Every 📧
6.3K posts

Every 📧
@every
The only subscription you need to stay at the edge of AI. Ideas and apps: @TrySpiral @CoraComputer @SparkleApp @usemonologue

We use OpenClaws to do all of our work at @every. We have 25 full-time employees, so we’re one of the few companies in the world that has seen how work changes when everyone has their own personal agent in the company Slack. I chatted with @every COO Brandon (@bran_don_gell) and @every head of platform Willie (@bigwilliestyle) to share what we’ve learned. We get into: - Why agents become mirrors of their owners, and how that influences how other people on the team interact with them - How a parallel AI org chart forms on its own. People have stopped tagging me on Slack with questions about Proof, the document editor I vibe coded, because they knew my agent R2-C2 can step in - The etiquette for human-agent collaboration is being invented in real time. Brandon's rule is that if there's an established process or documented answer, always ask the agent, not their human - Why everyone is a manager now, and why even experienced managers carry limiting beliefs about what their agents can do - This is a must-watch for anyone trying to understand how AI workers change daily operations, not just in theory, but inside a company that’s half-agent Watch below! Timestamps Introduction: How Brandon built Zosia, an AI agent to run his household: Brandon’s “aha” moment: What happened when everyone on the team got their own agent: How agents take on their owners' personalities, and why that matters inside an org: Why it’s important for agents to work in public: What we’re still figuring out when it comes to agent behavior, including memory gaps, group chat etiquette, and the "ant death spiral" problem: How we built Plus One, our hosted OpenClaw product: The cultural shift required to make agents work at scale:





we just opened up 5 new roles @every: - GTM engineer - Head of Finance Vertical, Consulting - Head of Learning and Development - Head of Product Marketing - Head of Social if you want to help discover and define how the world works with agents over the next 10 years—join us: every.to/careers







we just opened up 5 new roles @every: - GTM engineer - Head of Finance Vertical, Consulting - Head of Learning and Development - Head of Product Marketing - Head of Social if you want to help discover and define how the world works with agents over the next 10 years—join us: every.to/careers




SaaS isn’t dead, it just needs to become agent-native. Linear (@linear) is a great example of how: They pivoted the product to be used by both humans and agents, and that has made them one of the premier software tools in the agent-native era. I had Linear’s cofounder and CEO @karrisaarinen on @every's AI & I to talk about how a product management tool for human software developers became an agent-native tool—and how Linear’s trajectory reveals a bright future for SaaS businesses: - Speed means decisions matter more, not less. AI makes it easy to have an idea and build it without considering whether its existence is justified. When ChatGPT was released, SaaS companies were launching their own chatbots left, right, and center. Instead of jumping on the bandwagon, Linear stopped to consider whether the application was useful. (It wasn’t.) - Just because the technology has changed doesn’t mean your mission should. Karri attributes Linear’s success to never losing sight of what matters: helping teams develop great software. Instead of chasing trends, Linear focused on understanding how AI was impacting its customers’ workflows—and updating its product accordingly. - Agents are now first-class users. Linear never tried to change what it was or did well; it just expanded the user base. Companies can now kick off agents inside Linear, manage them, and track what they're working on alongside the humans on the team, which explains why Codex, Coinbase, and Brex all run their agents on Linear. This is a must watch for anyone interested in how an agent-native SaaS company operates. Watch below! Timestamps: Introduction and how Every first discovered Linear: 00:00:39 Why Linear waited to ship AI features instead of rushing to chatbots: 00:02:00 Linear's agent platform and becoming the system that guides AI agents: 00:05:06 Why "SaaS is dead" is a simplistic narrative: 00:07:42 How Linear adopted AI coding tools internally: 00:12:18 AI's impact on product building workflows—speed versus thoughtfulness: 00:17:45 The value of conceptual work and thinking before shipping: 00:22:18 How AI is reshaping Linear's product strategy: 00:29:30 Demo: Linear's agent skills, shared context, and code review workflow: 00:37:18 The future of product development and the enduring role of human judgment: 00:47:48




