Tailscale's Remy Guercio on the shift from token maxing to ROI maxing
Blog post from WorkOS
At the AI Engineer World's Fair 2026, Michael Grinich discussed the evolving landscape of AI expenditure with Remy Guercio from Tailscale, focusing on the shift from "token maxing" to "ROI maxing" in AI projects. Remy highlighted the financial implications of utilizing large context windows in AI models, emphasizing that while this exploration has been productive, it has also led to significant costs, prompting finance teams to scrutinize AI bills from various providers like OpenAI and Anthropic. He used the Concorde analogy to illustrate that efficiency should be measured per task rather than per token, as cheaper tokens don't necessarily equate to cheaper tasks. Aperture, Tailscale’s AI gateway, was introduced as a solution to monitor and manage AI model usage and costs, providing insights into average costs per million tokens and facilitating governance by tracking agent activities and stripping PII. Remy cautioned against consolidating AI services with one provider, advocating for diverse experimentation across models to ensure cost-effectiveness and performance verification. He noted the cultural shift within Tailscale, where AI has enabled engineers to explore multiple approaches, leading to potentially better software development. The discussion also touched on the broader theme of token allocation akin to capital allocation, underscoring the importance of thoughtful AI usage in balancing costs and innovation.
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