Best Chain of Thought Episodes on Open Source AI
Open weights, open ecosystems, and what they actually cost in production.
The open-versus-closed argument gets fought at the model layer and settled somewhere else: on what you can actually run on hardware you control, and on what the bill says at the end of the month. Nobody here argues the principle. They all show the arithmetic.
- 1 How DeepSeek Changed the AI Race Overnight Atindriyo Sanyal, Galileo The week DeepSeek’s R1 reset what an open model was allowed to cost. Recorded while it was still landing, which is why it holds up as a record of the argument rather than a retrospective on it.
- 2 How Intercom Cut $250K/Month by Ditching GPT for Qwen Fergal Reid, Intercom Intercom was spending $250K a month on one summarization task and replaced it with a fine-tuned 14B Qwen model. Fergal Reid walks the whole decision — the most concrete open-weights-in-production case the show has.
- 3 AMD's Challenge to NVIDIA: The Open Ecosystem Bet | Anush Elangovan & Sharon Zhou Anush Elangovan & Sharon Zhou AMD’s Anush Elangovan and Sharon Zhou on betting a silicon roadmap against CUDA lock-in, and what it takes to make community contribution a real path instead of a press release.
- 4 AI, Open Source & Developer Safety | Block’s Rizel Scarlett Rizel Scarlett, Block Block’s Rizel Scarlett on Goose, the on-machine open source agent her team shipped, and how open source development and developer safety pull on each other.
- 5 The State of AI: Open-Source Models & Enterprise Trust | May Habib May Habib, Writer The show’s first episode, which framed open versus proprietary as a question about enterprise trust rather than benchmarks — with Writer CEO May Habib on deploying generative AI at scale.
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