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

Y
Y Combinator Blog
有赞技术团队
有赞技术团队
J
Java Code Geeks
H
Hackread – Cybersecurity News, Data Breaches, AI and More
美团技术团队
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Hugging Face - Blog
Hugging Face - Blog
人人都是产品经理
人人都是产品经理
酷 壳 – CoolShell
酷 壳 – CoolShell
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
C
Check Point Blog
博客园 - 【当耐特】
The GitHub Blog
The GitHub Blog
Recent Announcements
Recent Announcements
The Cloudflare Blog
Microsoft Azure Blog
Microsoft Azure Blog
腾讯CDC
Vercel News
Vercel News
IT之家
IT之家
MyScale Blog
MyScale Blog
博客园_首页
Martin Fowler
Martin Fowler
WordPress大学
WordPress大学
罗磊的独立博客

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
My pre-sprint decision memo for AI-generated MVPs
Vivian Chi · 2026-06-14 · via DEV Community

Vivian Chi

I used to move from "this prototype looks promising" to "let's break it into tasks" far too fast.

Now, after NxCode generates a clickable MVP, I stop and write a short pre-sprint decision memo. It is not a product requirement doc. It is a forcing function that tells me whether the flow deserves engineering time at all.

Here is the structure I use.

1. Name one user and one trigger

I do not allow a generic answer like "teams" or "small businesses."

I write:

  • primary user
  • event that starts the workflow

Example:

  • User: operations manager at a small agency
  • Trigger: a lead is marked qualified after a discovery call

2. Identify the proof screen

The proof screen is the one screen that proves the job is being done.

For a client-intake MVP, mine is usually a board with:

  • owner
  • next action
  • due date
  • status

If the most important screen still feels decorative, the MVP is not ready.

3. List the must-be-right data

I only include the fields that would break trust if they were wrong:

  • contact source
  • priority
  • owner
  • due date
  • short customer note

This keeps me from over-modeling too early.

4. Write the fake edge case

Every AI-generated flow has at least one path that looks complete until you ask an annoying question.

My usual prompts:

  • what if no owner is assigned?
  • what if the due date is empty?
  • what if the item is blocked?

If the prototype falls apart here, it is still a demo.

5. Cut the first sprint on purpose

This is where I save the most time. I explicitly mark things out:

  • analytics
  • notifications
  • billing
  • permissions matrix
  • admin settings

The memo is useful because it removes convincing extras before they turn into tickets.

6. End with one handoff sentence

I finish with one sentence the team can challenge:

Build the intake board, manual status updates, and next-action workflow; leave permissions and reporting out of sprint one.

That sentence is enough for a useful handoff.

I have been testing this process around NxCode because it lets me review a realistic flow before I commit implementation time:

https://www.nxcode.io/

The prototype gives me something concrete to inspect. The memo decides whether it earns sprint time.