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All Episodes

Build Wiz AI Show — 229 episodes

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Title
1

Pacing the Frontier: A Blueprint for Measured AI Progress

2

The AI Agent Harness

3

@skills: An Open Protocol for Agent Skill Delivery

4

Policy on the AI Exponential

5

The Rise of Recursive Self-Improvement at Anthropic

6

AlphaProof Nexus: Advancing Mathematics Research via AI Formal Proof Search

7

Pi - and self-modifying AI Agents

8

Code with Claude - London 2026

9

Google I/O 2026 keynote

10

The Langchain Agent Development Keynote 2026

11

Building the Software Factory: From Code to Autonomy

12

Spec-Driven Development and Agentic Workflows in 2026

13

Efficient Pre-Training with Token Superposition

14

Skills at Scale: Building and Scaling Agentic Workflows

15

Jensen Huang on the AI Revolution 2026

16

Robotics' End Game: The Great Parallel to AGI

17

Andrej Karpathy at Sequoia - AI Ascent 2026: From Vibe Coding to Agentic Engineering

18

The Cognitive Revolution: Sequoia AI Ascent 2026 Keynote

19

Demis Hassabis on the Roadmap to General Intelligence

20

AHE: Observability-Driven Evolution of Coding-Agent Harnesses

21

Claude Mythos Preview

22

Anthropic Econimic Index Report 03/2026

23

How to Ship Complex Features 10x Faster with AI Agents

24

The Era of AI Psychosis and Agentic Leverage

25

Attention Residuals - from Kimi

26

Why long context make AI dumber

27

How Coding Agents Are Reshaping Engineering, Product and Design

28

Securing AI Agents and Execution Engine

29

The Blueprint for Engineering reliable AI Agents

30

The complete guide to build skills for AI Agents - from Anthropic

31

Something big is happening

32

AI Cybersecurity Trends and Defense Strategies for 2026

33

Agent World Model

34

Catching AI Sleeper Agent - LLM Backdoors

35

AI 2026: Scaling Laws, China, and the Race for AGI

36

The Hidden Cost of AI: Is Automation Killing Your Skills?

37

How AI changes software engineering

38

The creator of Clawd - ship code without reading it.

39

Kimi 2.5 and Data Agent Swarms

40

Claude's constitution

41

The World after AGI - Dario Amodei and Demis Hasssabis

42

Future of AI & Global Economy - Nvidia CEO Jensen Huang and BlackRock's Larry Fink

43

Recursive LM - model solves context rot

44

Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

45

DSPy: Programming and Optimizing LLM Workflows with Systems Mindsets

46

Based on Claude Agent SDK — Thariq Shihipar, Anthropic

47

Cybersecurity Trends in 2026: Shadow AI, Quantum & Deepfakes

48

DeepSeek: Manifold-Constrained Hyper-Connections (mHC)

49

AI agent trends 2026 - Google

50

Building reliable AI Agent with domain memory

51

METR's Benchmarks vs Economics: The AI capability measurement gap

52

Adaptation of Agentic AI

53

Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning

54

Career Advice in AI

55

Leadership in AI Assisted Engineering

56

AI Consulting in Practice

57

Google - 5 days: Prototype to Production

58

Google - 5 days: Agent Quality

59

Google - 5 days: Context Engineering: Sessions & Memory

60

The Gemini Interactions API

61

Google - 5 days: Agent Tools

62

Google 5 days: Introduction to Agent

63

The Adoption and Usage of AI Agents: Early Evidence from Perplexity

64

Monetizing AI: Pricing Strategies and Experimentation

65

The 2026 State of AI Agents in Production - report from Anthropic

66

Agents to Skills: Building Expertise with Procedural Knowledge

67

The Renaissance Developer - Dr. Werner at AWS re:Invent 2025

68

The RPI workflow (Research, Plan, Implement) - for advanced AI Coding Agent

69

The complete IDE workflow for AI-driven development - the BMAD method

70

Weaponizing AI: The Rise of Autonomous Cyber Attacks

71

MAKER: Million-Step LLM Tasks with Zero Errors

72

From Context Engineering to AI Agent Harnesses

73

First AI-Orchestrated Cyber Espionage Campaign Disrupted

74

Sam Altman on the future of AI and its massive impact on society

75

🧠 Supervised Reinforcement Learning for Step-wise Reasoning

76

Kimi K2: the current Leading Open-Weight Agentic Model

77

AI Vision of the Future: An Expert Panel Discussion

78

Creating Claude Code: Agent Design and Product Philosophy

79

Context Engineering 2.0: The Context of Context Engineering

80

⚡ Agent Lightning: Reinforcement Learning for Any AI Agent

81

🛡️ Breaking Agent Backbones: Evaluating LLM Security in AI Agents

82

🚀 OpenAI's Future: Research, Product, and Infrastructure Vision

83

GitHub Universe 2025: Agent HQ, The Agent Workflow

84

Jensen Huang - NVIDIA - Keynote 10/2025

85

Perplexity at Work: A Guide to Getting More Done

86

Context Engineering for AI Agents - from LangChain vs Manus

87

💻 A Survey of Vibe Coding with LLMs

88

AI Adoption, Productivity, and System Thinking - from the interview with Huyen Chip

89

The Hidden Dangers of Browsing AI Agents

90

🤏 DeepSeek-OCR: Contexts Optical Compression

91

Claude Skills: Standard Operating Procedures for Agents

92

Self-Adapting Language Models (SEAL)

93

Training-Free Group Relative Policy Optimization for LLM Agents

94

OpenAI's Vision: AGI, Sora, and Bottlenecks

95

Agentic Context Engineering: Evolving Contexts for LLMs

96

Less is More: Recursive Reasoning with Tiny Networks

97

Understanding the 4 Main Approaches to LLM Evaluation - from Sebastian Raschka

98

OpenAI DevDay 2025: Agents, Apps, and GPT-5 Pro

99

Self-Supervised Learning and the Future of AI - from a lecture given by Yann LeCun

100

Skill erosion, where relying on intelligent systems creates an "illusion of mastery" while core competence fades

101

The Essential Startup Guide to Building AI Agents with Google

102

LIMI: Less Is More for Intelligent Agency

103

AI Adoption: Claude and ChatGPT Usage Patterns

104

Teaching LLMs to Plan: Logical Chain-of-Thought Instruction Tuning for Symbolic Planning

105

⚖️ Self-Consistency Improves Chain-of-Thought Reasoning in LMs

106

Economic Index Report by Anthropic - 09/2025: Uneven Global and Enterprise AI Adoption

107

🤔 How People Use ChatGPT - from OpenAI Report

108

LLM Interview Questions: A Comprehensive Guide

109

Sam Altman & Khosla Ventures - AI: Evolution, Disruption, and the Future of Work

110

Distilling Step-by-Step: Outperforming LLMs with Less Data

111

😵‍💫 Why Language Models Hallucinate

112

Attention Is All You Need

113

LoRA: Low-Rank Adaptation of Large Language Models

114

The Ultimate Guide to Fine-Tuning LLMs

115

Compressing Large Language Models

116

The Enterprise AI Divide: Adoption, Failure, and Future Trends

117

AI's Rapid Ascent: MacroHard, Meta's Midjourney, and Sentient Concerns

118

Task-in-Prompt (TIP) adversarial attacks

119

Prompt Engineering: Still Essential – The Comprehensive Guide to AI Mastery

120

Andrew NG: Building Faster Startups with AI

121

LightRAG: Graph-Enhanced Retrieval-Augmented Generation for LLMs

122

Large Language Models (LLMs) in Cybersecurity

123

Fine-Tuning Large Language Models

124

Foundations of Large Language Models

125

GPT-5: The Future of AI

126

Small Language Models are the Future of Agentic AI

127

Deep Agents: Architectures for Advanced AI Performance

128

The Relentless Vision of Dario Amodei and Anthropic

129

Perplexity CEO: AI's Impact on Search, Browsers, and Jobs

130

Context Engineering with the PRP Framework

131

How to build an AI Agent

132

Navigating the Superintelligence Race

133

Founding Groq and the Future of AI

134

AI's Watershed: June 2025 Breakthroughs

135

Context Engineering

136

Becoming an AI-First Company: A Strategic Guide - BOX White paper

137

Software's Evolution: From Code to AI Operating Systems - Andrej Karpathy

138

The Agent Development Life Cycle

139

Small vs. Large AI Models: Trade-offs and Use Cases

140

GenAI: Skills, Markets, and Models

141

Apple WWDC 2025: Intelligence, Design, and Evolution

142

The Prompt Engineering Handbook

143

Darwin Gödel Machine: Open-Ended AI Evolution

144

Master Claude Code - Practical Tips and Tricks

145

Andrew Ng: State of AI Agents

146

Sergey Brin on the Future of AI and Gemini

147

Google I/O '25 Developer Keynote

148

Code with Claude Opening Keynote

149

Google I/O 2025 AI Stage: Day 1 Highlights

150

Microsoft Build 25 Keynote

151

Google IO 25

152

Log Anomaly Detection with LogLLaMA and RL

153

CySecBERT: Domain-Adapted Language Model for Cybersecurity

154

GitHub Engineering Success Playbook

155

Building AI Agents with a 7-Node Blueprint

156

How AI Reinventing Software Business Models

157

Sequoia AI Ascent 2025: The Trillion-Dollar Opportunity

158

LSAST: LLM-Supported Static Application Security Testing

159

MCP versus API: AI Agent Integration

160

A Survey of AI Agent Protocols

161

Mem0: Scalable Long-Term Memory for AI Agents

162

The Art and Science of Vibe Coding

163

12 factor agents

164

The AI Scientist: Automated Scientific Discovery

165

Thinking About Agent Frameworks: A Comprehensive Guide

166

Google A2A: Protocol for Interoperable AI Agents

167

Scaling AI Use Cases: An Adoption Guide

168

AI in the Enterprise: Seven Lessons from Frontier Companies

169

Practical Guide to Building AI Agents

170

Lightweight KG Reasoning with Language Model Prompts

171

Agentic Knowledgeable Self-awareness for Language Model Agents

172

AI 2027: Preparing for Superintelligence

173

Chapter 5&6: All-In on AI - How Smart Companies Win Big with Artificial Intelligence

174

Chapter 3 and 4: All-In on AI - How Smart Companies Win Big with Artificial Intelligence

175

All-In on AI: How Smart Companies Win Big with Artificial Intelligence (chapter 1 & 2)

176

Google Cloud Next 2025: The New Way to Cloud

177

AI's Growing Role in Software Development and the Future of Work

178

AI Model and Security Developments: Amazon, Google, Meta, Microsoft

179

AI Agents: Use Cases, Integration, and Business Impact

180

Decoding AI Agents: Infrastructure, Frameworks, and Market Trends

181

LLM Security: Threats, Detection, and Mitigation Strategies

182

Operationalizing Generative AI with MLOps on Vertex AI

183

LLMs for Domain-Specific Problem Solving

184

Vibe Coding: Setup, Advanced Tips, and Tricks

185

Agents Companion: Building and Evaluating Generative AI Agents

186

Generative AI Agents: Architecture, Tools, and Implementation

187

Embeddings and Vector Stores: A Comprehensive Guide

188

The Art and Science of Prompt Engineering

189

Foundational Large Language Models and Text Generation

190

Claude 3.7 Sonnet: Usage Patterns and Economic Insights

191

Qwen2.5-Omni: An End-to-End Multimodal Model

192

Knowledge Graph Enhanced Software Repair

193

GitHub Copilot: Enhanced AI with Custom Instructions

194

Knowledge Workers and Large Language Models: Current and Future Use

195

Chain-of-Tools: Reasoning with Massive Unseen Tools

196

Claude 3.5 Sonnet Achieves New SWE-bench Verified State-of-the-Art

197

Transformers Without Normalization: Dynamic Tanh Achieves Strong Performance

198

Fin-R1: Financial Reasoning with a Lightweight Language Model

199

Claude's "Think" Tool: Enhanced Complex Problem Solving

200

The Past, Present, and Future of AI for Developers

201

LLM Concepts Explained: Sampling, Fine-tuning, Sharding, LoRA

202

NVIDIA GTC 2025 Keynote: AI Factories and Accelerated Computing

203

Agentic RAG: Intelligent Retrieval Augmented Generation

204

🎣 Phishing: Attacks and Top Cybersecurity Defense Strategies

205

RAG vs. CAG: Augmenting AI Model Knowledge

206

LONGREPS: Reasoning Path Supervision for Long-Context Language Models

207

Prompt Engineering for AI

208

GraphFC: Graph-based Fact-Checking with Claim Decomposition

209

LLM Agents: A Survey of Planning Approaches

210

Anthropic's Model Context Protocol (MCP): Origins, Functionality, and Impact

211

🐳 Dockerizing AI: Model Context Protocol with Claude Desktop

212

Model Context Protocol: A QA Guide for AI Testing

213

Graph RAG: A Query-Focused Summarization Approach

214

AI Agents: Tools, Planning, and Failure Modes - Huyen Chip

215

AI Agents Research Papers: Best of 2024

216

Fine-Tuning LLMs: A Deep Dive into Alternatives

217

Advanced Prompt Engineering Techniques

218

ChatGPT Prompts for Software Engineers

219

The Art of AI Prompt Crafting

220

Generative AI Agents: A Comprehensive Guide

221

The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models

222

Building Effective LLMs Agents

223

Model Context Protocol (MCP) Explained

224

LazyGraphRAG: High-Quality, Low-Cost Graph-Enabled RAG

225

Retrieval Augmented Generation Architectures

226

Graph RAG: A Query-Focused Summarization Approach

227

DeepSeek-R1: Reasoning via Reinforcement LearningDeepSeek-R1: Reasoning via Reinforcement Learning

228

Google Cloud AI Business Trends 2025

229

LLM Post-Training: Reasoning, Reinforcement Learning, and Scaling