Real-world lessons from evolving a production chatbot into a coordinator-based multi-agent architecture, including performance trade-offs for enterprise-scale agent reuse.
A data-driven framework we use in enterprise deployments to decide between vector-only keyword and hybrid search, based on five measurable evaluation criteria.
A practical pattern for using GenAI research agents to produce reliable internal tooling by verifying assumptions with detection classes and a final checklist.
How to move AI-assisted development from ad-hoc experimentation to a coordinated team-wide capability using AGENTS.md and reusable skills with GitHub Copilot CLI
Evaluating AI agents for NL-to-SQL generation across Azure Databricks AI/BI Genie, GitHub Copilot CLI, and Microsoft Agent Framework. We achieved ~75% accuracy with schema documentation and runtime validation, while discovering that business logic errors represent a fundamental limitation requiring domain expertise.
A security-first architecture that propagates SharePoint document permissions into downstream AI systems, using Microsoft Entra ID object IDs (GUIDs) for safe, query-time filtering in Azure AI Search, RAG pipelines, and Copilot extensions.
Key insights from the EDA and Ground Truth journey for solving well identity resolution in the Energy industry—challenges that extend to any entity matching problem across distributed systems.