The Neuron: AI Explained

The Neuron

The Neuron covers the latest AI developments, trends and research, hosted by Grant Harvey and Corey Noles. Digestible, informative and authoritative takes on AI that get you up to speed and help you become an authority in your own circles. Available every Tuesday on all podcasting platforms and YouTube. Subscribe to our newsletter: https://www.theneurondaily.com/subscribe

  1. 2H AGO

    Can AI Improve Customer Service Without Killing Jobs? Crescendo Thinks So

    Customer service is one of the industries most impacted by AI — but what if AI alone isn’t the answer? In this episode of The Neuron Podcast, Grant Harvey and Corey Noles sit down with Matt Price, Founder & CEO of Crescendo, to explore how AI and humans working together can outperform automation alone. After spending 13+ years at Zendesk, Matt is now building an AI-native customer experience platform that automates up to 90% of tickets with 99.8% accuracy — without sacrificing empathy, trust, or outcomes. We cover: • Why LLMs are the biggest shift in customer service since the telephone • Why bolting AI onto old CX workflows fails • How Crescendo’s multimodal AI can chat, talk, see images, and control devices in one conversation • Real-world examples (like smart sprinkler troubleshooting via voice + vision + APIs) • Why Crescendo combines AI agents with forward-deployed human experts • How outcome-based pricing aligns incentives around real customer satisfaction • How AI is reshaping (not eliminating) customer service jobs • Why “deflection” is the wrong mindset for CX — and what replaces it • What customer support roles look like in an AI-native future This is a deep dive into the next generation of customer experience, where AI handles scale and speed — and humans deliver judgment, empathy, and innovation. Subscribe for weekly conversations with the builders shaping the future of AI and work. Subscribe to The Neuron newsletter for more interviews with the leaders shaping the future of work and AI: https://theneuron.ai

    57 min

  2. 3D AGO

    How Google's Gemini CLI Creator Ships 150 Features a Week

    Taylor Mullen, Principal Engineer at Google and creator of Gemini CLI, reveals how his team ships 100-150 features and bug fixes every week—using Gemini CLI to build itself. In this first in-depth interview about Gemini CLI's origin story, we explore why command-line AI agents are having a "terminal renaissance," how Taylor manages swarms of parallel AI agents, and the techniques (like the viral "Ralph Wiggum" method) that separate 10x engineers from 100x engineers. Whether you're a developer or AI-curious, you'll learn practical strategies for using AI coding tools more effectively. 🔗 Links: • Gemini CLI: https://geminicli.com • GitHub: https://github.com/google-gemini/gemini-cli • Subscribe to The Neuron newsletter: https://theneuron.ai

    56 min

  3. FEB 13

    BONUS: OpenAI Codex Demo, Learn the Absolute Basics of Coding with AI

    In this week's live-stream replay, we go live for a 2-hour, hands-on deep dive into GPT-5.1 Codex Max with Alexander Embiricos, product lead for OpenAI Codex. You’ll walk out feeling like an agentic-coding wizard, even if you’re starting from zero. GPT-5.1 Codex Max is OpenAI’s latest frontier agentic coding model. It’s built on an upgraded reasoning backbone and trained to handle real-world software engineering tasks end to end: PRs, refactors, frontend builds, and deep debugging. It can work independently for hours, compacting its own history so it can refactor entire projects and run multi-hour agent loops without losing context. In this live session, we’ll set it up together, build real agents, and push Codex Max to its limits.

    2 hr

  4. FEB 10

    Why Energy-Based Models Could Be the Next Big Shift in AI

    Modern AI has been dominated by one idea: predict the next token. But what if intelligence doesn’t have to work that way? In this episode of The Neuron, we’re joined by Eve Bodnia, Founder and CEO of Logical Intelligence, to explore energy-based models (EBMs)—a radically different approach to AI reasoning that doesn’t rely on language, tokens, or next-word prediction. With a background in theoretical physics and quantum information, Eve explains how EBMs operate over an energy landscape, allowing models to reason about many possible solutions at once rather than guessing sequentially. We discuss why this matters for tasks like spatial reasoning, planning, robotics, and safety-critical systems—and where large language models begin to show their limits. You’ll learn: What energy-based models are (in plain English) Why token-free architectures change how AI reasons How EBMs reduce hallucinations through constraints and verification Why EBMs and LLMs may work best together, not in competition What this approach reveals about the future of AI systems To learn more about Eve’s work, visit https://logicalintelligence.com. For more practical, grounded conversations on AI systems that actually work, subscribe to The Neuron newsletter at https://theneuron.ai.

    56 min

  5. FEB 6

    BONUS: Our 2026 AI Predictions.... Who Wins, Who Loses, and What Changes Everything?

    AI is moving fast — and 2026 is shaping up to be a turning point. In this livestream, Corey and Grant from The Neuron break down our biggest AI predictions for 2026, including: 🏆 Which companies, tools, and model types are most likely to come out on top 📉 Who could lose ground (and what’s driving the shift) 🎲 The wildcards most people aren’t factoring in yet 👀 What to watch across AI policy, agents, open source, and consumer adoption 🧠 The skills and strategies that will matter most in 2026 Join us live for audience Q&A and a real-time debate on the hottest AI takes — then drop your prediction in the comments: what’s the biggest AI surprise coming in 2026? 🔮 Subscribe for weekly AI coverage from The Neuron and more livestreams like this. 🎙️ https://theneuron.ai

    2h 41m

  6. FEB 3

    Inside Google Labs: 3 AI Tools That Will Change How You Create

    In this special episode, we go hands-on with three cutting-edge AI tools from Google Labs. First, Jaclyn Konzelman (Director of Product Management) demos Mixboard, an AI-powered concepting board that transforms ideas into visual presentations using Nano Banana Pro. Then, Thomas Iljic (Senior Director of Product Management) shows us Flow, Google's AI filmmaking tool that lets you create, edit, and animate video clips with unprecedented control. Finally, Megan Li (Senior Product Manager) walks us through Opal, a no-code AI app builder that lets anyone create custom AI workflows and mini-apps using natural language. Subscribe to The Neuron newsletter: https://theneuron.ai Links: Mixboard: https://mixboard.google.com  Flow: https://flow.google  Opal: https://opal.google  Google Labs: https://labs.google

    1h 57m

  7. JAN 27

    This AI Agent Builds Better Code Than Most Developers (Factory AI)

    Autonomous coding agents are moving from demos to real production workflows. In this episode, Factory AI co-founder and CTO Eno Reyes explains what "Droids" really are—fully autonomous agents that can take tickets, modify real codebases, run tests, and work inside existing dev workflows. We dig into Factory's context compression research (which outperformed both OpenAI and Anthropic), what makes a codebase "agent-ready," and why Stanford research found that the ONLY predictor of AI success was codebase quality—not adoption rates or token usage. Whether you're a developer curious about autonomous coding tools or just want to understand where AI engineering is headed, this episode is packed with practical insights. 🔗 Try Factory AI: https://factory.ai 📰 Subscribe to The Neuron newsletter: https://theneuron.ai 📖 Resources mentioned: • Factory's compression research: https://factory.ai/news/evaluating-compression

    56 min

  8. JAN 23

    OpenAI Researcher Explains How AI Hides Its Thinking (w/ OpenAI’s Bowen Baker)

    AI reasoning models don’t just give answers — they plan, deliberate, and sometimes try to cheat. In this episode of The Neuron, we’re joined by Bowen Baker, Research Scientist at OpenAI, to explore whether we can monitor AI reasoning before things go wrong — and why that transparency may not last forever. Bowen walks us through real examples of AI reward hacking, explains why monitoring chain-of-thought is often more effective than checking outputs, and introduces the idea of a “monitorability tax” — trading raw performance for safety and transparency. We also cover: Why smaller models thinking longer can be safer than bigger models How AI systems learn to hide misbehavior Why suppressing “bad thoughts” can backfire The limits of chain-of-thought monitoring Bowen’s personal view on open-source AI and safety risks If you care about how AI actually works — and what could go wrong — this conversation is essential. Resources: Title URL Evaluating chain-of-thought monitorability | OpenAI https://openai.com/index/evaluating-chain-of-thought-monitorability/ Understanding neural networks through sparse circuits | OpenAI https://openai.com/index/understanding-neural-networks-through-sparse-circuits/ OpenAI's alignment blog: https://alignment.openai.com/ 👉 Subscribe for more interviews with the people building AI 👉 Join the newsletter at https://theneuron.ai

    55 min
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About

The Neuron covers the latest AI developments, trends and research, hosted by Grant Harvey and Corey Noles. Digestible, informative and authoritative takes on AI that get you up to speed and help you become an authority in your own circles. Available every Tuesday on all podcasting platforms and YouTube. Subscribe to our newsletter: https://www.theneurondaily.com/subscribe

Information

  • Creator
    The Neuron
  • Years Active
    2024 - 2026
  • Episodes
    62
  • Rating
    Clean
  • Copyright
    © The Neuron
  • Show Website
    The Neuron: AI Explained

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