Building production-grade intelligent systems.
name: Richard
role: AI/ML Engineer
focus: Building intelligent systems that operate autonomously at scale
languages: ["Java", "Python", "Go", "Rust"]
methodology: Prompt โ Context โ Harness โ Loop
currently:
building: Multi-agent systems & AI infrastructure
exploring: MCP ecosystem, autonomous pipelines, LLM serving
reading: Papers on context engineering & agent orchestrationFrom a single instruction to autonomous systems โ each layer builds on the last.
| Layer | Focus | Key Concepts |
|---|---|---|
01 Prompt |
Instruction Design | Few-shot ยท CoT ยท Structured Output ยท Constraint Prompting |
02 Context |
Information Supply | RAG ยท Vector Search ยท Memory Systems ยท Knowledge Graphs |
03 Harness |
System Orchestration | Agents ยท Tool Use ยท MCP ยท Multi-Agent Coordination |
04 Loop |
Autonomous Operation | Feedback Loops ยท Self-Healing ยท Human-in-the-Loop ยท CI/CD for AI |
GitHub activity
Prompt โ Context โ Harness โ Loop