OpenAI is flooding the zone with verticalized how-to content and use-case libraries rather than announcing new model capabilities or research breakthroughs. Six of seven announcements are essentially tutorials on deploying existing products across specific workflows, custom GPTs for automation, ChatGPT for customer success teams, research and data analysis modules, financial services integration guides. This is the work of a company that has already won the base model competition and is now optimizing for adoption depth and enterprise stickiness. The financial services vertical gets its own resource bundle, a signal that OpenAI sees regulated industries as both high-value and requiring pre-packaged compliance scaffolding. Meanwhile, GitHub's Copilot CLI beginner guide sits in the same announcement cycle, reinforcing that the coding productivity layer is no longer novel enough to warrant standalone emphasis, it is now infrastructure, documented like any other developer tool. The pattern across both companies is identical: lock in usage through verticalization, documentation, and ease of deployment. Nobody is announcing breakthroughs. Everyone is announcing how to spend more money with them.
Sloane Duvall
A curated reference of models from major AI labs, with open/closed weight status, input modalities, and context window size. American labs tend towards closed weights models and Chinese labs tend toward open weights models.
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