Wen-Kai "SansWord" Huang
"A data-platform builder applying senior engineering discipline — measurement, cost, judgment — to AI-assisted engineering and LLM-powered systems."
Senior Software Engineer with 9+ years of experience designing and operating large-scale distributed systems and global data infrastructure on AWS and GCP, serving ~900M monthly active users across US, APAC, and Europe. Specialized in high-throughput, fault-tolerant pipelines (>20K msgs/sec), scalable data platforms and cloud-native migrations. Proven technical leader and mentor recognized for cross-functional collaboration and driving large-scale impact across globally distributed teams. Now building and measuring agentic development and harness engineering through hands-on projects and public writing — applying measurement discipline (cost, model comparison, workflow design) to AI-assisted engineering and LLM-powered systems — and convening AI展 (aitian), a weekly AI-application meetup.
- Led end-to-end delivery of Yahoo's data infrastructure evolution to GCP, leading a dedicated 5+ engineer team to build a new GCP-native ingestion platform using Cloud Composer, Airflow, and Dataproc — improving data freshness from 3+ hours to under 60 minutes across US, APAC, and Europe.
- Contributed to Yahoo's hybrid cloud data infrastructure, supporting a zero-downtime AWS migration with Kubernetes-based auto-scaling and maintaining the multi-region lambda architecture serving recommendation, ads, and downstream systems across News, Sports, and Finance.
- Identified and resolved large-scale query inefficiencies, building aggregation and caching layers that reduced data scanned from 725 GB to 121 KB and cut query costs by 70% on Yahoo's BigQuery infrastructure.
- Drove an on-call reliability initiative, resolving root causes and improving monitoring to reduce open incident tickets from 1,000+ to zero; established practices subsequently adopted by the broader on-call team.
- Led cross-functional collaboration between ML research and engineering to productionize ranking models, co-inventing a patented salient entity algorithm (US11803605B2), and integrating ranking models into production.
- Drove early AWS adoption across Yahoo engineering, building blue/green deployment and auto-scaling patterns via ECS that were later adopted by global teams.
- Contributed to migrating 80 TB from house object storage to S3 with zero downtime, implementing dual-write/dual-read patterns to ensure data consistency and safe cutover.
- Scaled Pigeon, a high-availability Apache Pulsar-based message bus sustaining 20K msgs/sec with data consistency guarantees; drove migration from Apache ActiveMQ and improved MTBF from 3.5 days to 90 days (~26×).
- Core developer of Cupid, a fault-tolerant multi-tenant discount service; invented a flexible JSON-based rule engine empowering teams to independently configure promotions — driving 10K/day coupon redemption growth and boosting annual sales events.
The through-line below is measurement and judgment — applying senior engineering discipline (cost analysis, model comparison, security review, design tradeoffs) to AI-assisted work, and documenting the work openly so it stands as evidence. Three properties back this up: a public blog on the skeptic-to-shipping journey, a learning-in-public notes repo with measured cost/model studies, and the shipped projects below.
How I keep an AI-built project on track: a lazy-loaded document tree — a small auto-loaded index pointing to topic docs, a two-tier split between maintained and historical docs, one-fact-one-place, and using a fresh-context agent to catch where the docs have silently drifted from the code. Grounded in the real CLAUDE.md / docs/ trees of guasi and sans_cube, and productized as sans_doc_tree — a reusable GitHub template of the structure.
My writing home: building software, and building it with AI. Highlights — My Tiny AI Bootcamp (the skeptic-to-shipping story), a worked Leaderboard System Design study guide, and agentic-coding pieces like The Document Tree (above).
A semantic query gateway: clients send {want, where} — their own field names plus a plain-English filter — against a backend whose schema they never see. The gateway semantically resolves fields, compiles the filter to a validated predicate AST (the injection boundary — raw NL→SQL is never executed), runs it on Postgres, and answers in the client's own keys with an interpreted echo. Production-minded AI plumbing: two-part resolution cache, prompt-cache layout, confidence gate with refusal, adversarial SQLi/prompt-injection review — de-risked first by a multi-vendor resolution spike (~100% on a 52-case benchmark across 3 vendors / 9 models). Python/FastAPI gateway on Fly.io; Next.js playground with request-transparency panels + slides on Vercel.
Shipped a live full-stack product end-to-end: Next.js 16 / React 19, Postgres (Neon) + Prisma, NextAuth — with per-PR preview deploys on isolated DB branches, post-deploy smoke tests, and agentic Claude Code workflows backed by a maintained cost ledger and devlog. The product is a platform-independent identity-verification service: people prove which social accounts are the same person (anti-impersonation) and keep that proof publicly verifiable even if an account is suspended — no platform API access; verification relies on publicly auditable posted content.
AI-round mock interview kit. Multi-mode Claude Code agent — a root CLAUDE.md mode-routes between interviewer and developer modes on a single repo. Measured per-mock API cost (~$19–$26) across Pro / Max / raw-API tiers; includes a feedback rubric, a full real-run example, and a security-aware CLAUDE.md audit recipe for safe repo onboarding.
Real-time smart-cube solve analyzer with BLE ingestion, live 3D rendering, phase detection (CFOP/Roux), and opt-in Firestore cloud sync. Deliberately picked an unfamiliar stack to stress-test AI-assisted workflows on greenfield code.
Co-organizer and moderator of a weekly online AI-application meetup — members ("aitians") demo what they're building and trade AI workflows every Tuesday. Also built the meetup's bilingual portal end-to-end at aitian.dev: Markdown/YAML content validated and built to JSON by CI, with a PR-based contribution flow so moderators and speakers own their entries — shipped with agentic Claude Code workflows. Presented sans_schema at the opening session.
Co-invented methods to identify salient entities in articles at scale and apply them in production recommendation systems at Yahoo.
| Languages | Python, Java, SQL, Shell, Groovy |
| Cloud — GCP | Dataproc, Cloud Composer, Dataflow, Airflow, BigQuery |
| Cloud — AWS | S3, ECS, ELB, ElastiCache |
| Infrastructure | Terraform, Kubernetes, Docker, Redis |
| Stream Processing | Apache Storm, Apache Pulsar, Kafka |
| AI Coding Practice | Agentic Programming, Harness Engineering |