJsM2kEBA2QDxuDmtJ?si=AJpR7zCpRgS2KCCfWwjjWg

📺 YouTube: https://youtu.be/lQGYaiThuBk?si=nRbHVEQk9dwL3gXr

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Generative AI Webinar Conversation Series

Hosting a Webinar Conversation Series

I was honored to be asked to host a series of conversational webinars with fellow AI experts at Arizona State University this spring. This webinar series provided an opportunity for faculty, staff, and students to engage in contemporary and emergent discussions around the use of generative AI in higher education. You can access the full webinar series along with other generative AI resources for ASU from the PO’s official website: Office of the University Provost: Generative AI

Episode 01 (April 4, 2023): What are generative AI tools?

Episode 02 (April 5, 2023): What generative AI tools are available?

Episode 03 (April 13, 2023): In what ways can generative AI impact academic integrity?

Episode 04 (April 14, 2023): How can ASU foster a positive culture around generative AI?

Episode 05 (April 18, 2023): Generative AI’s impact on critical thinking and research?

Episode 06 (April 19, 2023): Generative AI and social justice



Background For Conversation series

Generative artificial intelligence (AI) has been a burning topic of conversation far and wide since late 2022 - and the discussions among the higher education community is just one sector (out of many) that are trying to grapple with this seemingly sudden wide-spread emergent technology. While Generative AI tools have been available for a while, the sudden appearance of user-friendly interfaces popularized by OpenAI’s ChatGPT and Stability.ai’s Stable Diffusion, Midjourney, etc. have ushered in a new era of access to these large machine learning tools that were previously only accessible to those with more advanced AI / ML knowledge than the general public.

What is Generative AI?

Generative AI is a type of artificial intelligence that uses machine learning algorithms to create new content based on user input, without being explicitly programmed. Generative AI systems are trained using large datasets, and analyze patterns, rules and statistical structures to generate new content. There are different types of generative AI applications and models, each using different machine learning models, neural networks and approaches to generating content. Examples of generative AI include ChatGPT, DALL-E and StableDiffusion. DALL-E and StableDiffusion are text-to-image generators that use a type of neural network called generative adversarial network (GAN) to create new images based on input parameters. ChatGPT builds a transformer-based language model from a generative pre-trained transformer (GPT) to process sequential data and generate sequenced responses.



Unlocking Creativity with a Generative AI Workshop

Generative AI Workshop

An exploration of emergent artificial intelligence tools, Spring semester 2023.

Spring semester 2023 - the one topic that seems inescapable is artificial intelligence (AI) or more specifically the “Cambrian explosion” of generative AI platforms such as ChatGPT, StableDiffusion, Elevenlabs, and MidJourney just to name a few. This increasing awareness and need for exploring and understanding generative AI led to the development of this short introductory workshop offered in the Spring 2023. One of the core tenants of the experience is taking a hands-on approach through a Learn-it, Try-it, and Apply-it model with a short section of reflection.

Goals and Learning Outcomes

As educators work to familiarize themselves with these new and emergent tools this workshop was designed to foster a positive discourse to encourage a constructive dialogue and atmosphere regarding the integration of Generative AI in educational practices, academic research, and creative endeavors.

Learning Outcomes

  1. High level understanding of fundamental technology behind popular generative AI applications

  2. Discuss experiences and observations of affordances and constraints of generative AI tools

  3. Evaluate potential impact on educational context, and identify areas of need for deeper understanding

Background on the Purpose and Need

As the field of Artificial Intelligence (AI) continues to evolve and grow, there has been an increasing interest in the use of Generative AI in various industries (or perhaps another way to think about this - are there any industries at the moment that is NOT looking into the disruptive potential of generative AI?). In the field of higher education, Generative AI has the potential to revolutionize the way students learn and interact with the world around them. By enabling machines to generate new and unique content, educators can create personalized learning experiences that cater to each student's individual needs. However, with this exciting potential comes a need to understand how this technology actually works, and to evaluate the affordances and constraints it has in each contextual setting. Hosting a workshop for higher education faculty on Generative AI is crucial for ensuring that educators have the skills and knowledge necessary to incorporate this technology into their teaching practices effectively.