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AI 资讯

Eric Wu’s newest company, out of stealth since May, is going after construction’s labor crunch

Eric Wu, who built and ran Opendoor before stepping away in 2022, has had his new company, NavigateAI, out of stealth since May — building AI copilots that give construction workers real-time, hands-free guidance through smartphones and Meta's AI glasses, backed by $25 million from Elad Gil, Khosla Ventures, and Lennar to tackle a labor shortage severe enough that data center projects alone now need 4,000 to 5,000 workers apiece.

2026-09-08 原文 →
AI 资讯

You Aren't Choosing an AI Tool. You're Choosing Who Gets Paged at 2 AM.

Part of AI Leadership in the Real World — how leaders turn scattered pilots into governed, adopted, measurable capability. TLDR: A support agent doing 50,000 chats a month needs ~3.5 FTE and $500k+/year just to stay accurate — while a typical 100-seat Copilot rollout sees only 20-30 seats used weekly. For SMBs, build-vs-buy isn't about features. It's about what you can afford to own for 24 months. We thought we were choosing a tool. We were really choosing a future dependency, a support queue, a governance burden, and a second bill that arrives a year later. Every vendor demo promised acceleration, control, and simplicity at once. Every internal proposal promised flexibility, ownership, and leverage. Nobody said both bills arrive late — one in engineering on-call, the other in consumption meters. Good platform decisions feel a little boring at first and very smart a year later. Why AI is special (and why old build-vs-buy math breaks) Traditional software mostly stays still when you leave it alone. AI doesn't: It drifts. Knowledge changes, customer language shifts, users ask harder questions once they trust it. Accuracy quietly drops from 90% to 70% with no error log. It speaks for you — legally. A wrong Confluence page is embarrassing. A wrong chatbot answer is a commitment a tribunal can enforce. It lives on someone else's deprecation clock. OpenAI gives at least 6 months before retiring a GA model. That's a hard deadline, not a backlog item. Prompts, evals, and output parsers all need rework. It multiplies cost per request. One human click = one action. One agent resolution = 6 lookups, drafts, updates, and logs — each potentially metered. It turns connectors into permanent work. Salesforce, SharePoint, Jira, Zendesk all change auth, rate limits, and APIs. Your agent keeps running while its knowledge goes stale. Gartner predicts 40%+ of agentic AI projects will be canceled by end of 2027 on cost, unclear value, and weak risk controls. McKinsey's State of AI 2025 (

2026-09-07 原文 →
AI 资讯

The Moto Watch Ultra is a return to Wear OS

Just a few months after getting back into the smartwatch game, Motorola is targeting the premium end of the market with the first Moto Watch Ultra. It comes with some upgrades from the recent Moto Watch - most obviously the jump to Wear OS - but lacks the outdoorsy features that would make it a […]

2026-09-04 原文 →
开发者

Volunteer at TechCrunch Founder Summit in Boston

Our rebranded Boston event, TechCrunch Founder Summit (formerly All Stage), is back on November 4th! And we are looking for some incredible volunteers to help us make this event happen. If you are interested in finding out what goes into building tech events, apply to volunteer. If you are selected, not only will you get […]

2026-09-03 原文 →
AI 资讯

What is DevOps? A Plain English Guide

Ever Wondered How Netflix Never Seems to Go Down? Think about this for a second. Netflix has over 260 million subscribers worldwide. People are watching shows in Tokyo, London, Lagos, and New York — all at the same time. And yet, when was the last time Netflix crashed on you? Now think about your favourite food delivery app. You open it, order food, track your driver in real time, and get a notification the moment your burger arrives. All of that happens in seconds. Behind all of this is a way of working called DevOps. And by the end of this article, you'll understand exactly what it is — no jargon, no complicated diagrams, just plain English. The Old Way (And Why It Was a Nightmare) To understand DevOps, we first need to understand the problem it solved. Imagine a software company in the early 2000s. They had two completely separate teams: The Developers — the people who wrote the code and built new features The Operations team — the people who managed the servers and kept everything running These two teams barely talked to each other. Developers would spend months building new features, then hand over a massive pile of code to the operations team and say "here you go, make it work." The operations team would panic. They hadn't been involved in building it, had no idea what it did, and now they had to deploy it to millions of users without breaking anything. The result? Deployments took weeks. Bugs slipped through. Systems crashed. Customers complained. And the two teams blamed each other. Sound stressful? It was. So What is DevOps? DevOps is simply the practice of bringing developers and operations teams together to build, test, and release software faster and more reliably. The name itself is a combination of Dev (Development) and Ops (Operations). Instead of two teams working in silos, they work as one team with shared goals, shared tools, and shared responsibility. Think of it like a restaurant kitchen. In a badly run kitchen, the chefs cook the food and just s

2026-09-02 原文 →