Devman technical practice
Devman Agents
Practical architecture for production AI agents.
Devman Agents brings together LLMs, context, RAG, tools, workflows, observability, evaluation, and deployment discipline for real business systems.
Agent systems, not prompt demos
Useful AI agents need grounding, tools, traces, test cases, controlled secrets, and deployment patterns. Devman documents those pieces as an engineering practice.
The public docs are suitable for developers, clients, and collaborators who want to understand how Devman approaches AI automation responsibly.
Architecture Formula
LLM + Context + RAG + Tools + Workflow + Observability + Evaluation
What the docs cover
The public knowledge base focuses on repeatable patterns and avoids private infrastructure details.
Mastra-based agent architecture
RAG and knowledge pipelines
Langfuse observability
LLM training and evaluation
Local LLMs and embeddings
Production deployment patterns