Aerospace systems engineer learning to orchestrate AI. Domain expertise in NASA human-rated
spaceflight + demonstrated ability to build products by directing frontier AI models.
Published researcher on complexity in high-reliability organizations.
The Shift: Task Automation → AI Orchestration
My career arc mirrors Marc Andreessen's thesis on AI and work: jobs are bundles of tasks,
and AI automates tasks, not entire jobs. In aerospace, I learned systems thinking, safety-critical
design, and integration under NASA human-rating standards—skills AI can't replicate. The atomic
tasks (calculations, simulations, document synthesis) are increasingly automatable. The valuable
work is orchestration: defining objectives, selecting/directing AI tools, validating outputs against
domain constraints, and iterating.
I'm teaching myself to become an "AI orchestrator" in the Andreessen sense—someone who tells AI
how to build products. Not "coder" or "engineer" in the traditional sense, but a hybrid: domain
expert + AI workflow designer + product builder.
Current Work: AI-Orchestrated Product Development
bigBespoke LLC (2024-present): Building copapp.ai—an
AI-powered platform for improving law enforcement decision-making under pressure. This is AI
orchestration in practice: I direct Cursor (AI pair programmer), frontier models (Claude, GPT),
and Firebase services to build fullstack architecture I couldn't have coded from scratch two years ago.
React frontend, Node backend, OIDC + PKCE auth, rate limiting, multi-tenant data models, Stripe payments.
I orchestrate the AI agents, validate outputs, integrate pieces, write domain content (PERF/ICAT guidelines),
pilot with real officers, iterate. No customers yet—still learning the orchestration patterns.
This demonstrates the emerging skill: I don't write every line of code, I direct AI to generate it,
then apply domain judgment (security, architecture, user experience) to validate and refine. The job
is less "write React components" and more "orchestrate AI tools to ship a product that solves a complex
human-systems problem."
NASA Artemis Experience
Beyond Gravity (2022-2025): Systems engineer for SLS Block 1B
Universal Stage Adapter—the composite structure connecting Orion to the rocket for
Artemis 4+. Owned requirements integration, risk management, human systems safety
documentation, and compliance with NASA human-rating standards. Spent 12 weeks in
Sweden resolving NASA-standard compliance for the Payload Separation System with the
Leidos-Dynetics prime. Navigated DoD and NASA projects spanning Army/Space Force
requirements, DOORS traceability, and MIL specifications.
Background
Cal Poly Aerospace Engineering (2014-2021): Conducted research on
complexity management in high-reliability organizations under faculty guidance (2020-2022).
Published at AIAA SciTech 2022 and INCOSE Detroit. Led spacecraft C&DH and ground systems
for senior capstone (interstellar object intercept mission). Competed with Cal Poly Hyperloop
team at SpaceX—top 22 worldwide, authored test manuals and ran braking system experiments.
Princeton Airport (2016-2017): Flight Coordinator managing schedules
for 60+ student pilots and 100 renters. Earned Private Pilot License in 2017.
What I Offer
Domain expertise in safety-critical systems: Requirements integration, verification/validation,
human systems safety, NASA human-rating standards, DOORS traceability, risk management, compliance navigation
(MIL specs, DoD/Army/Space Force requirements). This knowledge is hard for general AI to replicate and increasingly
valuable as AI handles routine engineering tasks.
AI orchestration capability: Demonstrated ability to direct frontier AI models (Cursor, Claude, GPT)
to build production systems. Not just prompting—full workflow orchestration: planning, task decomposition, tool selection,
output validation, integration, iteration. Built CopApp fullstack using AI-augmented development from zero knowledge.
Hybrid mindset: I go wide (aerospace, software, research, human factors) but can dive deep when needed.
Comfortable working alone (building products end-to-end) or in large teams (NASA/prime contractor environments). The
through-line: understanding and building systems that improve human decision-making in complex, high-pressure environments.
Future-positioned: Not "aerospace engineer" or "software developer" in traditional silos—more like
"AI-augmented systems architect" or "AI orchestrator for complex domains." I'm learning to be the person who defines
what needs to be built, orchestrates AI agents to build it, and validates it against domain constraints that matter
(safety, reliability, human factors).
