Token Town (why compute strategy is product strategy)
Token pricing is a noisy headline. What matters in production is what you pay per task once outputs get longer, retries creep in, and “good enough” models get deprecated.
This talk breaks down the current dynamics of the frontier model market from the perspective of Notion AI product team on embarking this with Notion custom agents model, and shares a practical playbook for keeping leverage: stay genuinely multi-provider, invest in product value that is hard to undercut, and use open weight models as an escape hatch for everyday workloads that do not need frontier reasoning.
Sarah Sachs
Sarah Sachs is an engineering leader focused on shipping practical, high-leverage AI into real products at scale. Currently leading AI Modeling at Notion, she oversees four core areas of the company’s modeling efforts: Reasoning and Agentic Orchestration, Core Model Engineering, Search and Ranking, and Data Specialists & Evals — driving the next generation of Notion AI across reasoning, retrieval, and end-to-end drafting and editing.
Before Notion, Sarah was Director of Engineering for AI and Infrastructure at Tome, where she led AI features reaching 18 million users, built end-to-end presentation generation, and owned the OpenAI partnership and model infrastructure. Prior to that she spent three years at Robinhood as Head of NLP & GenAI, setting company-wide generative AI strategy, transitioning a BERT-powered chatbot into a compliant generative assistant, and building NLP content moderation for a regulated fintech environment. Earlier in her career she was a founding ML engineer at Sunshine (formerly Lumi Labs) and a software engineer at Google, where she launched and patented Personal Score in Google Maps, featured at Google I/O 2018. Sarah holds a Sc.B. in Applied Mathematics–Computer Science from Brown University, graduating with a 4.0 CS GPA and the University Distinguished Thesis Award.