The Agent Pattern
An agent: AI that takes actions. Not just generates text.
Posium is an agent. It tests websites autonomously.
Here's what building agentic products taught us.
What Makes It Different
Traditional SaaS
User takes action. Software responds.
Agentic SaaS
User sets goal. Agent acts autonomously.
Different UX. Different architecture. Different risks.
The Architecture
1. Goal Definition
User says: "Test our checkout flow."
Not: "Click button X. Then button Y."
2. Action Planning
Agent breaks goal into steps.
This is hard. Requires good prompting.
3. Execution
Agent acts. Browser automation. API calls.
4. Monitoring
User watches. Agent reports progress.
5. Verification
Agent checks results. Did it work?
The Risks
1. Infinite Loops
Agents can get stuck.
Build safeguards. Time limits. Escape hatches.
2. Unexpected Actions
Agents do unexpected things.
Sandbox carefully. Monitor closely.
3. Cost Explosion
Agents make many calls.
Costs can spiral. Monitor per-task costs.
The Opportunities
1. Automation
Agents automate tasks humans hate.
Boring, repetitive work. Perfect for agents.
2. Scale
One agent does work of many humans.
Cost-effective at scale.
3. Consistency
Agents don't get tired. Don't make tired mistakes.
Same quality, always.
When Agents Make Sense
Good For
- Repetitive tasks
- Well-defined goals
- High-volume work
- 24/7 operation
Not Good For
- Creative work
- Ambiguous requirements
- High-stakes decisions
- Novel problems
The Honest Take
Agentic SaaS is early. Risky. Promising.
Build agents when:
- Task is repetitive
- Goal is clear
- You can monitor costs
- Failure is recoverable
Don't build agents for everything. But for the right tasks, they're powerful.
