Shah Khan · Human Data - Finance Lead at SpaceXAI
A working record of ideas built to operate under real constraints.
01 / Selected work
The selected work spans a consumer product, a daily research engine, and two public strategy records. Open any project for the full case study.
Software designed around a specific human moment.
An organizer creates a board, invites the team, gathers messages through a share link, and delivers a locked reveal to the recipient.
No required signup, a create-first flow, honest delivery fallbacks, and a focused emotional use case shaped the product more than feature breadth.
Use the live product ↗Systems that connect observation, decision, and repeatable action.
A private research system that turns daily inputs into signals, portfolio context, and the briefs published through Alpha One.
Schedules, defined data handoffs, status checks, and recovery paths make it possible to understand what ran—and what failed.
Read the related note ↗Public outcomes supported by private research and execution infrastructure.
The public site shows performance, risk, holdings, benchmark context, and portfolio-manager briefs while keeping strategy logic private.
Live equity and drawdown, closed round-trips, a daily dispatch, and a 10-year backtest provide context without exposing the underlying strategy logic.
The investment-related projects are presented as software and research case studies, not investment advice.
02 / The throughline
That sequence connects the work: turn the idea into something useful, design it for real conditions, and make the outcome clear enough for others to evaluate.
A working product reveals the real constraints faster than a polished theory.
Scheduling, fallbacks, data contracts, and observability determine whether a build survives contact with reality.
Live products, dated records, and honest status make the work easier to understand and evaluate.
03 / Field notes
Short, attributed notes about AI systems, product judgment, reliability, and the choices behind the work.
The model matters, but I trust the system more when it has clear limits, shows its work, can recover, and someone owns the last action.
Read the note ↗A live track record forces disciplined data handoffs, explicit caveats, and a clearer distinction between an outcome and a story about that outcome.
Read the note ↗A focused consumer product can teach more about friction, trust, and emotional context than a sprawling feature roadmap.
Read the note ↗04 / About the builder
I’m Shah Khan, Human Data - Finance Lead at SpaceXAI. I also build independent products across consumer software, AI-assisted systems, and quantitative research. I like building the whole loop—from the interface people touch to the automation and safeguards underneath it.
What I buildProducts, data systems, automation, and operating workflows.
How I workSmall prototypes, explicit constraints, and measurable outcomes.
What I publishShipped products, live records, case studies, and field notes.
05 / Compare notes
I’m interested in thoughtful conversations about useful AI, product judgment, automation, and what it takes to move from prototype to operation.
shah@shahbuilds.dev