I'm Prime.X — engineer focused on AI agents, LLM applications, and AI-native developer tools.
Tech lead at an AI startup. Turning agent prototypes into products that ship.
I like turning fuzzy problems into clean system boundaries: validate the core path first, then polish interfaces, automation, and maintainability. Good engineering isn't piling complexity — it's making ideas faster to validate, reuse, and ship.
- AI agents & LLM applications — agent architectures, tool use, planning loops, memory strategies, and evaluation
- AI-native developer tooling — coding agents, CLI workflows, agentic dev experience that actually saves time
- Backend systems for AI products — APIs, queues, observability, and clean service boundaries under uncertain LLM behavior
- Idea → running demo — shortest path to verify whether something is worth pursuing
| Area | Stack |
|---|---|
| AI / Agents | LLM apps, agent workflows, tool use, planning, memory, evaluation |
| Languages | Go, TypeScript / JavaScript, Python |
| Backend | APIs, queues, data modeling, service integration, observability |
| Infra | PostgreSQL, Redis, Kafka, Docker, Kubernetes, Linux |
| Frontend & prototypes | Vue, React, HTML / CSS, interactive demos |
- Make the riskiest assumption runnable before deciding to scale
- Prefer simple, direct, verifiable implementations
- Care about developer experience: clear commands, clear docs, clear failure paths
- Hold system boundaries in design — no abstraction for abstraction's sake
- Profile: @primexiao
- Snippets: Gists
- Repos: Repositories
