Independent builder / AI operations / Available for work

Paul Rodriguez.

I ran the operations.
Now I build the tools.

Ten years in business taught me where work gets stuck. Automating my real estate wholesale company got me building. Now I deliver sourced research, clean reporting, persuasive presentations, and websites that make your offer clear.

See finished deliverables → Discuss a project

Four focused ways to start

Buy a deliverable.
Not a vague promise.

Finished sample work you can inspect, download, and test. Each project starts with an agreed brief.

More work you can put to use.

Planning timelines begin after the brief and materials are complete; availability and revisions affect the final schedule. Samples are self-initiated and use synthetic data where noted. AI assists production; sources, calculations, and interactions are checked.

Built to be explored / Three independent samples

A little more range.

Creative coding, operational software, and a travel experience. Working browser demos, not commissioned client projects.

01 / Creative technology

Order. In motion.

Shape a living composition. Change its rhythm. Export your own poster.

Open Form Studio →

02 / Operations product

Good work. On its way.

Move jobs through a dispatch board with live metrics, filters, and CSV export.

Open Relay →

Elsewhere.

03 / Travel experience

Take the scenic route.

Choose an escape, adjust your budget, and download a personal itinerary.

Open Elsewhere →

For AI companies

Product ops and support systems

Turn support tickets, customer escalations, launch risk, and quality signals into tracked operating decisions.

For gig platforms

Marketplace workflow automation

Build routing, QA, onboarding, trust-and-safety, and operator dashboards that reduce manual coordination.

For founders

Fast internal tools

Scope one workflow, build a usable prototype, and document the handoff. Dashboards, CSV/API importers, and review queues.

Operator background 10 years in entrepreneurship, real estate, and service operations. Former real estate investing company CEO.

Builder mindset Comfortable using Codex, OpenAI APIs, dashboards, automation tools, and evidence-driven iteration.

Work style Useful fast, honest about limits, focused on revenue, customer experience, and execution proof.

Start with one defined project

What do you need delivered?

Share the output, deadline, and budget range. I'll review the fit and scope before any work begins. Please send redacted samples, not passwords or confidential customer data.

Open tickets 0 -

High risk 0 Needs owner review

SLA pressure 0 Breached or near breach

Revenue at risk $0 Enterprise/Growth exposure

Weekly Support Ops Report

Product operations signal

Launch Readiness Risk

Aggregates customer tier, SLA pressure, safety flags, and high-risk product feedback into release-review guidance.

0 Loading

Product Feedback Clusters

Roadmap Actions

Stakeholder Follow-Up Briefs

Trend History

Eval Evidence

Runtime gates, coverage, and review controls for the support triage workflow.

Eval Cases

Live OpenAI Readiness Runbook

Objective Audit

Control Matrix

Reviewer proof hub

OpenAI Product Ops Evidence Map

One-screen proof of support analytics, hiring outreach readiness, and live OpenAI quota remediation boundaries.

Proof Status

Eval Trace Explorer

Live Quota Remediation

Support Signal Analytics

Hiring Outreach Readiness

Hiring Action Board

Operating Cadence

Daily triage: review critical/high risk tickets and assign owners.
Launch supportability: route release-blocking issues to product ops.
Product signal: cluster recurring themes and push to roadmap review.
Executive update: summarize SLA pressure, revenue risk, and top asks.

Human Review Controls

Draft responses are never auto-sent.
Policy, privacy, and safety risks require owner approval.
Enterprise or public-sector issues receive escalation review.
Every AI label stays inspectable and overrideable.

Portfolio walkthrough

AI Product Ops Support Triage System

A working operations console that turns support tickets into prioritized actions, product feedback, release risk, and executive reporting while preserving human review controls.

6tickets triaged

9eval cases

0launch risk

$54.5krisk surfaced

OpenAI Role Fit

System Architecture

Client
Loads sample support data and calls local server endpoints.
Server
Keeps `OPENAI_API_KEY` server-side and exposes health, analysis, and release evidence APIs.
OpenAI path
Uses Responses API with Structured Outputs for auditable ticket classification.
Fallback path
Uses deterministic rules when live OpenAI quota or network access is unavailable.

Verification Stack

npm run test:api npm run eval npm run verify:publish npm run verify:deploy npm run verify:ci npm run verify:release

Release readiness requires publish readiness, live OpenAI diagnostic success, and OpenAI-backed eval success.

Current Release Truth

Publish and deploy verification pass.
API contract tests pass with traversal protection and no secret leakage detected.
Fallback evals pass across support, reliability, access, launch-readiness, and prompt-injection cases.
Live release remains pending until OpenAI quota allows `source=openai` eval output.

Talk Track

I built this as the operating layer I would want during an AI product launch: triage is structured, quality gates are explicit, customer-facing action remains human-reviewed, and release status is honest instead of hidden behind a green-looking demo.