Articles
Engineering notes from the HEU.AI team on agent frameworks, retrieval, and what it takes to run AI systems reliably in production.
These articles are written by the engineers who design and build HEU.AI's client systems. Each one takes a single question that comes up when an AI system has to work outside a demo, such as which agent framework to build on or why a retrieval system misses an exact product code, and answers it with the trade-offs laid out plainly rather than as a feature list.
The topics follow the work we do most. On the agent side, that means agentic AI development: how frameworks like LangGraph, CrewAI, and AutoGen execute, hold state, and recover from failure. On the retrieval side, it means RAG development: hybrid search, reranking, the vector databases underneath, and the evaluation that shows whether a change actually helped.
Where an article includes code, the sample is short and there to make an idea concrete, not to serve as a full implementation. Each article ends with answers to common questions and links to the service page behind it. If you are weighing one of these decisions for your own system, you can book a free consultation and talk it through with an engineer.