Snapshot · This Week in Tech (Audio)
OpenAI's single $122 billion raise is the largest in history, insulating it from cash concerns even as operating costs for training frontier models remain enormous.
Where this was said
At 43:49 · chapter starts 39:50
The central topic of the episode arrives in full force: a wave of Chinese frontier AI models that are closing the gap with the best American closed models. Leo describes Kimi K3 as 'almost — not quite, but almost — Fable quality,' built entirely on 100,000 Huawei chips with no NVIDIA hardware. Kimi's subscription sold out immediately — a move Harper Reed compares to the classic T-shirt marketing trick of doing a small run to generate hype. Alex Wilhelm pushes back slightly, noting that Kimi K3 is not actually cheap to run, and that at current pricing it looks similar to a mid-tier American model. Harper uses GLM as his point of comparison: he was using Claude Code in early 2025 when it was still rough, and today's GLM is at least as capable as that early version — effectively making it a 6-month-behind Claude for free. The Toyota Corolla analogy emerges: it's not whether the model is the best, it's whether it's good enough and the price is rational.
When the US government and Anthropic pulled Fable access, it didn't just inconvenience users — it broke trust and sent developers experimenting with alternatives. OpenAI made it worse by publishing a guide to using Sol inside Claude Code. Once users discovered the models were interchangeable, Anthropic's lock-in evaporated.
Claude Fable costs ~$10/M input tokens and $50/M output tokens — a premium that Chinese open-weight models threaten to make untenable.
Anthropic is buying compute from xAI at ~$1B/month, illustrating how demand for frontier AI inference is outpacing what any single company can build alone.
China's open-weight models aren't just catching up — they're on track to make billion-dollar American AI labs economically unviable. Once DeepSeek-style models become free to run anywhere in the world, the pricing power of Anthropic and OpenAI collapses, and with it the incentive to fund AGI.
Sam built Algrow from zero to $14,000 in monthly revenue within just six months of shipping his first MVP.
Algrow reached over 10,000 users in roughly six months, driven almost entirely by organic Discord community growth.
Sam acquired his first 400 users entirely through Discord communities, without paid advertising or traditional outreach.
Algrow added exactly 480 new paying customers in its most recent month, demonstrating strong ongoing growth.
Sam's Stripe dashboard showed over £10,000 in revenue in the last four weeks, equivalent to roughly $13,000–$14,000 USD.
Sam gave all early users free access so they could show the tool to friends, turning them into live demos and advocates who helped the product spread virally.
By silently screen-sharing his tool in Discord voice chats rather than posting links, Sam attracted curiosity without violating no-self-promo server rules.
Before building Algrow, Sam and two friends made over $10,000 in revenue through affiliate marketing for RizzApp by posting faceless texting story content.
Bhanu grew SiteGPT to $13,000 monthly recurring revenue entirely through organic channels, spending nothing on paid marketing.
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