Subvolts take AI coding is a gamble; learn to keep your technical intuition. Mar 3, 2026
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Learn how AI tools are changing software engineering and how to maintain your technical intuition in this new landscape.
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Understand the potential shift in software development workflows and the implications of AI-assisted coding for productivity.
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Features a deep dive with a foundational researcher on the practical impact of AI on software development.

"Vibe Coding is a Slot Machine" - Jeremy Howard

1 h 27 Interview Hosts: Tim Scarfe
0:001:26:39

Audio streams from Machine Learning Street Talk (MLST). Your place is remembered on this device.

From Subvolts

Summary and analysis by Subvolts editorial, AI-assisted.

Summary

Machine Learning Street Talk features fast.ai founder Jeremy Howard discussing AI-assisted coding and the origins of fine-tuning. Howard explains why AI might make software engineering feel like a slot machine and how to keep technical intuition. The episode also touches on cognitive science and the future of developers.

Explained simply

This episode explores how AI tools might make writing computer code feel like a game of chance. It also looks at how AI started and how people can still be good at their jobs even with AI helpers.

Why listen

This episode is for developers and researchers interested in the practical implications of AI in software development. Howard, a pioneer in transfer learning, offers insights into how AI tools are changing the field. It connects to current frontier lab efforts in agentic AI and developer tools, highlighting the need for human intuition alongside AI assistance. Listen to understand the potential shift in software engineering and how to adapt.

On the mic
  • HostTim Scarfe
  • GuestJeremy Howardfast.ai founder, fast.ai
About
Key facts
  • Guest: Jeremy Howard
  • Title: Vibe Coding is a Slot Machine
  • Show: Machine Learning Street Talk
  • Length: 87 minutes
  • Key Topic: AI-assisted coding and the illusion of 'vibe coding'
  • Key Topic: Origins of modern fine-tuning and ULMFiT
Show notes from Machine Learning Street Talk (MLST)

Dive into the realities of AI-assisted coding, the origins of modern fine-tuning, and the cognitive science behind machine learning with fast.ai founder Jeremy Howard. In this episode, we unpack why AI might be turning software engineering into a slot machine and how to maintain true technical intuition in the age of large language models.


GTC is coming, the premier AI conference, great opportunity to learn about AI. NVIDIA and partners will showcase breakthroughs in physical AI, AI factories, agentic AI, and inference, exploring the next wave of AI innovation for developers and researchers. Register for virtual GTC for free, using my link and win NVIDIA DGX Spark (https://nvda.ws/4qQ0LMg)


Jeremy Howard is a renowned data scientist, researcher, entrepreneur, and educator. As the co-founder of fast.ai, former President of Kaggle, and the creator of ULMFiT, Jeremy has spent decades democratizing deep learning. His pioneering work laid the foundation for modern transfer learning and the pre-training and fine-tuning paradigm that powers today's language models.


Key Topics and Main Insights Discussed:


- The Origins of ULMFiT and Fine-Tuning

- The Vibe Coding Illusion and Software Engineering

- Cognitive Science, Friction, and Learning

- The Future of Developers


RESCRIPT: https://app.rescript.info/public/share/BhX5zP3b0m63srLOQDKBTFTooSzEMh_ARwmDG_h_izk


Jeremy Howard:

https://x.com/jeremyphoward

https://www.answer.ai/


---

TIMESTAMPS (fixed):

00:00:00 Introduction & GTC Sponsor

00:04:30 ULMFiT & The Birth of Fine-Tuning

00:12:00 Intuition & The Mechanics of Learning

00:18:30 Abstraction Hierarchies & AI Creativity

00:23:00 Claude Code & The Interpolation Illusion

00:27:30 Coding vs. Software Engineering

00:30:00 Cosplaying Intelligence: Dennett vs. Searle

00:36:30 Automation, Radiology & Desirable Difficulty

00:42:30 Organizational Knowledge & The Slope

00:48:00 Vibe Coding as a Slot Machine

00:54:00 The Erosion of Control in Software

01:01:00 Interactive Programming & REPL Environments

01:05:00 The Notebook Debate & Exploratory Science

01:17:30 AI Existential Risk & Power Centralization

01:24:20 Current Risks, Privacy & Enfeeblement


---

REFERENCES:

Blog Post:

[00:03:00] fast.ai Blog: Self-Supervised Learning

https://www.fast.ai/posts/2020-01-13-self_supervised.html

[00:13:30] DeepMind Blog: Gemini Deep Think

https://deepmind.google/blog/accelerating-mathematical-and-scientific-discovery-with-gemini-deep-think/

[00:19:30] Modular Blog: Claude C Compiler analysis

https://www.modular.com/blog/the-claude-c-compiler-what-it-reveals-about-the-future-of-software

[00:19:45] Anthropic Engineering Blog: Building C Compiler

https://www.anthropic.com/engineering/building-c-compiler

[00:48:00] Cursor Blog: Scaling Agents

https://cursor.com/blog/scaling-agents

[01:05:15] fast.ai Blog: NB Dev Merged Driver

https://www.fast.ai/posts/2022-08-25-jupyter-git.html

[01:17:30] Jeremy Howard: Response to AI Risk Letter

https://www.normaltech.ai/p/is-avoiding-extinction-from-ai-really

Book:

[00:08:30] M. Chirimuuta: The Brain Abstracted

https://mitpress.mit.edu/9780262548045/the-brain-abstracted/

[00:30:00] Daniel Dennett: Consciousness Explained

https://www.amazon.com/Consciousness-Explained-Daniel-C-Dennett/dp/0316180661

[00:42:30] Cesar Hidalgo: Infinite Alphabet / Laws of Knowledge

https://www.amazon.com/Infinite-Alphabet-Laws-Knowledge/dp/0241655676

Archive Article:

[00:13:45] MLST Archive: Why Creativity Cannot Be Interpolated

https://archive.mlst.ai/read/why-creativity-cannot-be-interpolat

Jargon decoded
fine-tuning
Jeremy Howard
adjusting a pre-trained AI model for a specific task.
transfer learning
Jeremy Howard
using knowledge gained from one task to help with another.
ULMFiT
Jeremy Howard
a foundational method for language model pre-training and fine-tuning.
agentic AI
NVIDIA
AI systems that can act autonomously to achieve goals.
Published
Show
Machine Learning Street Talk · Machine Learning Street Talk (MLST)
Length
1 h 27
Products
ULMFiT
Summary by
Subvolts, using an AI model (how we work). Spotted a mistake? Tell us.

Questions people ask

What is ULMFiT?
ULMFiT is a method developed by Jeremy Howard that laid the foundation for modern transfer learning and the pre-training and fine-tuning paradigm used in language models.
What is GTC?
GTC is a premier AI conference where NVIDIA and partners showcase breakthroughs in areas like physical AI, AI factories, agentic AI, and inference.

Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Machine Learning Street Talk (MLST).