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

S
SegmentFault 最新的问题
博客园 - 三生石上(FineUI控件)
爱范儿
爱范儿
博客园 - 聂微东
V
Visual Studio 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
M
MIT News - Artificial intelligence
The GitHub Blog
The GitHub Blog
Recent Announcements
Recent Announcements
有赞技术团队
有赞技术团队
L
LangChain Blog
I
InfoQ
T
Tailwind CSS Blog
博客园 - 【当耐特】
V
V2EX
博客园_首页
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
GbyAI
GbyAI
Vercel News
Vercel News
雷峰网
雷峰网
量子位
A
About on SuperTechFans
Martin Fowler
Martin Fowler
H
Help Net Security

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 Made Software Faster. It Didn't Make It Instant
Danilo Assis · 2026-05-13 · via DEV Community

AI Made Software Faster. It Didn't Make It Instant.

There's a growing belief that AI has made shipping software almost trivial. Push a button, get a product. Need a feature? Ten minutes.

It's not true.

Yes, AI accelerates parts of the process — writing code, drafting tests, and scaffolding services. But software, like any real product, lives or dies on the decisions around it: architecture, scale, reliability, users, operations. None of that goes away because the typing got faster.

The Hotel

Imagine you're building a hotel. You start with three rooms. Water pressure is fine. Electricity, A/C, TV, internet — all sized for three rooms. Guests are happy.

Demand grows. You want to serve more people. So you build more rooms.

Now showers run dry in the morning. The power flickers. The Wi-Fi crawls. Costs creep up, and you can't tell why. You doubled your rooms and doubled your problems — because you only thought about rooms, not the system underneath them.

Software works the same way. Adding features, users, and clients isn't free. Every layer below — infrastructure, data, monitoring, on-call, support — has to grow with it. Skipping that conversation doesn't make it disappear. It shows up later as an outage, a cost spike, or a lost customer.

What to Do With This

If you're non-technical, the takeaway isn't "slow down engineering." It's: ask what's underneath the room. What does the next 10x of users actually require? Who owns it? When does it break?

If you're technical, the same applies in reverse. Sales need speed. Ops needs security. Finance needs predictability. Their constraints are as real as yours.

The fastest companies aren't the ones that ignore the trade-offs. They're the ones where every side sees the others' problems clearly enough to decide together.


Recommended reading: The Phoenix Project, by Gene Kim.


Follow me on Twitter
See more in https://linktr.ee/daniloab.


Photo by Sean Pollock on Unsplash