Damian McCabe

Today we announced that we have acquired @call_hyper, a leader in conversational, agentic AI designed to reduce the burden on understaffed public safety answering points by handling non-emergency calls. Welcome to the team, Hyper! Read the press release: bit.ly/4dBG4QD

For this episode of Uncapped I got to sit down with my close friend @Max, cofounder of Instacart 🥕 We talked about the key moments of Instacart...how it got started, critical wins, tough losses, competitive dynamics, earned insights, going public, and Instacart's future. Max is also an awesome startup investor, and we talked about what he looks for in founders, consumer investing, and what he's building with Workshop. He's one of the best people I know, hope you enjoy. (0:00) Intro (0:36) The inception of Instacart (4:55) Finding product market fit (7:20) Landing Trader Joe’s (11:04) Big levers for growth (13:36) Operationally complex businesses (14:55) Amazon’s acquisition of Whole Foods (17:50) COVID and Instacart’s IPO (20:02) Prioritizing profitability (23:21) Avoiding temptations (24:59) The future of Instacart (25:53) Investing in consumer (28:21) Irrationally optimistic founders (29:49) B2B vs consumer founders (30:35) How to work with investors (33:38) Building Workshop

Today, it was announced that @EniacVC portfolio company @call_hyper has been acquired by Motorola Solutions (NYSE: MSI). @8ENs previously co-founded Clearco, which reached a $2B valuation and became one of Canada's most prominent fintech unicorns. He also ran for federal office in Canada — against the same Congressman he used to bring water to as a teenage Page in the Canadian House of Representatives back in 2001. His co-founder @DamianMcCabe built and scaled Connected to 200 people before ThoughtWorks acquired it, after product leadership roles at Xtremelabs (part of the original @sundeep and @avarma mafia!), Uber, Meta, and Instagram. But what made us say yes wasn't the resume — it was the mission. Ben wanted to be a cop as a kid. He literally had his mom sew yellow stripes on navy sweatpants so he could wear the uniform. His whole career has been building at the intersection of tech and public safety. When he read that his hometown was looking to use AI to reduce 911 wait times, he dropped everything. That's founder-market fit you can't fake. From a cobbled-together prototype in fall 2023, to their first live 911 call in December 2024, to being acquired by the global leader in public safety communications — in under 3 years. Hyper's voice AI handles up to 75% of non-emergency 911 calls autonomously, reclaiming capacity for real emergencies at a time when most PSAPs are staffed at only 75%. Now that technology will reach every corner of the country through Motorola's Command Center portfolio. Congrats Ben Sanders, Damian McCabe, and the entire Hyper team. You built something that literally saves lives. Proud to have had your backs from day one and (after you take a weekend off), very excited for your next chapter! 🚀 PS- thank you @boardyai for the original introduction to Ben!

ANNOUNCEMENT: We've built a coding agent that beats Claude Code on long tasks. Today we're releasing it for free. Meet Volt: The coding agent who never forgets. → Dominates Claude Code on the OOLONG long-context benchmark, including at every length from 32K to 1M tokens. → Has unlimited recall. No more amnesia. Volt can code for weeks in a single coherent session. → Massively parallel. One tool call can process thousands of tasks. Like "Map" for LLMs. → Open source and model agnostic. Try Volt today with @openrouter or your API of choice. Volt's performance is the result of a new architecture, Lossless Context Management (LCM), which applies lessons from the history of operating systems and programming languages to LLMs. LCM is like paged virtual memory, except for managing context: - Layer 1. An immutable append-only store of everything that occurs in the coding session. - Layer 2. The active "context window" which functions like a cache layer for navigating to the appropriate section(s) of Layer 1 via a high-fanout DAG. From a user perspective, this feels like an infinite context window, because the model never forgets and performance stays crisp. For the technical details, read our paper: papers.voltropy.com/LCM For the code, go to github.com/voltropy/volt. Or get started with one line: curl -fsSL voltropy.com/install | sh