AE
AI Engineer
Episodes
- Coding Evals: From Code Snippets to Codebases – Naman Jain, Cursor
- From Vibe Coding To Vibe Engineering – Kitze, Sizzy
- Minimax M2: Building the #1 Open Model – Olive Song, MiniMax
- Proactive Agents – Kath Korevec, Google Labs
- Moving away from Agile: What's Next – Martin Harrysson & Natasha Maniar, McKinsey & Company
- Hard Won Lessons from Building Effective AI Coding Agents – Nik Pash, Cline
- The State of AI Code Quality: Hype vs Reality — Itamar Friedman, Qodo
- Can you prove AI ROI in Software Eng? (Stanford 120k Devs Study) – Yegor Denisov-Blanch, Stanford
- Agent Reinforcement Fine Tuning – Will Hang & Cathy Zhou, OpenAI
- RL Environments at Scale – Will Brown, Prime Intellect
- Efficient Reinforcement Learning – Rhythm Garg & Linden Li, Applied Compute
- Don't Build Agents, Build Skills Instead – Barry Zhang & Mahesh Murag, Anthropic
- 2026: The Year The IDE Died — Steve Yegge & Gene Kim, Authors, Vibe Coding
- VoiceVision RAG - Integrating Visual Document Intelligence with Voice Response — Suman Debnath, AWS
- Government Agents: AI Agents Meet Tough Regulations — Mark Myshatyn, Los Alamos National Lab
- Future-Proof Coding Agents – Bill Chen & Brian Fioca, OpenAI
- Katelyn Lesse – Evolving Claude APIs for Agents, Anthropic
- No Vibes Allowed: Solving Hard Problems in Complex Codebases – Dex Horthy, HumanLayer
- Defying Gravity - Kevin Hou, Google DeepMind
- Building Cursor Composer – Lee Robinson, Cursor