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Live Updates Checklist for AI-Built Apps

Real-time sync without refreshing

When you vibe code live updates with tools like Cursor, Lovable, Bolt, v0, or Claude Code, the generated code often works in development but misses critical production requirements. This checklist helps you catch what AI missed before you ship.

Danger Zone

high risk

Real-time features work great with 5 users — then mysteriously fall apart with 500

Making something update live on the screen feels like magic when it works. Behind that magic is a constant connection between every user and your server that needs to survive spotty wifi, browser sleep modes, and server restarts. Each connection uses memory, and suddenly you're managing thousands of open connections that all need to know when something changes. One user's browser going to sleep and waking up can create a cascade of duplicate updates.

Failure scenario

You build a real-time dashboard. Works perfectly in testing. You launch and get 200 concurrent users. Your server runs out of memory from holding all those connections open. Users start seeing stale data because their connections silently died and never reconnected. Support tickets pile up saying "the dashboard isn't updating" but when they refresh, it's fine.

Common mistakes

  • Connections that die silently when wifi drops or browser sleeps — user thinks they're seeing live data but it's frozen
  • Every new connection subscribes to every update, so adding users makes everything slower for everyone
  • No tracking of which connections are actually alive — server holds thousands of dead connections in memory
  • Updates sent to every single user instead of just the ones who need to see them
  • Reconnecting creates duplicate subscriptions, so users see the same update 3-4 times

Time to break: 2-6 months when you hit your first traffic spike

How are you building this?

Showing what to check when using a managed service

Audit Prompts

Copy these into your AI coding assistant to check your implementation.

Will connections survive real-world conditions?
reliability
Check how our live update service (Pusher, Ably, etc.) handles connection problems. What happens when someone's wifi drops for 10 seconds? When their laptop goes to sleep and wakes up? When they switch from wifi to mobile data? Do they automatically reconnect? Do they get any updates they missed while disconnected? Is there visual feedback showing connection status?

Real users have spotty connections. If your live updates silently die when wifi hiccups, users think they're seeing current data when they're not.

Are you only sending updates to people who need them?
performance
Look at how we've set up channels or rooms in our live update service. When something updates, does it only notify users who are looking at that specific thing (not everyone)? Are users unsubscribed from channels when they navigate away? Can someone subscribe to channels they shouldn't have access to?

Sending every update to every user kills performance as you grow. It's like announcing every email to an entire office instead of just the recipient.

Can your service handle your traffic?
cost
Check our live update service plan and limits. How many concurrent connections does our plan support? How many messages per month? Are we monitoring usage so we know when we're approaching limits? What happens if we exceed limits — does it fail gracefully or just break?

Free tiers on WebSocket services run out fast. 1,000 concurrent users on a free plan means everyone gets disconnected when user 1,001 shows up.

Is live data secured properly?
security
Review security for our live update channels. Are channels locked down so users only see data they're authorized to see? Are channel names predictable (like user-123) where someone could guess others? When someone subscribes to a channel, do we verify they should have access? Are sensitive updates encrypted?

Live updates bypass normal page security. If channels aren't locked down, changing a channel name in browser dev tools could let someone watch updates meant for other users.

Checklist

0/10 completed

Smart Move

Use a service

WebSockets are deceptively hard to scale. Connection management, reconnection logic, and message fan-out are all things that look simple until you have real traffic. Services have solved these problems across millions of connections. Unless you have very specific requirements or are building the next Figma, use a service.

Pusher

Dead simple pub/sub for live updates — great docs, works with everything

100 concurrent connections, 200k messages/day free

Supabase Realtime

Built into Supabase — if you're already using it, this is the easiest choice

Included with Supabase free tier (500 concurrent connections)

Ably

More features than Pusher, better for complex scenarios like presence and history

200 concurrent connections, 6M messages/month free

PartyKit

Edge-first, great for multiplayer and collaborative features, runs on Cloudflare

Free for development, pay-as-you-go in production

Tradeoffs

You're paying per connection and per message, which can get expensive at scale. Migration is painful if you ever need to switch. But getting it right yourself requires deep infrastructure knowledge most teams don't have.

Did you know?

WebSocket connections use 10-50x more memory than regular HTTP requests, and a single server can typically handle 10,000-60,000 concurrent connections before running out of memory.

Source: AWS Architecture Blog on WebSocket scaling patterns

Related Checks

🩺Monitoring

Error tracking and observability

🔔Notifications

Push, email, and in-app alerts

🔐Authentication

Sign up, log in, password reset, 2FA