Supabase for AI Is Also a Bad Idea

The Honest Take

Supabase is a solid product.

Postgres is great.
Row-level security is powerful.
Self-hosting sounds reassuring.

But AI generation does not magically become a good fit just because it's Postgres-backed.

Using Supabase for AI often recreates the same problems as Firebase. just with more knobs and more confidence.

Why Supabase Feels "Safer" for AI

Developers reach for Supabase because it promises:

• SQL instead of NoSQL
• Open-source tooling
• Self-hosting options
• Familiar backend patterns

Compared to Firebase, it feels more serious and more controllable.

That feeling is misleading when it comes to AI generation.

Problem #1: AI Prompts Still Have to Leave the Device

No matter how you configure Supabase:

• Prompts are sent over the network
• Data hits a backend
• Logs, backups, or replicas exist somewhere

Even if you self-host:

• Prompts exist outside the user's device
• You now have operational and security responsibility
• "Private" becomes a promise you must maintain forever

Offline AI avoids this by design.

Problem #2: Postgres Is Not a Creative Medium

Postgres excels at:

• Structured data
• Transactions
• Queries and joins

AI generation produces:

• Large prompts
• Binary outputs
• Iterative experimentation
• Disposable artifacts

Forcing AI workflows through a database:

• Adds friction
• Encourages unnecessary persistence
• Turns creativity into records and rows

Most AI outputs do not need to be stored centrally at all.

Problem #3: "Self-Hosted" Still Isn't Local

This is the subtle but critical distinction.

Self-hosted Supabase means:

• You run the servers
• You manage uptime
• You manage security

It does not mean:

• The AI runs on the user's machine
• Prompts stay on-device
• Offline usage is possible

From the user's perspective, it's still:

"My data goes somewhere else."

Local AI means:

"My data never leaves."

Those are fundamentally different trust models.

Problem #4: Latency Is the Enemy of Iteration

AI creativity depends on fast feedback loops:

• tweak prompt
• generate
• adjust
• repeat

Supabase-based AI flows add:

• Network latency
• Request overhead
• Queueing
• Failure points

Local generation:

• Removes the round trip
• Feels instant
• Encourages experimentation

You don't need "web scale" for creative iteration.

Problem #5: Costs Still Scale With Usage

Even with Supabase:

• Storage grows
• Bandwidth grows
• Compute grows
• Backups grow

Heavy users become expensive users.
You're incentivized to:

• Rate limit
• Compress
• Restrict
• Meter creativity

Offline AI has a different incentive structure:

• One-time cost
• Unlimited local usage
• No per-generation penalty

That aligns better with creators.

The Mistake: Treating AI Like a Backend Feature

Supabase shines when AI is:

• A feature of a larger app
• Supporting CRUD workflows
• Secondary to collaboration or sync

It breaks down when AI is the product.

AI generation is:

• Personal
• Exploratory
• Often private
• Frequently offline-friendly

It doesn't need a database first.

A Better Mental Model: Local-First AI

Local-first AI tools:

• Run directly on user hardware
• Avoid backend dependencies
• Don't require accounts
• Don't upload prompts by default

This model:

• Eliminates entire classes of risk
• Simplifies architecture
• Builds immediate trust
• Scales naturally with users' machines

Where LocalForge AI Fits

LocalForge AI is built on the assumption that:

• AI generation should work offline
• Prompts should stay private
• Saving should be explicit
• The cloud should be optional, not mandatory

That's a different philosophy than "Postgres for everything". and that's intentional.

When Supabase Does Make Sense

Supabase can be a good choice if:

• You're building collaborative AI tools
• Shared state is core
• Cloud sync is a requirement
• Users expect accounts and persistence

But those are product constraints, not defaults.

Final Takeaway

Supabase is a great backend.

AI generation is often not a backend problem.

If your AI tool requires a database before it can create anything, you're likely solving the wrong problem first.

Local, offline AI removes that complexity entirely.