AI researcher Ā· Community builder ā reaching 500 000+ developers every month
Turning cuttingāedge AI research into reliable, productionāready systems
If you build technology that fits the generative AI agent or RetrievalāAugmented Generation stack - vector databases, embeddings APIs, real time web search, orchestration layers, observability platforms, GPU hosting, security guardrails, and similar - let us coācreate an open source Jupyter tutorial that shows developers a neutral end to end workflow for your tool. The content stays free and vendor agnostic, you gain authentic adoption, and the community gets another fully runnable example.
- Reach - 500 000+ developer views per month
- Format - clear, reproducible notebooks with no paywalls or ads
- Goal - give developers runnable examples while partners gain authentic adoption
Interested? Contact me on
LinkedIn
or at
DiamantāAI.com.
Repository | What you learn | Live Stars |
---|---|---|
Agents Towards Production | Stepābyāstep notebook tutorials that cover ingestion, retrieval, memory, tool routing, guardrails, evaluation, observability, CI/CD, cost tracking, security, and cloud deployment for productionāready AI agents. | |
Prompt Engineering | A 20āchapter notebook series that moves from prompt basics to advanced techniques with handsāon code examples and exercises drawn from the 170āpage Prompt Engineering handbook. | |
RAG Techniques | More than 30 tutorials demonstrating RetrievalāAugmented Generation methods, evaluation metrics, and best practices to build accurate and efficient RAG pipelines. | |
GenAI Agents | Guides and reference implementations for building chatbots, autonomous agents, and multiāagent workflows with memory and tool integrations. |
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