Becca just got back from NeurIPS, the academic AI conference that feels like an adult science fair. We dig into research on training large AI models across cheap GPUs and slow internet connections—and why that could dramatically lower the barrier to building AI.

Then we’re joined by Harper Reed, CEO of 2389, for a wide-ranging conversation about code generation, coaching-based engineering teams, and why “production code” might have always been a myth. We talk vibe coding (begrudgingly), the shifting role of software engineers, taste vs. technical skill, and what happens when you can build almost anything in a week.

Smart, funny, and a little unsettling—Chaos Agents at full volume.

1. NeurIPS (Conference on Neural Information Processing Systems)
2. NeurIPS 2024 Accepted Papers

1. NVIDIA H100 Tensor Core GPU (referenced GPU class)
2. Pluralis Research (distributed training across low-bandwidth networks)

1. GPU vs CPU explained (parallel vs sequential compute)
2. Data Parallelism vs Model Parallelism (training overview)

1. Claude Code (Anthropic code-gen tooling)
2. Cursor (AI-first code editor, discussed implicitly)

1. Matrix (open-source, decentralized chat protocol)
2. Model Context Protocol (MCP) overview

1. Jesse Vincent’s Superpowers (Claude workflow enhancer)
2. Fly.io (deployment platform referenced)
3. Netlify (deployment & hosting)