Manage evolving business knowledge for AI. AI Context Versioning ensures accuracy, auditability, and consistency for intelligent systems.
Leverage AI for cloud capacity planning. Forecast future resource needs, optimize performance, and reduce costs with intelligent scaling.
AI Change Impact Analysis predicts software release risks by analyzing code, dependencies, and historical data, improving reliability.

Build AI-powered knowledge validation systems with .NET and ASP.NET Core to ensure accurate, consistent, and up-to-date organizational knowledge.
Master AI Context Lifecycle Management: Store, update, and retire context effectively for better AI responses and reduced costs.

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.
DevSocialUpcoming · 3rd editionAI Agents ConferenceNov 23–27, 2026Live onlineMembers only16days leftRegisterMembers onlyWrite an article and earn +1,000 SHARP when it is approved.
Write an article