I think the days of companies relying only on frontier models are coming to an end. 1. Tokenmaxxing at frontier-model API prices makes no sense. Uber burned through its entire 2026 AI budget in 4 months, Microsoft moved engineers off Claude Code due to cost, and companies are realizing that running everything on frontier models can get expensive fast. Tokenmaxxing makes sense when you’re on a subsidized $200/month plan, but it’s unsustainable at API rates. 2. Companies will rely on a portfolio of models. Coinbase recently cut its AI spend nearly in half by switching engineers to Chinese open-source models like GLM and Kimi. Airbnb and Pinterest have done the same with Alibaba’s Qwen models. I believe this will be the default path forward: using frontier models for high-stakes work and cheaper models for everything else. 3. China’s open-source strategy is working. Chinese models are taking market share from frontier models at US companies. China is also building the full AI stack, from energy, like solar and nuclear, to data centers to domestic chips. The Chinese government is planning a $295B investment in AI data centers, with at least 80% of chips built domestically. 4. Frontier labs are in a Catch-22 situation. If they release great open-source models, they might undercut their own frontier API revenue. If they gate the best models behind a trusted list, companies will just lean on open alternatives more. The last major US open-source model was OpenAI’s gpt-oss series back in August 2025, which already feels like decades ago in the AI space. 5. The US needs to think about its AI strategy holistically. I believe restricting access to frontier models will only hurt American innovation. Banning US companies from using Chinese models won’t work either. Just look at how China took over the global electric vehicle market. To maintain our edge, we need the best closed and open models while scaling our energy grid and data centers much faster. 📌 More in my recent essay: