Building a Practical AI Radar — notes from the state-management trenches

1. 1Design a state management system to track data sources and pipeline status
2. 2Implement a multi-source OSINT radar to collect and process data
3. 3Use AI as a reviewer to validate and refine pipeline outputs
4. 4Configure pipeline workflows to optimize data flow and minimize errors
5. 5Test and refine the pipeline using real-world data and scenarios

Data engineers, AI researchers, and DevOps teams can benefit from this approach to build more efficient and scalable pipelines

💡 State management is crucial for building efficient and scalable AI pipelines, and AI works best as a reviewer, not a doer

🚀 Build a practical AI radar by prioritizing state management and using AI as a reviewer, not a doer! 💡