Blogpost
Artificial General Intelligence dominates headlines, but where exactly are we? This analysis cuts through the hype, examining current capabilities, expert perspectives from Altman to LeCun, and what enterprise leaders should actually be planning for.
Blogpost
Software is evolving from transactional tools to autonomous agents that reason, plan, and execute. This comprehensive guide for CIOs explores what the agentic revolution means for enterprise architecture, risk management, and competitive strategy.
Blogpost
For healthcare, finance, and other regulated industries, AI deployment demands more than technical excellence. Explore the essential pillars of compliance, explainability, and governance that make enterprise AI both powerful and responsible.
Blogpost
Just as Ruby on Rails revolutionized web development with "convention over configuration," Microsoft's Semantic Kernel is transforming AI application development. Learn why this opinionated framework is a game-changer for .NET teams.
Blogpost
Building AI in-house is expensive. Off-the-shelf solutions are rigid. Discover why a platform approach—combining infrastructure with flexibility—is the strategic winner for mid-sized enterprises looking to deploy AI at scale.
Blogpost
Learn how Retrieval-Augmented Generation (RAG) transforms LLMs from generic chatbots into reliable enterprise knowledge systems. This deep-dive covers vector databases, embedding models, and production RAG architecture in .NET.
Blogpost
Discover how to add intelligent automation to mature .NET applications without a costly rewrite. Learn practical strategies using Semantic Kernel and the Façade pattern to build AI agents that orchestrate your existing systems.
Blogpost
Many AI projects show promise in the lab but falter before delivering real-world value. This guide explores the five common pitfalls that derail AI initiatives and provides a strategic framework to ensure your PoC successfully transitions to a production-ready asset.
Blogpost
For .NET shops, the path to AI isn't one-size-fits-all. This guide breaks down the three primary routes—ML.NET, Azure ML, and third-party APIs—helping you decide when to build, when to leverage a platform, and when to just consume.
Blogpost
MCP is the "HTTP for AI." Learn how this open protocol solves the enterprise integration nightmare, eliminates vendor lock-in, and enables a future of interoperable, secure, and scalable AI applications.
Blogpost
Move beyond simple chatbots. Learn the architectural principles and strategic steps to build robust, production-ready AI agents using Microsoft's Semantic Kernel within your existing .NET ecosystem.
Blogpost
A comprehensive developer's guide to fine-tuning Large Language Models. Learn the complete stack from LoRA and PEFT to production deployment with Python and .NET integration.
Blogpost
How .NET enterprises can upgrade to AI and machine learning without risky rewrites. Learn about ML.NET, Azure ML, and Smaltsoft's MCP integration.
Blogpost
Discover how prompt engineering and Smaltsoft's smalt prompt tool can reduce LLM API costs by up to 60% while improving accuracy.
Blogpost
Should you build, buy, or fine-tune your AI models? Smaltsoft's guide for mid-sized businesses covers data, ROI, and smart strategy.