Hi everyone,
AI agents are becoming more common, but building reliable agent-based applications still comes with many challenges.
I am interested in learning how developers are approaching real-world AI agent systems.
Some areas I would like to discuss:
- Designing effective agent workflows
- Managing context and memory
- Connecting agents with external tools and APIs
- Improving accuracy and reliability
- Handling unexpected outputs or failures
For developers working with AI agents:
- What architecture patterns have worked well for your projects?
- How do you evaluate and improve agent performance?
- Which tools or frameworks have helped you build better AI applications?
Looking forward to hearing everyone’s experiences and ideas.