Nidhi Sharma's contributions

Build AI-powered ADR systems using .NET to automate decision capture, improve knowledge discovery, and enhance architectural governance.

Learn how to build AI-based data quality monitoring in .NET, including validation, anomaly detection, duplicate detection, data drift monitoring, and quality scoring.

AI sprint planning assistants optimize Agile development by automating estimations, predicting capacity, and identifying risks for faster, more predictable sprints.

Learn how to build an AI-powered data classification service in .NET and ASP.NET Core to categorize documents, detect sensitive information, and apply governance policies.

Optimize enterprise AI performance with prompt and semantic caching. Reduce costs, boost speed, and enhance scalability for LLM applications.

Leverage AI for legacy .NET modernization. Accelerate migration, reduce risk, and transform old systems with intelligent strategies.

Unlock developer productivity with AI analytics dashboards. Gain insights, identify bottlenecks, and predict risks for better software delivery.

AI-powered pull request analysis enhances code reviews by identifying risks, improving quality, and boosting efficiency beyond traditional methods.

Design enterprise AI escalation workflows for critical decisions, balancing automation with human oversight for accuracy, accountability, and compliance.

Build AI-powered incident triage for cloud apps using .NET, Azure OpenAI, and OpenTelemetry to accelerate troubleshooting and reduce MTTR.

Master AI model benchmarking for .NET developers. Measure accuracy, cost, and latency for optimal production AI solutions.

Build AI-powered API documentation assistants with .NET, Azure AI Search, and Azure OpenAI for enhanced developer productivity and accessibility.

Unlock enterprise efficiency with Small Language Models (.NET). Discover SLMs for faster, cost-effective AI solutions, enhanced privacy, and flexible deployment.

Unlock AI potential with .NET Enterprise Knowledge Graphs. Understand relationships, boost accuracy, and build smarter AI applications.

Optimize AI costs & performance by routing requests to the right LLM. Discover strategies for efficient model selection.

Master AI incident response for LLM apps. Learn to debug production failures, monitor performance, and ensure reliability with .NET.

Build AI-powered support engineers with ASP.NET Core, Azure OpenAI, and Azure AI Search for faster resolutions and reduced costs.

Master AI runtime management for enterprise apps: architecture, monitoring, scaling, and cost optimization for reliable production AI.

Unlock AI's true potential: Measure real-world usage, quality, cost, and business impact with AI analytics & telemetry.

Build AI-powered documentation search for engineering teams using ASP.NET Core. Overcome keyword search limitations with semantic search & LLMs.

Master AI workload orchestration to manage multiple models in production. Optimize performance, cost, and reliability for enterprise AI applications.

Explore Local-First AI Development: run enterprise models on Windows PCs for enhanced privacy, reduced costs, and lower latency.

Make your website AI-searchable with Schema.org and NLWeb. Enhance discoverability, user experience, and future-proof your content for intelligent systems.

Build cost-aware AI apps that scale efficiently. Master LLM costs, optimize RAG, implement tiering & budget controls in .NET.

Safely deploy AI in .NET with feature flags. Control rollouts, A/B test models, manage costs, and ensure governance for AI innovations.