Xiayang Zhang
Summary
I build and ship LLM products end-to-end — AI-native. At Dreemar I was the sole developer for ~1.5 years, effectively the entire engineering team: I built and deployed an early-stage multi-agent AI SaaS solo on AWS and ran the platform's production AWS ops. Today I'm the primary engineer on a live AI + AR education platform — agentic voice tutoring, assessment, and personalization, on real research data. My edge is decomposing problems into specs and orchestrating fleets of models and agents to ship fast, with sharp judgment on model selection, prompting, cost, and reliability. My architecture bias is correctness-first: keep the LLM as adviser/orchestrator and put facts, permissions, and calculations behind deterministic executors with end-to-end provenance — so a stronger model improves coverage without breaking guarantees.
Core Skills
- LLM app engineering
- multi-agent orchestration (Claude Agent SDK, OpenAI Agents SDK, CrewAI)
- agent harness / agent-native ops
- correctness-first architecture (deterministic executors + provenance)
- multi-model selection & routing (self-built gateway + LiteLLM)
- model-landscape breadth (US / China / open-weight)
- local inference (Apple silicon)
- prompt engineering
- realtime voice (OpenAI Realtime)
- LLM observability
- eval-as-regression & cost (Langfuse, Prometheus)
- TypeScript / JavaScript (primary)
- Python
- Go
- C# / .NET
- Next.js
- React
- React Native
- Node.js
- Prisma
- Tailwind
- NextAuth
- REST
- Postgres / Supabase
- pgvector
- MySQL
- ClickHouse
- Redis
- MinIO
- WebXR (Babylon.js)
- Three.js
- Unity
- Blender
- Docker
- CI/CD
- self-hosted Linux / VM ops
- multi-provider LLM gateway
- AWS (production)
- Vercel
- Playwright + Vitest
Selected Shipped Work
Named apps on the App Store / Google Play (Dreemar) — mostly kids' education AR
Irish-folklore IP for ages 4+ — wildlife exploration, AR field guide, games, storybook read-along.
K–Prep learning AR + companion books. A Berwick Lodge Primary × Deakin University project.
View 3D models / video and showcase student & teacher work, for the Victorian Tech Schools.
iOS App Clip + Android Instant App — cross-platform AR with no install. An industry-first.
Dreemar's consumer AR app — tens of thousands of downloads.
Built the dynamic QR-code URL routing for AFL star / fantasy trading cards.
Experience
Independent AI Engineer — Self-directed R&D · Apr 2025 – Present · Melbourne
Building LLM/agent systems and operating fully AI-native.
- AREAR — live AI + AR education platform (primary engineer; a research collaboration with a university Research Fellow — live, on real research data — that began when the Fellow sought out my Dreemar AR-analytics work). A WebXR platform delivering: an agentic voice tutor with persistent cross-session memory; assessment via tool-call quizzes/games and per-lesson probes; personalization via per-student persona modelling; and feedback/analytics from audio emotion analysis plus spatial replay of student view-direction and movement.
- Stack: Next.js 16 / React 19 / TS · Babylon.js + Three.js · multi-model — GPT-5.5 (analysis), OpenAI Realtime (voice), Gemini (dynamic storybook imagery) · Supabase/Postgres · Playwright + Vitest. (Private repo — live walkthrough on request.)
- Breadcrumbs — two-sided clinical-AI system (solo): Gretel, a real consumer iOS/Watch app live on the App Store (SwiftUI, on-device AI; non-diagnostic) — biosignal shifts → lightweight voice check-ins → structured, medication-aware, auditable episodes — and Hansel, a hospital-facing clinician console closing the loop — episode monitoring → AI-drafted follow-up suggestions (draft-only) → clinic check-ins pushed back into the app (React / TanStack; fully functional, shown as an all-synthetic demo — heavily regulated domain; demo sign-in at hansel.lemomo.ai) — integrating over a frozen, machine-checkable contract. Showcases correctness-first architecture — deterministic clinical executors (schema / terminology / medication checks) kept separate from a draft-only LLM adviser, with a provenance hub labelling every output real / mock / license-required / production-path. Cleared App Store health-data privacy review. gretel.lemomo.ai
- Harness-led / agent-native ops — I don't hand-write deep infra; I design the architecture and write the agent harness that drives agents to run it. Proof:
/incus, a single-host IncusOS homelab (dual-Xeon / ZFS) running ~20 services and several long-running agent VMs, operated 24/7 by agents via an Agent Handbook + skills — plus a self-built multi-provider LLM gateway (GPT / Gemini / Grok / Claude) and multi-machine deployment. (Single-host homelab — not production multi-tenant scale.) - AI-native operator — drive a fleet of models across my own dev/agent work — ~10.7B tokens/mo through Claude Code (~97% cache-hit) plus ~14.4B tokens/mo across self-run harnesses (incl. Codex, OpenCode), ≈$23K/mo equivalent API cost (my own dev/agent consumption, not product traffic — a conservative floor).
- Open-source (github.com/2nd1st) — AIMA, an early cognitive-agent framework (TypeScript · Bun · Postgres/pgvector); api-log, an LLM-gateway recording proxy (Go); claudoros, a Claude Code focus monitor (Python). Also building: api-log-analytic (Go / SQLite / Svelte — large-scale LLM-traffic analysis & ingestion correctness) and loomomo (Rust — a baseline-delta CI gate that flags only the findings an agent's change introduced). (work samples; releasing.)
AR/AI Software Developer & Multimedia Specialist — Dreemar · Nov 2021 – Mar 2025 · Melbourne
Sole developer for the final ~1.5 years — effectively the entire engineering team: built, updated and maintained the frontend, backend, CMS, web editor and mobile apps single-handed, plus all production AWS operations (shipped a full app solo in year one). Worked in an Agile team for the first ~2 years before becoming sole developer.
- Built ARI-AI — an early-stage multi-agent AI marketing-content SaaS (pre-users), solo, end-to-end, deployed on AWS: Next.js + TypeScript frontend (NextAuth, Prisma); a Python CrewAI multi-agent backend; a LiteLLM gateway across OpenAI + Anthropic with a deliberate Claude-for-orchestration + GPT-for-content split; and full observability (Langfuse tracing/cost, Prometheus) on a Dockerised multi-service stack with CI/CD.
- Shipped 6+ AR apps to the App Store / Google Play (Unity / C#) — mostly kids' education AR, including a Deakin University collaboration and Victorian Tech School apps; Dreemar's broader app portfolio has tens of thousands of downloads. Also DreemXR (React Native) — a downloadless cross-platform marker-tracking AR app (iOS App Clip + Android Instant App).
- Maintained the AR Online Editor / CMS (Angular · .NET · Unity-WebGL editor); built immersive AR/3D experiences and the platform's spatial analytics — position/orientation capture for session replay, attention targets, popular paths, and dwell-time patterns; produced multimedia/design assets.
Earlier — Game Developer (self-employed, Unity / C#, 2020–21) · Digital Designer intern @ Triangle Financial (web + AWS, 2020) · Graphic Designer intern @ MountainTop Education (2019).
Education
University of Technology Sydney (UTS) — Bachelor, Game Design (with Interaction Design coursework & capstone) · graduated with High Distinction · FEIT Dean's Letter & Dean's List.