I am exploring different approaches for building AI-powered workflow systems where Gemini can understand user intent, reason through tasks, and interact with external tools or APIs.
A common architecture I have been experimenting with includes:
- User request/input layer
- Gemini reasoning layer
- Tool/API execution layer
- Workflow orchestration
- Validation and human approval steps
Some questions I would like to discuss with the community:
- What patterns are you using for managing multi-step workflows with Gemini API?
- How do you handle failures when an AI agent calls external APIs?
- Are you using custom orchestration layers, Google Cloud services, or third-party workflow tools?
- What approaches have worked well for maintaining reliability in production AI agents?
Would love to hear how developers are designing scalable Gemini-powered automation systems.