Agentic Engineering
AI agent infrastructure, cognitive memory systems, and MCP integrations that give your agents real capabilities.
The gap between AI demos and production AI systems is enormous. I build the infrastructure that makes agents reliable: persistent memory, tool integration via MCP, structured skill systems, and human-in-the-loop safety controls. This isn't prompt engineering — it's systems engineering for autonomous software.
What this includes
- Agent architecture design with safety guardrails and trust ladders
- MCP (Model Context Protocol) server development for tool integration
- RAG pipeline design and implementation with pgvector or similar vector stores
- Cognitive memory systems that give agents persistent, evolving context
- Human-in-the-loop (HITL) workflow design for agent oversight
- Multi-agent orchestration patterns for parallel task execution
What you get
- Production-ready MCP servers exposing your domain knowledge to AI agents
- Agent memory architecture with semantic search and knowledge evolution
- Structured skill and context file systems for autonomous agent operation
- Safety framework with escalation policies and audit trails
- Integration with Claude, OpenAI, or open-source models
Interested in this service?
Every engagement starts with a conversation. Let's talk about your specific needs.