"I play with code, but more often with ideas."
I am a Product & Technology Leader, entrepreneur, and startup advisor. I specialize in translating complex technology into product strategy, guiding organizations through AI & Data transformations, and advising early-stage startups.
While my day-to-day focus is on product leadership and strategy, I remain a builder at heart—frequently experimenting with new technologies and ideas.
| Category | Skills & Technologies |
|---|---|
| Strategy & Leadership | PM Strategy • Startup Advisory • Data Product Management • Experimentation |
| Data & AI/ML | Python • LLMs • Graph Databases • Agentic Workflows |
- PLAM: A local-first, multi-agent system designed to orchestrate local LLMs (via llama.cpp), manage hierarchical agents with complex memory systems (pgvector & JSONB), and safely run LLM-generated code inside Docker sandboxes. Optimized for CUDA acceleration on NVIDIA DGX Spark.
- Apache Superset (Contributor): Contributed to the data exploration, time-series, and database connectivity components of this leading open-source data visualization platform.
- python-cayley: An open-source Python client library designed to interface seamlessly with the Cayley graph database.
- Oscar2015-Dataflow: A Google Cloud Dataflow pipeline built in Python to process and analyze Oscar-related tweets in real-time.
LLM and simplicity
An AI agent just tried to hand-roll raw SQL queries for my new product's backend.
The goal? "Keep it simple." The reality? A massive architectural risk disguised as clean code.
Lately, my LinkedIn feed has been flooded with trendy frameworks pushing AI to write tiny, hyper-minimalist code—think of the "Caveman" or "Ponytail" development concepts, or even Karpathy's four rules for agentic coding.
As a product executive who leans into modern AI workflows, I love the philosophy of radical simplicity until I look at the output with a critical eye.
On Apple intelligence
Everyone is calling Apple’s new Siri "too little, too late."
They are fundamentally misunderstanding how Apple wins.
A lot of people are making the same mistake Sam Altman did: assuming Claude and ChatGPT are directly competing with Siri. They aren't.
Foundational AI models are currently an Enterprise game. The handful of tech enthusiasts paying $20 a month for personal AI are a rounding error.
Siri is pure Consumer. And in the consumer hardware market, the rules of the game are completely different.
Lack of Product Integrity
A simple trip to McDonald's today revealed a hidden flaw that breaks countless digital products.
I call it a lack of "Product Integrity."
Here is what happened: My family and I were ordering at the digital kiosk. Right before paying, I decided to remove the fries from my order. I clicked the button clearly labeled "View Order."
Instead of simply showing me my cart, the app forced me through the entire multi-step checkout funnel just to let me delete one item.
A long time ago, in university, I conducted research on cryptography. I still bring that same curious mindset to my daily work.
- ForwardDiffSig: Co-author of The ForwardDiffSig scheme for multicast authentication, published in the IEEE/ACM Transactions on Networking, focused on secure and efficient multicast network authentication.
- Merkle Trees: Co-author of On the Performance and Use of a Space-Efficient Merkle Tree Traversal Algorithm in Real-Time Applications for Wireless and Sensor Networks, published in the IEEE International Conference on Wireless and Mobile Networking and Communications, focused on optimal techniques to traverse Merkle Trees.
- Forward Secure Signatures: Co-author of An Optimized Double Cache Technique for Efficient Use of Forward-secure Signature Schemes, published in the PDP2008: 16th Euromicro Conference on Parallel, Distributed and Network-Based Processing, focused on making Signature Schemes with Forward Security usable. Forward Security is the property by which the signature remains valid even if the private key gets compromised.
