Large Language Models and AI for Developers
Complete guide and related articles on LLM
Practical guide to LLMs for .NET developers: integrate generative AI, GitHub Copilot and models into real applications without falling for market noise.
Practical guides on LLMs and AI for software development
4 articles found
Use hybrid search if you want to stop getting almost-right results
Signs you need hybrid search: unstable ranking, ignored tokens, imprecise results. Solutions across keyword search, embedding and re-ranking.
Software as an asset or a cost? How much money are you really losing every month?
Discover why treating software as an asset changes estimates and business risk. Practical criteria, indicators and choices to turn code into capital.
What is the best AI for programming without losing control
Discover the best AI for programming in 2026: when to use it in the IDE and when to use a chat. Real examples, free-tier limits, and method choices.
When LLMs become a real leverage point
LLMs become a real leverage point when they are connected to processes, data, and concrete use cases. Without integration they remain an impressive demo; with the right method they become assistants, semantic search engines, intelligent interfaces, and productivity multipliers for technical teams and companies.
Useful technologies for AI and LLM projects
- .NET — runtime and libraries for integrating LLMs into enterprise applications
- C# — main language for orchestrating AI pipelines with Semantic Kernel
- Azure — Microsoft cloud with OpenAI Service, AI Search and Cognitive Services
Sources and references
Chip Huyen - Applied AI systems
I use this to keep the LLM discussion grounded in real systems, metrics, and operational reliability.
Simon Willison - LLMs in production
This helps cut through hype and bring the focus back to observability, prompting, tool use, and practical limits.
Martin Fowler - Generative AI engineering
I include it to connect AI adoption with the same architecture, risk, and governance questions that matter in serious software.