Building Something Different
We built Posium. An AI testing agent.
It was different from any SaaS we'd built.
Here's what we learned.
The AI Addition
Not a Feature. A Core Capability.
Most "AI features" bolt onto existing products.
Posium IS AI. The product is the AI.
Different approach required.
What Is Different
1. Output Quality Varies
Traditional software: Same input = Same output.
AI: Same input = Variable output.
You need:
- Prompt engineering
- Output validation
- Fallback mechanisms
2. Latency
Traditional: Fast responses.
AI: Can take 30+ seconds.
Design for this. Show loading states. Be honest.
3. Cost
Traditional: Compute costs are predictable.
AI: Per-call costs can spike.
Monitor usage. Set caps. Design for efficiency.
The Build
1. Start with Outputs
What should the AI produce?
Define the format. Define the quality bar.
Test outputs before building integration.
2. Build Validation
AI produces garbage sometimes.
Build validation. Catch bad outputs.
3. Design the Human Loop
AI doesn't replace humans. It assists them.
Design for human review. Human correction. Human override.
The Honest Take
Building AI SaaS is harder than traditional SaaS.
But it's also more defensible.
If your AI is good, it improves with use.
That's a competitive moat.
When to Add AI
AI adds:
- Development complexity
- Cost complexity
- Latency complexity
Make sure the value justifies the complexity.
For Posium, it did. For many products, it doesn't.
