> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

---
title: "Podcasts & YouTube"
url: https://daily.dev/agentic-ai-hub/podcasts-youtube/
description: "Latent Space (swyx & Alessio): latent.space/podcast. Best for: the AI-engineering discipline."
lastUpdated: "2026-07-22"
---

## Podcasts

- **Latent Space** (swyx & Alessio): [latent.space/podcast](https://www.latent.space/podcast). *Best for:* the AI-engineering discipline. Deep, technical interviews with founders and researchers.  
- **Dwarkesh Podcast** (Dwarkesh Patel): [dwarkesh.com](https://www.dwarkesh.com/) / [YouTube](https://www.youtube.com/@DwarkeshPatel). *Best for:* long, rigorous conversations with frontier researchers and CEOs (the Dario Amodei and DeepMind episodes are notable). Unusually well-prepared.  
- **No Priors** (Sarah Guo & Elad Gil): [no-priors.com](https://www.no-priors.com/). *Best for:* an investor-and-founder view of where AI is heading; strong guest list.  
- **The Cognitive Revolution** (Nathan Labenz): [cognitiverevolution.ai](https://www.cognitiverevolution.ai/). *Best for:* fast coverage of new capabilities with a builder and safety balance.  
- **Lex Fridman Podcast**: [lexfridman.com/podcast](https://lexfridman.com/podcast/). *Best for:* long interviews with prominent names in the field. Uneven but occasionally definitive.  
- **Machine Learning Street Talk (MLST)**: [YouTube](https://www.youtube.com/@MachineLearningStreetTalk). *Best for:* deep, philosophical, technically serious debates; a lower-hype option.  
- **The TWIML AI Podcast** (Sam Charrington): [twimlai.com/podcast](https://twimlai.com/podcast/twimlai/). *Best for:* long-running, deeply technical interviews with ML researchers and practitioners. 770+ episodes and still going.  
- **AI + a16z** (Andreessen Horowitz): [a16z.com/podcasts/ai-a16z](https://a16z.com/podcasts/ai-a16z/). *Best for:* a builder-and-infrastructure view of applied AI from the investor side.  
- **Hard Fork** (Kevin Roose & Casey Newton): [nytimes.com/column/hard-fork](https://www.nytimes.com/column/hard-fork). *Best for:* a mainstream, well-produced weekly take on AI and tech news. The accessible on-ramp.

## YouTube channels

- **Theo (t3.gg)**: [youtube.com/@t3dotgg](https://www.youtube.com/@t3dotgg). *Best for:* fast, opinionated reactions to AI tooling and the dev stack. Tracks what developers are arguing about this week. 🔄  
- **Andrej Karpathy**: [youtube.com/@AndrejKarpathy](https://www.youtube.com/@AndrejKarpathy). *Best for:* build-it-from-scratch lectures (nanoGPT, tokenizers, LLM intro).  
- **3Blue1Brown**: [youtube.com/@3blue1brown](https://www.youtube.com/@3blue1brown). *Best for:* visual intuition on neural nets and transformers. Explains why attention works.  
- **Yannic Kilcher**: [youtube.com/@YannicKilcher](https://www.youtube.com/@YannicKilcher). *Best for:* paper walkthroughs covering the math and the contribution.  
- **Two Minute Papers**: [youtube.com/@TwoMinutePapers](https://www.youtube.com/@TwoMinutePapers). *Best for:* quick hits on new research (especially generative and visual). Light but broad.  
- **AI Explained**: [youtube.com/@aiexplained-official](https://www.youtube.com/@aiexplained-official). *Best for:* benchmark-driven breakdowns of frontier releases. Skeptical and precise.