12
From the hardwood to the backend

Kyle
Young

I used to be the voice of the defense. Now I build the automation and AI systems that keep a whole business on the same page.

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01 / THE GAME

Where it
started

I come from a family of athletes. My parents both competed at Syracuse University, my brother played basketball at Northwestern and Duke, and my sister played volleyball at GW and Rhode Island. Watching my brother thrive in AAU basketball, I followed right in his footsteps. It got serious my junior year of high school when the college interest and scholarship offers started coming in. I went on to play collegiate basketball at Siena College in upstate New York, then at Flagler College in St. Augustine, Florida.

02 / THE LESSONS

What the game
taught me

Basketball taught me most of what I live by. How to put in work alone and how to win with a team. How to manage my time, take a loss and learn from it, and make the right call in a split second. How to lead, and just as important, how to be led. My job was anchoring the defense, and the hardest part was when five guys weren't on the same page. The fix was always the same: over-communicate. If the defense was out of sorts, that was on me. I still work that way.

03 / THE SWITCH

The next
season

In college I got hooked on how SaaS companies actually run behind the scenes: the backend, the marketing strategy, and the UI decisions built around human behavior to lift conversion and cut churn. On the court I was always about efficiency, and that carried straight over. It clicked when I started talking shop with people who did this for a living. I'd go from automation to backend engineering in the same conversation and sometimes lose them along the way. That's when I realized I had picked up more than I thought, and it pushed me to keep teaching myself.

04 / NOW

Building
the machine

I started out running an automation service, building AI workflows in n8n for a handful of clients, but the goal was always to build a SaaS company and scale it. Today I build the campaign, automation and AI systems behind a large marketing operation, and I'm building OpsHarbor on the side. Everyone has single AI agents doing single tasks. Nobody had given them a board: one controlled place where agents work together as a team, nothing big happens without your yes, and budgets never fly off the rails.

05 / OFF THE CLOCK

Not really
off

I golf, but honestly this doesn't feel like work. AI and automation are my hobby, so my free time usually goes into building better systems and tools. I've also gotten good at explaining technical things in plain English, because I was that person once. When I'm learning something new, I ask for a basketball or golf metaphor until it makes sense, and I use the same trick to explain it to whoever I'm talking to.

1K+Hours saved a year
50+Automations shipped
1SaaS in beta

Selected
Work

Systems I've designed and shipped: campaigns, automation, data, and AI. Click a project to read more.

Ops
Harbor
In beta

OpsHarbor.io

Stop managing AI agents. Run an AI company.

A team of AI agents set up like a real company. A CEO agent plans the work and proposes the team, managers hand out tickets, and specialists do the work. You act as the board: you approve hires, set budgets, sign off on anything risky, and can read every conversation.

Org chart & hiring · Decisions inbox · Spend limits · Bring your own AI key · 400+ integrations

Visit opsharbor.io →
At Cardone

The
Toolkit

What I work with every day. Hover over a skill to light up the tools behind it.

Skills
  • Lifecycle & email marketing
  • Marketing automation
  • CRM operations
  • AI agents & assistants
  • Data, attribution & reporting
  • API integrations
  • Self-hosting & infrastructure
  • Security & monitoring
  • Social & video content
  • SMS campaigns & compliance
Infrastructure & code
LinuxDockerGoogle CloudCaddyCloudflareTailscalePostgreSQLPythonJavaScriptGitHubTrivyFalcoDocker Bench
Automation & AI
n8nClaudeAnthropic APIZapierResend
Platforms & SaaS
HubSpotGoHighLevelAlowareBigQueryNetSuiteMonday.comZoomGoogle WorkspaceSocialPilotHeyGen
Always on

Running in the
background

I don't wait for things to break. A set of scripts runs on a schedule, reports into my admin portal, and pings me the moment something looks off.

Canary attack tests

Scheduled tests act like an attacker and try to break in, so I find the weak spot before someone else does.

Falco: always watching

A security camera on every running container, flagging suspicious behavior the moment it happens.

Trivy + Docker Bench

Every image is scanned for known vulnerabilities, and every host is audited against Docker security benchmarks.

Multi-tenant guardrails

Scheduled checks confirm each tenant's data, budgets and access stay walled off from every other tenant.

Standard procedures

SaaS-grade runbooks for backups, cleanup and maintenance run on their own and log every result.

Reporting & alerts

Every result lands in the admin portal, and notifications are wired up for anything that needs a human.

How I think

The
Playbook

Fix the offer
before the copy

When something isn't converting, the instinct is to rewrite it. Usually the offer is the problem. A strong offer survives average copy; great copy can't save a weak offer.

Value before
the ask

Every email, popup, signup and upgrade prompt earns its moment first. Show people the benefit, then ask for the commitment, never the other way around.

One change
at a time

Measure the baseline, change one thing, and let the numbers decide. Small wins multiply when you stack them, and guessing doesn't stack.

The playbooks

Pick a strategy

These aren't slides. Every playbook below is built into my AI automations on n8n and loaded into my agent configs as skills and instructions, so the agents work the same way I do.
The Interview · StrategyRec
Q.Where does a campaign actually start for you?
With the offer. If the offer is weak, no email or ad is going to save it. Once the offer is right, I work out who it's for and the one thing I want them to do, and everything gets built backwards from that.
Q.What's the biggest mistake you see teams make?
Sending more instead of sending better. Blasting the whole list feels productive, but segmenting, suppressing the right people and giving every message one job is what actually moves the numbers.
Q.How do you decide what to automate?
If someone does it twice the same way, it's a robot's job. Copying data between tools, rebuilding the same campaign, chasing the same report. But anything that reaches a customer stays off until a human has looked at it.
Q.What's next?
OpsHarbor. It takes everything I've learned running automations and lets a business run a whole team of AI agents like a company, with a human sitting as the board.
How I run it
    What I watch
      Where it runs