The Startup Ideas Podcast
The best businesses are built at the intersection of emerging technology, community, and real human needs.
Start Small, Iterate Agent Development
A development approach for AI agents where you begin with the simplest possible version and progressively add complexity through rapid iteration
How It Works
Build minimal viable agent, test it, observe failures, add instructions to handle edge cases, repeat until sophisticated
Components
Start with the simplest possible agent
Test and observe where it fails
Add specific instructions for failure cases
Gradually increase complexity
Maintain feedback loop between testing and instruction updates
When to Use
When building any AI agent or automation workflow, especially when the end goal is complex
When Not to Use
When you need a perfect solution immediately or when iteration costs are prohibitive
Anti-Patterns to Avoid
Example
“LinkedIn outreach agent starts with just sending one DM, then adds calendar checking, then follow-up sequences, eventually becoming a full nurturing system.”
Related Knowledge
Marketing-First Product Validation
A product development approach that validates marketing channels and customer acquisition before building the actual pro
ICE Score Feature Prioritization
A scoring system for prioritizing product features using Impact × Confidence ÷ Effort to determine what to build next
Three-Technology Product Validation
Validate product ideas by ensuring they work with three key technologies: 3D printing for prototyping, AI for ideation,
validate people want to buy this thing see if you can build it
Prove market demand and distribution viability before spending time building the actual product
impact times confidence over effort put it into score
Prioritize product features using quantified impact, confidence, and effort scores rather than subjective preference