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

雷峰网
雷峰网
B
Blog
博客园_首页
云风的 BLOG
云风的 BLOG
S
SegmentFault 最新的问题
罗磊的独立博客
Jina AI
Jina AI
C
Check Point Blog
Martin Fowler
Martin Fowler
J
Java Code Geeks
博客园 - 司徒正美
美团技术团队
MongoDB | Blog
MongoDB | Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
大猫的无限游戏
大猫的无限游戏
有赞技术团队
有赞技术团队
U
Unit 42
Hugging Face - Blog
Hugging Face - Blog
WordPress大学
WordPress大学
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
博客园 - 叶小钗
博客园 - 三生石上(FineUI控件)
小众软件
小众软件

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
AI Agents Can Do a Lot. But Should They?
Anish Shirod · 2026-05-09 · via DEV Community

Most conversations about AI agents focus on what they can do.
Very few focus on what they should be allowed to do.

That gap is what I kept thinking about when I built Vouch for
the Auth0 "Authorized to Act" hackathon.

The Problem:

AI agents are getting good at taking actions: booking meetings,
calling APIs, sending emails, managing files. But the current
delegation models are broken. You either leak credentials in
prompts, which is dangerous, or you hand the agent broad OAuth
access and hope it stays in its lane, which is just risky in a
different way.

There is no clean way to say: this agent can do X on service A,
for user B, until this session ends. Nothing more. That missing
primitive is the whole problem.

How Vouch Works:

Vouch sits between the agent and the services it wants to interact
with. Instead of giving the agent raw credentials, you define a
permission scope for each action. The agent operates within that
scope and nothing outside it.

The credential delegation runs through Auth0 Token Vault. When a
user authorizes an action, Vouch generates a scoped token tied to
that specific permission. The agent uses the token to act. It
never sees the underlying credentials. When the session ends,
access is revoked.

The agent brain is Llama 3.3 70B running through Groq's API.
Backend is Node.js and Express, frontend is React and Vite.
Built the whole thing in 48 hours.

The Hard Part:

The auth flow was not the challenge. The permission schema was.

Too broad and the whole point falls apart. Too narrow and the
agent becomes useless. I went through three complete redesigns
before landing on something that felt both flexible and actually
enforceable. That balance took most of the 48 hours.

The Takeaway:

Capability gets all the attention. Constraint gets almost none.
As agents get more capable, the trust problem gets harder, not
easier. An agent that can browse the web, write code, and send
emails on your behalf needs a much more sophisticated permission
model than anything running in production today.

Scoped delegation with session-bound tokens is not the final
answer. But I think it is the right direction.

Live: vouch-q017.onrender.com
GitHub: github.com/Anish0104/vouch

If you are building in the agentic space, how are you handling
permissioning? Would love to hear how others are defining trust
in their stack.

AgenticAI #MachineLearning #Auth0 #LLMs #BuildInPublic