AI

Built in partnership with Owl & Co (Hernan Lopez, ex-Wondery/Fox/NatGeo) to determine what a streaming subscriber is worth once you combine subscription payments with ad revenue monetization. The model covers every major US streaming service (Netflix, Disney+, HBO Max, Hulu, ESPN, Peacock, Paramount+, and more), at the grain of individual plan, distributor, and billing cadence. Tech stack: Snowflake (warehouse, SQL transform layer), Sigma (semantic layer, editable write-back input tables, dashboards), Claude Code and Codex / MCP tooling (AI-assisted data modeling, SQL, and Sigma workbook builds), HTML/JS for client-facing dashboard prototyping. ...

Since I read Andrej Karpathy’s viral tweet back in April, I’ve wanted to tackle building a ‘second brain’ where an LLM handles the organization, thinking, and maintenance. For as long as I can remember, I’ve had the consistent urge to streamline all that I consume across articles, newsletters, posts, Tweets, YouTube videos, and everything in between. I even created a separate Household Manager harness to manage everything across our family and household. While my Rube Goldberg machine of cobbled-together processes and tools worked alright, the room for improvement grew starker as I learned about implementations that “rode the latest AI model” capabilities. The gap was sharpest around continual improvement that compounds over time: a system that gets smarter with everything you feed it, instead of starting over from zero each session. ...

Inspired by Andrej Karpathy’s “second brain” concept, this is a git-backed system where an LLM handles the organization, thinking, and maintenance of everything I consume and everything I build. Capture: Readwise Reader is the inbox and ingestion layer for articles, highlights, forwarded emails, and uploaded PDFs, plus Google Drive for working docs. Live external tools (DataCamp, Sigma, Snowflake, Gmail, Calendar) are queried on demand via MCP rather than statically stored, so structured, dynamic data sits alongside all ingested document knowledge. ...

With all of the investment in and implementation of enterprise AI, one would think that AI should be transformative for so many aspects of work. AI will drive higher revenue, increase efficiency, and improve productivity while transforming the toil of labor into a more enjoyable existence for knowledge workers. However, as has become common knowledge at this point, despite the seeming panacea that AI transformation is touted to be, the majority of businesses continue to not see a return on their AI investments. ...

Building an AI-native household management app designed for busy parents. Provides households with an intuitive application that learns more about your family and improves over time. Eliminates the setup, development, maintenance, API-cost tracking, and overall burden of building with Claude Cowork/Claude Code, while delivering a comprehensive household management solution that drives actionable workflows rather than piecemeal outputs, like an email digest of the week ahead. Tech stack: Next.js 16 (App Router), TypeScript, Supabase/Postgres, Claude API, Tailwind CSS + shadcn/ui, deployed on Vercel. Claude API calls run server-side. ...