APPLIED AI / TECHNICAL DELIVERY

Intelligence,
put to work.

I’m Tyler. I turn operational challenges into software, AI-assisted workflows, and systems people can actually use.

Designated AI Implementation Officer for the SpaceX security team. M.S. Computer Science. Builder with an operational perspective.

Explore my work ↘Run the workflow lab ↗

THE IMPLEMENTATION LOOP01 — 04

t↗HUMAN INTENT
MACHINE CAPABILITY

Understand the actual work.

Start with people, constraints, and the decision the system needs to support.

OPERATIONS → REQUIREMENTS → WORKING SYSTEMSSCROLL TO EXPLORE ↓

AI implementationSoftware & workflow designM.S. Computer ScienceFAA Part 107

01 / SELECTED WORK

Built around
the real problem.

From frontline operations to independent software products. Explore the decisions behind the work.

01 PROFESSIONAL EXPERIENCE

Operational insight.
Working software.

I created and implemented a dispatch program for the SpaceX security team, bringing firsthand operational knowledge into a software workflow.

RequirementsSoftware deliveryOperational workflows

Public overview · employer systems and internal data are not displayed.

WORKFLOW DESIGNILLUSTRATIVE MODEL

INCOMING REQUEST

↳

Bring structure
to the handoff.Request · Context · Ownership

01Capture the needMake context explicit✓

02Coordinate the workIdentify the next action✓

03Keep people informedMake status understandable↗

MADE EASY●INTERACTIVE CONCEPT

JOB READINESS

Ready means
ready.

Complete the requirements.
Watch the decision change.

Estimate approved 01 Waiver accepted 02 Deposit recorded 03

2 requirements remaining↗

Sample data · no actual signatures or payments

02 INDEPENDENT PRODUCT · IN DEVELOPMENT

Made Easy

A service-business workspace organized around a deceptively important question: is this job authorized to begin?

AI-assisted intake supports the workflow. Explicit rules determine readiness. The product connects estimates, approvals, deposits, and evidence to a shared job record.

Next.jsExpoPostgreSQL

ASTRA PILOT ACADEMYPROTOTYPE

107LEARN / PRACTICE / REVIEW

03 / TECHNICAL LEARNING

Astra Pilot Academy

A Part 107 learning-platform foundation connecting lessons, assessments, and progress views.

ENGINEER ZEROPERSONAL PILOT

01 understand(the_problem)

02 build(a_solution)

03 test(the_assumptions)

→ show_the_evidence_

04 / ENGINEERING ENABLEMENT

Engineer Zero

Evidence-led technical training exploring coding practice, visible tests, and release-quality gates.

02 / INTERACTIVE WORKFLOW LAB

See the decisions.
Not just the output.

A small demonstration of a big principle: useful automation makes uncertainty and human review visible.

01 / CHOOSE AN INPUTREQUEST NOTES

Try changing the location, priority, or description. Inputs stay in your browser. This demonstrates validation and routing; it does not call an AI model.

02 / WATCH THE HANDOFFS

01
IntakeRead structured request fields
○
02
ValidateCheck required context
○
03
RouteApply explicit review rules
○
04
Prepare handoffKeep a person in the loop
○

03 / INSPECT THE RESULT

Ready when you are.

Run a sample to see the decision, the reason, and the next action.

View structured output

No run yet.

INTENTIONAL DESIGN

Incomplete context pauses the handoff. Safety concerns require escalation. Automation supports the decision; a person owns it.

03 / HOW I WORK

The interface is
only the beginning.

I connect the operational need, the technical work, and the people who need to use the result.

01 / DISCOVERY

Understand the work.

Translate real constraints into requirements, clear ownership, and a useful definition of success.

02 / IMPLEMENTATION

Make it work together.

Connect interfaces, workflow rules, and data. Use AI-assisted development with deliberate review.

03 / DELIVERY

Make readiness visible.

Surface dependencies, test failure cases, document decisions, and help people adopt the result.

04 / THE PERSON BEHIND THE SYSTEMS

Technical curiosity.
Operational judgment.

My path runs through public safety, instruction, customer-facing technology, project work, and aerospace operations.

That experience shapes how I approach AI implementation: understand the environment, build something useful, explain it clearly, and take responsibility for the handoff.

M.S. Computer Science · AI focusB.S. Information Technology ManagementMBA, IT Management · in progressFAA Part 107 Remote Pilot

Professional background ↗

AUG 2024 — PRESENT

SpaceX

Security Officer Level 3

Additional responsibilities include designated AI implementation for the security team, workflow automation, dispatch software development, and FAA-licensed drone work for inspections and construction progress.

AI IMPLEMENTATION + OPERATIONS

CUSTOMER & PROJECT EXPERIENCE

Translate needs into action.

Software account work at Heartland, project support at Lowe’s, and field project direction at Workout Anytime inform my approach to stakeholders and delivery.

PUBLIC SAFETY & INSTRUCTION

Melbourne Police Department

Police, SWAT, and instructor experience built a foundation in clear communication, training, and decisions under operational constraints.

OPEN TO THE RIGHT CONVERSATION

Let’s put better
systems to work.

Exploring remote opportunities in AI implementation,
technical project delivery, and applied automation.

Start a conversation ↗View résumé ↗

LinkedIn ↗GitHub ↗

Intelligence,put to work.

Built aroundthe real problem.

Operational insight.Working software.

Ready meansready.