Spencer Connaughton is a founder and technical leader with 10 years of experience building applied AI and systems-level software from research to product. He led zero-to-one efforts at X’s Moonshot Factory on generative-AI solutions for real estate and served on Project Hamilton at the MIT Media Lab, giving him rare experience at the intersection of digital currency, regulation, and scalable system design. Currently founding GGX to build AI tools for traders, he combines hands-on backend engineering with product intuition informed by earlier work in algorithmic trading and AR/eye-tracking interfaces. An active contributor to infrastructure-focused open source, he added Cassandra (CQL) support to a prominent SQL builder/ORM, showing deep expertise in database dialects and query interpolation. Spencer pairs rigorous engineering (MIT, dual BS in EE and Math) with a taste for tackling domain-specific complexity across finance, real estate, and emerging interfaces. Colleagues describe him as someone who deliberately chooses “interesting problems” and assembles interdisciplinary teams to solve them.
10 years of coding experience
9 years of employment as a software developer
Media Lab – Digital Currency Initiative, Media Lab – Digital Currency Initiative at Massachusetts Institute of Technology
Bachelor of Science (B.S.), Electrical Engineering, Bachelor of Science (B.S.), Electrical Engineering at Southern Methodist University
High School Diploma, High School Diploma at The Field School
A flexible and powerful SQL string builder library plus a zero-config ORM.
Role in this project:
Back-end Developer
Contributions:6 commits, 4 PRs, 3 comments in 4 months
Contributions summary:Spencer primarily contributed to adding support for the CQL (Cassandra Query Language) database flavor to the SQL builder library. Their work included implementing CQL argument compilation, interpolation, and support for CQL-specific features such as blobs, timestamp interpolation, the NOW function, and update IF statements. The user also updated documentation and incorporated CQL support into existing tests, demonstrating a focus on database interaction and SQL dialect compatibility.
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