- Prompt engineering alone is insufficient for agents because it ignores the complexities of system architecture and real-world execution.
- Agent development is fundamentally an orchestration problem requiring backend expertise.
- Tool interaction contracts must be rigorous to prevent the AI from filling in gaps with dangerous assumptions.
- Retrieval systems require sophisticated strategies like re-ranking to ensure the model receives quality signal instead of noise.
- Reliability patterns such as circuit breakers must be implemented to manage the inherent instability of external API dependencies.
- Security in agents is a system-level concern involving both input validation and strict permission boundaries.
- Continuous improvement in agent performance must be driven by data and metrics rather than anecdotal feedback.
- Successful agents prioritize user experience by clearly communicating uncertainty and handling failures gracefully.
