Data & AI Architect
I integrate software and AI applications in enterprise settings, build digital products, and write about innovations in tech.
Writing
Why building a concept map beats studying one, why the untyped wikilink throws away the information you needed, and how to layer embeddings, LLM triple extraction, and structural gap detection on top without letting the machine author your graph.
A full technical walkthrough of building a governed write-back interface on Microsoft Fabric Apps with the Rayfin SDK — static hosting, Entra ID SSO, and a server-side functions proxy to an existing REST API, with no separate web app to maintain.
A practical guide to DQX, the PySpark-native data quality framework from Databricks Labs that quarantines bad data before it reaches your gold tables.
A technical deep dive into PaperBanana, an open-source agentic pipeline that generates publication-quality methodology diagrams and statistical plots from text.
Why Stanford's DSPy framework treats prompts as compiled artifacts, and how GEPA — the ICLR 2026 Oral — outperforms reinforcement learning with 35x fewer rollouts.
Exploring Microsoft Research's Data Formulator, the concept-binding paradigm, and how its AI agents remove the tidy-data tax from visualization authoring.
How the Open Service Broker API turned the N x M problem of platform-service integration into N + M, and how it fits alongside Kubernetes Operators today.
A walkthrough of turbovec, a Rust + Python vector index built on Google Research's TurboQuant algorithm — 16x compression, faster than FAISS, no codebook training.