Pada si Iroyin
Ile-iṣẹAI Understanding finifini

Brian Chesky jiyan awọn aṣoju AI nilo ẹrọ iṣẹ ti a ṣe iyasọtọ

Alakoso Airbnb Brian Chesky jiyan pe awọn aṣoju AI lọwọlọwọ kuna lati pese iriri iṣọpọ nitori wọn ko ni ẹrọ ṣiṣe ipilẹ, ni iyanju pe awọn ohun elo gbọdọ dagbasoke sinu awọn aṣoju interoperable.

4 min readRead the original reporting
Source-provided image accompanying Brian Chesky argues AI agents require a dedicated operating system
Ijabọ iroyinOrisun ti o gbasilẹ
Olutẹwe
techcrunch.com
Orisun ọna asopọ
techcrunch.comhttps://techcrunch.com/2026/10/01/brian-chesky-interview-ai-agents-need-their-own-operating-system/
Orisun iru
Ijabọ nipasẹ ijade iroyin kan - kii ṣe iwe-ipamọ ẹgbẹ akọkọ.

Ohun ti a ko le jẹrisi ni ominira: Ibeere yii jẹ ikasi si iṣan ti a npè ni. A ko jẹrisi rẹ lodi si iwe-ipamọ ẹgbẹ akọkọ. (techcrunch.com)

AtokọLoye eyi ni iṣẹju 60

Bẹrẹ nibi

Awọn ofin bọtini

MCP (Awoṣe Ilana Ilana ọrọ)
Ilana ti o ṣii ti o jẹ ki awọn ohun elo AI sopọ si awọn irinṣẹ ita, awọn orisun data, ati awọn olupese agbegbe ni ọna boṣewa.
AI Aṣẹ̀dá
Awọn eto AI ti o gbejade akoonu titun gẹgẹbi ọrọ, awọn aworan, ohun, fidio, tabi koodu.
Ẹya ara ẹrọ
Oniyipada igbewọle ti a lo nipasẹ awoṣe lati ṣe awọn asọtẹlẹ.
Ṣe idanwo fun ara rẹAI Aṣoju adanwo

Kini o ṣẹlẹ

Airbnb CEO Brian Chesky stated in a TechCrunch interview that the current consumer AI landscape is failing because it lacks a dedicated operating system. Chesky argued that existing AI agents, such as Muse and Instinct, struggle to interact effectively with platforms like Airbnb because they lack a robust software developer kit (SDK) and kernel-level integration. He proposed that for AI to reach its potential, apps must transition into 'agentic' forms that are inherently interoperable, rather than relying on current chatbot interfaces that he believes are ill-suited for complex e-commerce and travel discovery.

In an interview with TechCrunch, Brian Chesky expressed skepticism regarding the current state of consumer AI, noting that his own experiences using agents like Muse and Instinct to book travel have been suboptimal. He argued that these tools lack the necessary software infrastructure to handle the nuances of platforms like Airbnb, which require complex features such as map integration, identity verification, and host messaging.

Chesky emphasized that the industry is currently missing a true 'AI operating system' that would allow components and agents to interact at the kernel level. He criticized the lack of a comprehensive SDK for AI agents, comparing the current state of AI development unfavorably to the early days of the App Store, which provided the necessary framework for developers to build functional, interoperable software.

The CEO outlined a vision where the Airbnb app itself evolves into an agent, with specific agents handling tasks like exploration and customer service. He suggested that these internal agents would eventually become interoperable with external agents through standards like MCP, effectively turning apps into 'apps with faces' that can communicate autonomously to complete user requests.

Awọn alaye orisun: techcrunch.com ↗

Kini idi ti o ṣe pataki

Chesky’s critique highlights a significant friction point in the current AI industry: the lack of standardization for agent-to-agent communication. By calling for an 'AI operating system' rather than just a 'quarterback' agent, he identifies a structural limitation that prevents AI from seamlessly navigating complex, multi-step tasks across different platforms. This perspective challenges the prevailing Silicon Valley trend of building standalone chatbots, suggesting instead that the future of consumer AI depends on deeper, system-level integration that allows apps to function as interoperable agents. His comments underscore the ongoing struggle to move beyond simple text-based interactions toward functional, agent-driven workflows.

The core of Chesky’s argument is that the current 'chatbot' paradigm is a poor fit for e-commerce and travel, where users value browsing, inspiration, and collaborative planning. He believes that by forcing users into a linear, turn-based chat interface, companies are stripping away the 'library experience' of travel planning.

By advocating for an operating system approach, Chesky is highlighting the need for a shift from 'apps as data layers' to 'apps as agents.' This shift would theoretically allow for a more fluid user experience where an agent can perform tasks across multiple platforms without the user needing to manually switch between disparate applications.

The interview also touches on the role of design, with Chesky asserting that human designers are still better at creating intuitive interfaces than models. He suggests that the future of AI interfaces will be a hybrid of deterministic, pre-designed elements and generative components, rather than a total abandonment of traditional UI.

Interactive Mechanism

Ibaraẹnisọrọ Mechanism: Bii O Ṣe Nṣiṣẹ Lootọ

Ṣawari imọ-ẹrọ abẹlẹ lẹhin idagbasoke yii ni ibaraenisọrọ.

Agent Lifecycle Stage:
1
User Intent & Planning: "Audit customer refund request #4092 and settle payment."
2
Tool Calling: Emits structured JSON call crm_get_transaction(id='4092').
3
Guardrail & Verification:🛡️ Paused: High-value action requires human operator sign-off.
4
Final Settlement: Refund recorded, email receipt dispatched, and audit log stored.
Core takeaway: An AI agent is not just a language model—it is a closed loop of planning, tool invocation, and environment feedback. Production systems require self-healing retries and strict human approval guardrails.
Ibanisọrọ Erongba Ṣayẹwo+10 Points
AI Agents Quiz

An agent must create a draft calendar event for Tuesday at 2 p.m. Which evidence would establish the requested result?

Kini lati wo tókàn

Airbnb plans to roll out voice-enabled agents this fall to assist with search and customer service. Additionally, the company is exploring 'multiplayer' AI interfaces designed for group trip planning, moving away from the single-user chatbot model. Observers should monitor whether Airbnb’s push for agent-friendly infrastructure and interoperability standards, such as the Model Context Protocol (MCP), gains traction with other major platforms or if the industry remains fragmented by competing 'quarterback' agent models.

Airbnb is actively developing 'multiplayer' AI, which aims to support group collaboration—a Chesky identifies as a major weakness in current single-user AI agents.

The company is preparing to launch voice agents this fall, which Chesky believes will eventually become the primary way users interact with computers, surpassing typing.

The industry's reliance on Apple and Google platforms remains a critical factor. Chesky noted that unless these platform holders build a new, agent-centric OS, the industry will likely remain stuck with 'apps that have agents inside them' rather than achieving a true transition to a universal agent ecosystem.

Awọn itọsọna ti o jọmọ & awọn ibeere

Awọn aṣoju AIỌjọ́ Iwájú AIAwọn awoṣe AI ti ṣalayeṢe idanwo ohun ti o mọ — gbiyanju idanwo AI ọfẹ kanWa ọrọ AI kan ninu iwe-itumọ waTẹle olutọpa igbeowosile AI
Ṣe eyi wulo?