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Jamie Cuffe
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Jamie Cuffe
@jamiecuffe
Building @pacecom: The AI operations partner for insurance · Past @retool, cheer (acq by retool), @sequoia
New York, NY
withpace.com
Joined October 2012
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    Jamie Cuffe
    @jamiecuffe
    May 27
    Today, Pace has raised a $46 million Series B, co-led by @ThriveCapital and @sequoia, with participation from @emergencecap and @pruvencapital, to help our customers insure more of the world’s risk. @pacecom agents have completed more than 250,000 critical insurance operations,
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    Jamie Cuffe
    @jamiecuffe
    Jul 30
    As models become increasingly better at computer use, we've spent a lot of time thinking through the optimal architecture for a harness to best leverage these capabilities. @aryanjn9 wrote about how we've built a 30x cost effective computer use harness that maintains a 94%
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    Jamie Cuffe
    @jamiecuffe
    Jul 22
    Such a blast recounting stories with @ryanjdaniels from the early days. The momentum at @crosbylegal is palpable and built by creating happy customers everyday. It was special to see how far both teams have come in shaping this new era of AI-native services. Even more to come in
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    Ryan Daniels
    Crosby
    @ryanjdaniels
    Jul 22
    2 years almost to the day, @jamiecuffe and I started working out of the same office. We sat side-by-side for another 6 months. I watched him pull an all-nighter to launch @pacecom's first client, we competed for many early hires. Most important, we pushed each other to think
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    Jamie Cuffe
    @jamiecuffe
    Jul 21
    After deploying into the world's largest insurers, we've realized that FDEs are essential but need to be complemented with a great product. FDEs are invaluable: they build customer trust, deeply understand a customer's operations, and build reliable agents to automate complex
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    Jamie Cuffe
    @jamiecuffe
    Jul 18
    We're growing the research team at Pace. The project I'm most excited about right now is a new product we're building with Anthropic for some of the largest insurers in the world. The ideal fit is an engineer who loves backtesting ideas against massive datasets, building

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