AI’s biggest gains will come from networks of models arranged as agents inside rules, protocols, and institutions rather than from ever‑bigger solitary models. Products are the institutionalized glue that turn raw model capabilities into durable real‑world value.
— This reframes AI policy and investment: regulators, companies, and educators should focus on protocols, governance, and product design for multi‑agent systems, not only model scaling.
BeauHD
2026.01.07
92% relevant
Cherny’s account is a direct, operational example of the idea that value comes from networks of models arranged as agents inside product workflows: he runs multiple Claudes in parallel, hands off context ('teleport'), and uses verification loops and shared memory — exactly the multi‑agent, productized workflow the existing idea predicts.
Anish J. Bhave
2025.12.03
88% relevant
The article argues explicitly for 'trusted AI agents' operating inside shop‑floor institutions to enforce quality, safety and supervision — a direct instantiation of the existing idea that AI’s biggest gains come from networks of agents embedded in institutional rules and protocols; the Sambhajinagar family‑factory example is the operational case.
Tyler Cowen
2025.12.02
100% relevant
Tyler Cowen quotes Séb Krier stating most transformative change will come from products and organised multi‑agent systems, not a single genius model.
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