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Joaquin Abondano

Joaquin Abondano

Twenty years building businesses. Three years deploying AI systems inside them.

COO of a NASDAQ-listed company. I built the operating system my own team uses: ten agents across six departments, monitoring, drafting, routing, and escalating real work every day. The methodology is called the JBOT Protocol.

  • NASDAQ COO
  • 65% sales growth in 2025
  • 27+ countries
  • 10-agent ops fleet
  • 101 daily automations
  • $20M+ prior company scale
  • Walmart / Target / Amazon

COO at Innovative Eyewear (NASDAQ: LUCY). Based in Miami.


current

2024–

COO at Innovative Eyewear (NASDAQ: LUCY)

Building smart eyewear for the voice-first future.

Business decisions have never been faster or more consequential. The executives who will lead the next decade are not waiting for AI to mature — they are deploying it now, inside real organizations, against real problems.

At Innovative Eyewear, I built operating infrastructure for a public company using AI agents. Not as a side experiment. As practical leverage for the work itself. The system runs across sales, marketing, fulfillment, supply chain, finance, and executive operations, helping the team move faster without adding proportional headcount.

What I believe: AI will do for decision-making what electricity did for manufacturing. It will not replace the people who run things, but it will fundamentally change what one capable person and a small team can do. The advantage will belong to companies that learn how to deploy these systems with judgment, controls, and operating discipline.


featured: jbot protocol

JBOT Protocol

The operating methodology behind my AI work: principles, architecture, deployment sequence, outputs, and governance for moving AI from demos into real business operations. It starts with business divisions, maps recurring decisions and workflows, then builds specialized agents with shared memory, tool access, human approvals, and executive escalation paths. Read the protocol →

The point is not unsupervised automation. The point is controlled leverage: routine work goes to agents, exceptions go to humans, and consequential decisions stay with executives.


recent thoughts

Apr 12, 2026

Building AI Operations in Reality

What it actually looks like to deploy AI agents in a real company. No theory. Just the parts (runtime, fleet, shared brain, channels), how they work together, and what I learned trying to make bots productive employees. Discord for the work floor. Telegram for the exec layer.

Apr 12, 2026

The Systems Flywheel

How AI operations get better with every deployment — and why each implementation makes the next one faster, cheaper, and more valuable. The real power isn't in the tool. It's in the methodology flywheel.

Apr 7, 2026

The Control Problem: Managing 4 Brands with AI Agents

When you run multiple product lines with a small team, the bottleneck isn't talent or budget. It's coordination. Here's how I'm building a system where the agents do the status tracking and humans just talk.

View all notes →


advisory

Advisory is downstream of the proof. I work with a small number of executives and companies each year when the work maps to what I have actually built: AI agents inside real operating workflows, with human judgment and business controls intact.

Best Fit

CEOs, COOs, and operators with messy real workflows, lean teams, and enough urgency to move beyond AI curiosity.

Outcomes

AI operations audit, agent architecture, automation roadmap, first deployed workflows, and practical governance.

Proof

Built from public-company deployment: 10 agents, 101 recurring automations, six departments, and real business systems.

AI Operations Audit + Roadmap

For companies ready to move from curiosity to implementation. I assess current workflows, systems, decision points, and approval paths, then identify where AI agents can create operating leverage without adding unnecessary risk. The output is a practical roadmap: first workflows, architecture, governance, and a sequence for deployment.

Deploy Your First 3 Agents

For executives and operators who want proof in the business, not another strategy deck. We choose three high-leverage workflows, define the human-in-the-loop rules, connect the right systems, and build the first agent layer so the team can see where AI belongs in the operating rhythm.

Send a paragraph to hello@jabondano.co on what you're trying to ship. I'll respond within a week if it's a fit.


ai & technical projects

Production AI systems. Built at a public company. Running operations across six departments. These aren't prototypes.

AI Agent Fleet — Production Operations

Ten specialized AI agents running daily operations at a NASDAQ-listed company — sales pipeline monitoring, fulfillment tracking, marketing intelligence, supply chain alerts, content generation, and financial monitoring. Each agent has defined responsibilities, institutional memory, and escalation logic. The system generates its own training signal over time. Built with Claude, deployed on VPS infrastructure, integrated with NetSuite, Shopify, HubSpot, Meta Ads API, and Amazon SP-API.

Production · Multi-Agent · 10 Agents · 6 Departments

EOS Operating System — AI-Powered Weekly Rhythm

Implemented EOS (Entrepreneurial Operating System) for a 6-person exec team using AI agents instead of manual tracking. Agents collect scorecard data across all channels, generate the L10 meeting agenda Sunday night, and send the Monday exec email automatically. Execs update their Rocks by replying to the email — no dashboard, no login. Built on Supabase, Gmail API, and Claude Haiku for intent parsing.

EOS · Real-time Ops · Supabase · Gmail API

Enterprise Systems — NetSuite, CRM, ERP

Full NetSuite ERP implementation for a NASDAQ-listed consumer hardware company. CRM infrastructure across B2B wholesale and DTC channels. Executive dashboards for real-time decision-making. Amazon SP-API, Shopify, and HubSpot integrations. The measure was not the software — it was whether leadership made better decisions faster.

NetSuite · Shopify · HubSpot · NASDAQ

Supply Chain & Global Operations

China factory relationship development across multiple product lines. AQL inspections, BOM optimization, and cost engineering. Global logistics across ocean, air, and land fulfillment at scale. Led ANSI Z87.1+, CSA Z94.3, and EN 166 safety certifications — getting complex hardware compliant across three regulatory regimes simultaneously.

Supply Chain · Compliance · Global Logistics

Legacy Products

X Drone: DTC drone brand with $20M+ in sales. WebRC: First toys-to-virtual-world platform built on Unity (licensed by Toyota, Hummer, GM). AppRC: iOS/Android apps with Bluetooth dongle to control RC helicopters. These products shipped at retail scale — Walmart, Target, Amazon, Canadian Tire.

Consumer Hardware · DTC · $20M+ Revenue

Most of this work is internal by nature. What's public is at github.com/jabondano.


press & publications

View all LUCY press releases →


timeline

2023

COO, Innovative Eyewear (NASDAQ: LUCY)

Joined to build operations infrastructure for a public company. Deployed the company's first AI operating system — ten agents across six divisions. Expanded distribution across 27+ countries. First COO at the company to integrate AI at the operating layer.

2012

Co-founder & VP Product, Groovy Toys LLC

Built from startup to $20M+ in annual revenue. Five hundred consumer products across mobile apps, multiplayer games, and IoT hardware. Clients included Walmart, Target, Amazon, and Canadian Tire. Operated across Hong Kong, Colombia, and Florida. This is where I learned that operations is the company.

2010

CEO, Funky Planet

E-commerce operation serving Target, Walmart, Amazon, Best Buy, Macy's. 200% increase in online orders. Led digital marketing across Google, Facebook, Amazon Ads yielding 20% ROI improvements.

2006

Business Development, Millbrook Ventures

Secured Environmental Impact Statement approval for $1.2B mixed use development in upstate New York. Created DCF valuation models and investor pitch books for hedge fund partnerships.

2002

Purdue University

BS Management with Minor in Finance. Graduated in 3.5 years.


expertise

AI & Automation

  • JBOT Protocol
  • MCP Servers
  • Claude/LLM Agents
  • Workflow Automation
  • NetSuite/Airtable

Operations & Supply Chain

  • China Manufacturing
  • Global Logistics (3PL)
  • ERP Implementation
  • Process Optimization
  • Vendor Management

Product & Commerce

  • Product Management
  • Mobile/IoT Apps
  • Multi-Channel (B2B + DTC)
  • Amazon/Shopify Plus
  • GTM & Distribution

Finance & Strategy

  • Financial Modeling
  • Investor Relations
  • SEC Reporting
  • M&A Due Diligence

Interests

  • Stoic Philosophy
  • History & Civilization
  • Systems Thinking
  • Human Nature

Real Estate Development

  • Commercial Projects
  • DCF/IRR Modeling
  • Investor Pitch Books
  • Entitlements

library

Books that shape how I'm thinking right now. These aren't beliefs set in stone—they're lenses I'm looking through, subject to revision. Intellectual humility means holding ideas loosely while engaging with them seriously.

0 Books
5 Categories

Philosophy & How to Think

0

How Leaders Built Things

0

Systems & Human Nature

0

Business & Strategy

0

Literature

0

bio

Joaquin Abondano is the Chief Operating Officer at Innovative Eyewear Inc. (NASDAQ: LUCY), where he leads operations and the company's AI transformation. The company posted 65% sales growth in 2025 and expanded distribution to 27+ countries.

Before Lucyd, he co-founded and scaled Groovy Toys to $20M+ in revenue — 500 products, three continents, a decade of building things that shipped. He holds a BS in Management with a Finance minor from Purdue University.

He is based in Miami. He advises a small number of executives and companies on AI strategy and implementation, with an implementation-first bias shaped by operators who have to make systems work in reality.

Philosophy: Stoic
Languages: English, Spanish (Native)

He reads obsessively — 200+ books across philosophy, history, systems, and strategy. He gravitates toward people who bring solutions and have skin in the game.


roots

Caribbean upbringing in a bilingual household. Eldest of brothers. Started working in the family business as a teenager, first trips to Asian factories before university. Competitive equestrian through adolescence.

Born in '83—analog childhood, figured out the internet as a teenager, built my first databases before most people had email. Now AI. I've watched companies adapt (or not) through each wave. That pattern recognition shapes how I think about tools and the people who choose them.