Use the custom prompts from this article and the linked repository to have the agent (1) plan, (2) implement, and (3) review any code for better results.
AI is transforming network routers and switches by driving intelligent automation, boosting performance and security, while streamlining operational complexity.
In this article, learn the core challenges of running AI in the cloud — availability, reliability, observability, and responsibility — and how to overcome them.
Explore existing problems with AI-assisted coding. AI tools need to give developers more structure, more control, and more ways to test and trust what gets built.
Zero "agentic AI". Zero "cloud native". Zero other hype. Just an approach to achieving an efficient AI-centric automation using 100% free open-source components.
Learn to build a no-code AI bot to generate test cases from user stories using ChatGPT. Customize tone, behavior, and export structured test scripts easily.
Introductory article about MCP, a universal adapter that allows AI assistants to access and interact with external systems while maintaining a consistent interface.
Learn in this article how LangGraph’s Orchestrator-Worker agents enable dynamic task delegation using LLMs for smarter, scalable, and adaptive AI workflows.
Learn to build a simple AIOps dashboard using Prometheus, Grafana, and ML-based anomaly detection to monitor metrics, set alerts, and prevent failures.
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