惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

爱范儿
爱范儿
WordPress大学
WordPress大学
C
Check Point Blog
GbyAI
GbyAI
U
Unit 42
Google DeepMind News
Google DeepMind News
B
Blog RSS Feed
Blog — PlanetScale
Blog — PlanetScale
J
Java Code Geeks
I
InfoQ
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Hugging Face - Blog
Hugging Face - Blog
Vercel News
Vercel News
博客园 - 【当耐特】
美团技术团队
小众软件
小众软件
S
SegmentFault 最新的问题
Jina AI
Jina AI
阮一峰的网络日志
阮一峰的网络日志
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
The Cloudflare Blog
Last Week in AI
Last Week in AI
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
V
Visual Studio Blog

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
Orchestrating the Future with the Agentic Enterprise
Diego Martin · 2026-04-30 · via DEV Community

Diego Martinez L.

Google Cloud NEXT '26 Challenge Submission

This is a submission for the Google Cloud NEXT Writing Challenge

The landscape of Artificial Intelligence has shifted. We have moved past the era of simple AI chatbots that merely answer questions to the dawn of AI Agents that achieve goals. At Google Cloud NEXT, the vision of the "Agentic Enterprise" was unveiled—a future where every employee becomes a director of a boundless autonomous workforce. The core of this transformation lies in bridging the gap between the promise of AI and the daily reality of enterprise complexity.

The Three Pillars of an AI Agent

To understand this shift, we must define what makes an agent truly "agentic." Unlike traditional LLMs, an enterprise agent requires three core capabilities:

  • Context: A deep understanding of unique business information and workflows.
  • Reasoning: The ability to break down complex, multi-step goals into actionable plans.
  • Orchestration: The power to act across different tools and systems to get the job done.

Unified Intelligence: Workspace and Gemini Enterprise

The most significant takeaway from the session is the integration of Workspace Intelligence and Gemini Enterprise.

  • Workspace Intelligence turns scattered emails, chats, and files into a cohesive "Knowledge Graph," providing the real-time context of daily collaboration.
  • Gemini Enterprise acts as the organization's central nervous system, connecting this human context with structured data from CRMs, ERPs, and even third-party platforms like Microsoft 365.

Key Innovations for the Modern Workforce

Several groundbreaking tools were introduced to facilitate this new way of working:

  • Enhanced Agent Designer: A no-code interface that allows anyone to build sophisticated agents using natural language, blending generative creativity with deterministic business logic.
  • Long-Running Agents: These autonomous nodes can operate for hours or days in secure sandboxes, handling mission-critical tasks without constant human supervision.
  • Gemini Projects & Shared Chats: Transitioning AI from a private assistant to a "multiplayer" experience, where teams and agents co-create in a shared, transparent environment.

Trust and Sovereignty: Turning Shadow AI into Managed AI

For the enterprise, power without control is a liability. Google Cloud addresses this through a robust governance framework:

  • Agent Identity: Enforcing the principle of least privilege for every digital worker.
  • Agent Registry & Gateway: Providing IT teams with total visibility and centralized management of every agent in the ecosystem.
  • Data Sovereignty: Ensuring that "your data is your data." Google guarantees that enterprise information is never used to train global models or viewed by humans without explicit permission.

Conclusion: From Managing Tasks to Directing Outcomes

The "Google Cloud NEXT Writing Challenge" highlights a fundamental truth: the tools we choose today define how we innovate tomorrow. By leveraging an open ecosystem—supported by partners like ServiceNow and Oracle—Google is not just adding AI to existing apps; it is building a new foundation for work. We are no longer just doing work; we are directing it.