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

腾讯CDC
Microsoft Azure Blog
Microsoft Azure Blog
L
LangChain Blog
Y
Y Combinator Blog
Microsoft Security Blog
Microsoft Security Blog
宝玉的分享
宝玉的分享
B
Blog RSS Feed
MongoDB | Blog
MongoDB | Blog
Jina AI
Jina AI
D
Docker
B
Blog
Engineering at Meta
Engineering at Meta
Last Week in AI
Last Week in AI
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
I
InfoQ
G
Google Developers Blog
博客园 - Franky
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
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 GitHub Blog
The GitHub Blog
T
The Blog of Author Tim Ferriss
大猫的无限游戏
大猫的无限游戏
阮一峰的网络日志
阮一峰的网络日志
U
Unit 42

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
Stop Building AI Assistants. Build AI Firewalls.
yongrean · 2026-05-28 · via DEV Community

yongrean

Every week another "AI agent for X" launches. Email triage. Calendar coordination. Sales follow-up. PR reviewer. Slack monitor. Meeting summarizer.

I've installed enough of them to see the pattern. Here's the dirty secret nobody mentions in the launch posts:

These tools don't reduce your work. They multiply your notifications.

Each AI tool is configured to be helpful by default. "Helpful" means: "I noticed this thing — here's a notification." Stack a dozen of those, and instead of one inbox to ignore you have twelve. The signal-to-noise ratio gets worse every time you add an AI to your workflow.

The mainstream answer is "just configure each one." Sure. Spend four hours tuning notification settings every time you add a tool, and another four hours when one of them ships a "smarter notifications" update. That's not productivity. That's notification janitorial work disguised as setup.

This is a structural problem. Not a configuration problem.

The wrong question

Every AI tool asks the same thing: "Is this important?"

Wrong question. There is no objective "important." Importance depends on you, right now. A Stripe webhook is important when you're debugging a checkout flow. The same webhook is pure noise during a deep work block. A Slack message from your cofounder is critical at 11am Tuesday and irrelevant at 11pm Friday.

The right question is:

Is this urgent enough to interrupt me, right now, given what I'm doing?

That's not a question any individual AI agent can answer. It's a layer above all your AI agents. None of them have the context. None of them know what the others are doing. None of them know how you're spending the next hour.

So they all default to "I'll just send you a notification, you decide." Which is exactly the experience you have right now: drowning.

What an AI firewall actually looks like

I'm building that layer. It's called Klorn. Here's how it works in practice.

Every signal — email, calendar invite, agent action, webhook, push from another tool — goes through a 5-tier decision:

Tier Behavior When
Silent Log it. Nothing else. Available if you ask. Default for noise: marketing, GitHub auto-closes, Stripe receipts, Vercel deploy success.
Queue Show up in a daily digest. No push. Newsletters, FYIs, batched updates.
Push Phone notification. Real interrupt. Rare. Someone replying to a thread you're waiting on.
Call Phone call. Pick up or it escalates. Genuine emergencies. Production down. Family.
Auto-handle Just do the thing. Send the receipt later. Calendar accepts that match your rules. Form replies. Receipts.

The tier decision uses:

  • Per-contact trust scores that learn from your reply rate, meeting acceptance, and historical interactions — not just rules you wrote once and forgot about
  • Calendar status awareness (deep work? meeting? off-hours? PTO?)
  • Actual urgency signals, not "URGENT!!!" in the subject line, because "URGENT" in a subject line usually means the opposite of urgent
  • Per-domain priorities you set once and don't touch again

Default-deny. Most things get Silent or Queue. Push is rare. Call is reserved. Auto-handle stays out of your way and ships you a receipt later if you want to review.

Why building this is unpopular in 2026

Building AI firewalls is unsexy. Investors want "AI agents that DO things." Saying "I built a system that does fewer things, more quietly" sounds backwards on a pitch deck.

But every founder I've shown this to has the same reaction: relief. Because they're drowning. Because every productivity tool they bought made their attention worse, not better. The AI agent boom didn't reduce their work. It raised the floor of background notifications.

The default for AI tools should be: shut up unless it actually matters.

Most don't. So I'm building the layer that enforces it from outside, since none of the individual tools will do it on their own.

Where I am

Week 5 of solo building. Private beta with manual invites. I dogfood it every day — my own inbox, calendar, and connected agents all run through Klorn. I'm down to 3-7 actual push notifications per day. Used to be 40+. The 40+ wasn't "I forgot to mute Slack." It was the genuine noise floor of running multiple AI tools alongside a real inbox.

Stack: Next.js 15, TypeScript, Prisma, Postgres, Claude / OpenAI tool use, Gmail + Google Calendar integrations, Render.

The actual unpopular opinion

If your AI tool sends push notifications by default, it's broken. Doesn't matter how good its reasoning is. You can't reason your way out of a notification flood.

The next valuable layer of agentic products won't be more agents. It'll be the firewall that decides which agents are allowed to interrupt you, when.


Try it: klorn.ai
Code: github.com/k08200/klorn

If you're building agentic products and you disagree, I want to hear it. If you've solved it differently, I want to hear that more.