technology
Hosted by John Jezl and Jon Rocha · technology · EN
Two Minds, One Model is a podcast dedicated to exploring topics in Machine Learning and Artificial Intelligence. Hosted by John Jezl and Jon Rocha, and recorded at Sonoma State University.
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Contact path
Verified email
Booking probability
29%
Guest openness
Selective
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Signup to Generate a PitchTwo Minds, One Model is a podcast dedicated to exploring topics in Machine Learning and Artificial Intelligence. Hosted by John Jezl and Jon Rocha, and recorded at Sonoma State University.
Two Minds, One Model is hosted by John Jezl and Jon Rocha. The show has published 13 episodes to date.
Recent episodes include "Two Minds, Lower Trust" (5 May 2026, 53 minutes), "Agent Architecture: A Look Under the Hood" (14 April 2026, 61 minutes), and "When the Scaffold Moves Inside" (9 April 2026, 50 minutes).
Two Minds, One Model publishes roughly every two weeks, with episodes averaging 61 minutes across 13 episodes.
Booking probability for Two Minds, One Model is 29%, and the host is rated Selective on guests. Two Minds, One Model requires a Pod Score of 80 or higher. Two Minds, One Model's contact route on record: verified email.
The strongest fits for Two Minds, One Model are IT Services & Software Development. Two Minds, One Model has a technology audience.
John Jezl and Jon Rocha hosts Two Minds, One Model, a technology podcast with 13 episodes published.
Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.
Episode #5
<p>Why orchestrate multiple AI agents when a single strong model is so capable? Jon walks through three distinct rationales — capability, parallel context, and trust — and uses Anthropic's Claude Mythos Preview and...
<p>This episode deconstructs how production AI agents are actually built, introducing a six-component architecture framework (system prompt, model, tools, memory, orchestration loop, and execution environment) and...
Episode #3
<p>This episode traces AI reasoning from human-designed external scaffolding (process reward models, test-time compute scaling) to internally emergent capability, culminating in DeepSeek R1's finding that a model...
<p>This episode is a practical guide to working with AI agents — covering what makes them different from chatbots, how to craft effective agentic prompts, how to calibrate trust and supervision across the autonomy...
Episode #1
<p>This episode traces how prompt engineering evolved from informal tricks (tipping, role-playing, "take a deep breath") into three structured reasoning frameworks — Chain of Thought, Self-Consistency, and Tree of...
<p>This season finale episode features interviews with two SSU computer science capstone teams applying AI/ML to real-world problems: Sean Belingheri's edge computing project using YOLO on a Raspberry Pi to identify...
<p>This episode examines how Anthropic's circuit tracing and attribution graph tools reveal the internal mechanics of Claude 3.5 Haiku across three categories of complex behavior, abstract representations, parallel...
Two Minds, One Model
<p>This episode explores how Anthropic researchers successfully scaled sparse autoencoders from toy models to Claude 3 Sonnet's 8 billion neurons, extracting 34 million interpretable features including ones for...
Two Minds, One Model
<p>This episode explores how Anthropic researchers successfully scaled sparse autoencoders from toy models to Claude 3 Sonnet's 8 billion neurons, extracting 34 million interpretable features including ones for...
Two Minds, One Model
<p>This episode explores how sparse autoencoders can decode the phenomenon of superposition in neural networks, demonstrating that the seemingly impenetrable compression of features into neurons can be partially...
Episode #3
<p>This episode of "Two Minds, One Model" explores the critical concept of interpretability in AI systems, focusing on Anthropic's research paper "Toy Models of Superposition." Hosts John Jezl and Jon Rocha from Sonoma...
Episode #2
<p>This episode explores why AI systems might develop harmful or deceptive behaviors even without malicious intent, examining concepts like convergent instrumental goals, alignment faking, and mesa optimization to...
Two Minds, One Model
<p>This premiere episode provides a comprehensive history of artificial intelligence development from the 1950s through the present day, tracing the cycles of excitement and disappointment ("summers and winters") that...
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