For Zach Yadegari's stealth founding team · Founding Marketer

Hello, Zach. I think I'm your founding marketer.

Bold thing to say to someone I haven't met yet. But I don't just build product — I engineer growth. I've spent years shipping the software behind LatAm sportsbook retention, and the black-hat distribution machine that makes content spread: phone farms, per-post content uniqueness, propagation at scale. Solo, from Guatemala, with Claude Code. I saw your video. I'm in.

Marcelo García
Marcelo García · "Chelo"
CRM & Player Retention Leader — Sportsbook & Casino · Founder, ChatPuesta · ex-Head of CRM, ChatBet
📍 Guatemala City → open to relocate · 🌐 EN / ES native · ⚡ ships with Claude Code every day
See the real results → WhatsApp me →
SCROLL
Growth engineeringPhone farms + ADBContent uniquenessDevice-identity spoofingVideo propagation at scalePlayer RetentionChatBetKambiDigitainBetPlayWhatsApp Business APIClaude CodeLatAm, from the inside
// Track record — real companies, real numbers

Six years turning attention into revenue.

I've owned CRM & retention for regulated sportsbook and casino operators across Latin America — the commercial side that actually moves GGR. Here's the receipts.

Platforms, operators & brands I've worked with and for
ChatBet Kambi Digitain BetPlay 1XBET
ChatBet Head of CRM · 2025–2026

I led retention for a real conversational sportsbook.

ChatBet lets bettors place bets inside WhatsApp & Telegram — natural language turned into a betslip on the operator's sportsbook. I owned player lifecycle, segmentation and retention strategy across live LatAm operators, on a platform integrated with Kambi and Digitain and deployed with BetPlay, betvip and Betcris.

WhatsApp / Telegram Kambi + Digitain integrated LatAm operators live
chatbet.gg ↗
ChatBet Proven Success: +20% monthly GGR, +30% 90-day retention, +35% new bettors, +30% average wager size ChatBet's own published operator results — chatbet.gg
Founder · CRM Director

ChatPuesta

2026 – Present · current venture

My own conversational CRM for LatAm sportsbook players: segmented, fixture-triggered campaigns over WhatsApp/Telegram, with in-chat bet placement. Early-stage — building the retention engine and the product at the same time.

Conversational agentWhatsApp API
Head of CRM

ChatBet

2025 – 2026

Led CRM, engagement & retention for the conversational betting platform above — segmentation, reactivation and bonus mechanics across operators running both sportsbook and casino, with a WhatsApp Business (Meta) delivery layer.

+30% retention*+20% GGR*Kambi · Digitain
CTO → Senior CRM

Unifymedia · Playgreen

2023 – 2025

Shipped a WhatsApp betting product with the operator's CPO and ran mass WhatsApp campaigns timed to kickoff and in-play moments of live football — a repeatable weekly format that pulled players in at peak intent.

Product + CRMEvent-triggered
CMO · CRM Director

ACTA Managers

2023 – Present

Creator-management agency doing $31,000/month at its peak. I drove that revenue with AI-driven content — and built ACTA OS, the full internal ERP the agency runs on (see below). Growth and engineering, same person.

$31K/mo peakFull-stack ERP
Creative + Strategy

MelBet & 1XBET · via BCKBN Social

Campaigns

Produced influencer video content and the full implementation plan for MelBet's UGC programme, and designed a 3-tier influencer acquisition campaign for 1XBET — two of the biggest betting brands in the world.

UGC programmeInfluencer acquisition
The through-line

I think like the funnel

I register at operators as a real player, go silent for six days, screenshot every lifecycle message they send — and don't — then hand the Head of CRM a one-page audit: "your first 72 hours are leaking players." Retention is a reflex.

Retention obsessed

* +30% 90-day retention and +20% monthly GGR are ChatBet's own published operator results (the "Proven Success" figures on chatbet.gg), attributed to the platform — not claimed as my personal numbers. I never invent a metric.

// Growth, engineered — where I'm genuinely dangerous

Building it is half the game. I make it spread.

Anyone can make one video. I built the machine that turns one asset into hundreds of native-looking uploads across accounts and platforms — and gets them past the filters that kill reposts. This is the black-hat distribution muscle most engineers simply don't have.

Distribution at scale

Real hardware. Real accounts. Zero rate limits.

A rack of Android phones driven over ADB, posting to dozens of accounts on human-like schedules. Hardware distribution doesn't trip the API rate limits and bans that instantly kill server-side posting — it looks like real people, on real devices, because it is.

ADB device control Multi-account drip Human-paced scheduling
phone farm · propagating
01 · uniqueness

Content uniqueness at scale

The same creative, made unique for every upload: per-post device-identity & metadata spoofing across 63 real device profiles (ExifTool), re-encoding, and subtle transforms — so each platform reads it as native, first-party capture, not a flagged duplicate. One video becomes a hundred without getting suppressed.

02 · pass the filter

Publish-health forensics

Before a single post, my Inspector shows exactly what a platform's ingest scanner sees: container atoms, claimed device, C2PA credentials, AI-generation likelihood, and a per-platform publish-health score. I know if content will pass before I spend a post on it.

03 · the pipeline

End-to-end propagation

Discover → clean & re-encode → uniquify → schedule & drip → post across accounts → verify. Runs 24/7, self-healing, as a Windows service. 266 videos propagated, 270 device-identity injections audited with before/after snapshots.

This is growth-hacking / distribution engineering for social content — the same category as aggressive UGC and repost farming. It's grey-hat by platform ToS, and I run it on my own accounts and content. The point: when a product needs to grow, I don't just buy ads — I can manufacture organic distribution as an engineering system.

// A little about me

Guatemala City → wherever you're building.

I'm a kid born and raised in Guatemala City. I went through an American high school here, so my English is near-perfect and Spanish is home — which means I understand the Latin American market from the inside, not from a slide. That's rare, and it's an edge.

I've been building things since I was a kid. It's the only thing that's ever really held my attention. When I found out what Zach and Blake were doing — the YouTube, Cal AI, shipping real products young — I got obsessed. That became the life I wanted: build something that matters, get to the Valley, be in a house full of people who are the best in the world at this.

Here's the honest part. Guatemala doesn't have much of a culture for this — no ecosystem, no scene, no obvious path. I built one anyway. Taught myself, shipped systems solo, and ran real B2B relationships with operators across LatAm. I'm hungry in a way that's hard to fake, and I want to upscale my life by doing the work, not talking about it.

I don't want a job. I want in.

Marcelo García
📍 Guatemala City 🇬🇹 → the Valley
// The unfair part

A marketer who ships his own tools.

Most growth people file a ticket and wait two weeks. I open Claude Code and build the system myself. These are production tools I designed and shipped solo — the reason I move faster than a marketer who has to wait on engineering.

Agents that take real actions, not just chat

JobHunt OS operates my Gmail (IMAP), 13 different ATS platforms, and a live browser session end to end. ZEBRA drives Instagram, YouTube and the Meta API. I've been building this class of agent for months.

Deciding what to say when nobody asked

My Command Center is a proactive agent: it decides on its own when a failure, a deadline, or a shipped result is worth a Telegram ping — and when silence is the right call. Signal over noise, by design.

Where to draw the line on autonomy

I've drawn it in production. JobHunt OS never fabricates a screening answer, never bypasses a CAPTCHA, caps applications per company, and routes anything irreversible to me for a one-tap approval on my phone. Autonomy with brakes.

Demo works, production fails

I treat verification as sacred: an application is only "confirmed" when a real inbox email proves it. Evidence for every action (2,500+ screenshots). I've debugged the regex-OOM, the empty-SPA render, the silently-miscoring bug — from production data.

When Claude's output is "correct but generic"

I tell it to stop designing like a template: commit to one strong reference, kill the defaults, name the exact type ramp, spacing scale and one signature interaction — then iterate on the seams. This very site is the artifact of that loop.

What I'm building right now, outside of work

A dozen live systems — an AI video factory (reelforge), a Shopify competitive-intel crawler (shopscope), a multi-account lead listener (telelistener), and this portfolio, built by a 7-agent research harness that mined 3 years of my own work.

// What I build, solo, with Claude Code

A dozen live systems. Here's the short list.

Each is an agent or tool I designed, coded and shipped alone. Numbers are live production counts — not mockups.

🎯

JobHunt OS

Autonomous agent: scans ~300 boards, fills & submits ATS forms, reads the emailed code from Gmail to finish — zero touch.

Node · Playwright · IMAP
397applications
🎬

ZEBRA

24/7 content agent: watches Instagram, cleans & enhances video with FFmpeg, injects device identity, auto-posts to YouTube/IG.

FastAPI · React · FFmpeg · ExifTool
266videos
🛰️

Command Center

Proactive mission-control dock: launches & monitors every project and pings my phone over Telegram on its own.

Electron · Node
11projects
🏢

ACTA OS

Full internal ERP run by an AI executive team (CEO/CMO/CTO agents); the CTO agent shipped code via PRs.

React · Express · Prisma · Postgres
65data models
🎞️

reelforge

6-stage AI-video factory: reel → frames → transcript → Claude-compiled prompts → generation queue. Every stage idempotent.

Python · Whisper · yt-dlp
117clips
🔬

Forensics Inspector

Drop a video, see what a platform's ingest scanner sees: metadata, claimed device, C2PA, AI-likelihood, publish health.

Python · C2PA
270audits
🕵️

shopscope

Point it at any Shopify store; Playwright crawls it and emits a design system, component inventory, copy teardown, build plan.

Node · Playwright
8artifacts
📡

telelistener

Monitors Telegram & Discord across many accounts, scores every message 0–10 for buying intent, forwards the hits.

Python · Flask · Telethon
0–10intent score
// The one that proves the range

I ran a company with an AI executive team.

ACTA OS is the full-stack operations platform I built for a creator-management agency that hit $31,000/month at its peak. Clearest proof that I can take a real business and build the entire agentic system it runs on — alone.

0
Prisma / PostgreSQL data models
0
Commits on the staging repo in ~6 weeks
0
AI executives: CEO, CMO & CTO agents
0
Peak agency revenue it helped run
The AI executive team

I ran the org through Paperclip with CEO, CMO and CTO agents. The CTO agent shipped code through feature-branch PRs against a protected staging repo that I visually reviewed before merging to production. Agents that build, guardrailed by a human.

Three portals, 232 backend files

An Admin Command Center (40+ pages), an Employee Workspace (15 role-specific dashboards), and a Model Portal (earnings, invoices, content, tickets). Express + React 19 + Vite + Tailwind 4, on Railway, Neon & Render.

Real-workforce automation

A signed Electron app drives anti-fingerprint browsers so staff operate managed accounts without ever seeing passwords; a 17-day account-warming state machine; clock-in gated on live screen-share presence with idle detection.

A dozen integrations, wired solo

Discord.js, Telegram Bot API, Google Drive + Calendar, Calendly, Recurrente payments, Gemini for morning briefs & AI captions, Bull/Redis queues. One person, the whole stack.

// Why me, specifically

A marketer who actually builds.

Short and specific — the way you asked for it.

Zero-to-one is my normal

I've stood up CRM functions from first principles and built the software they run on, with no team and no budget. That's the founding-marketer job at a startup, and I've done it repeatedly.

Grind + taste + Claude Code

Exactly the stack you named. Agentic coding isn't a tool I tried — it's how I ship every day, across a dozen live systems. Speed is my edge; JobHunt OS was idea-to-verified in a week.

I bring an unfair growth edge

Most founding engineers can build. Few can also make it spread — phone farms, content uniqueness, propagation pipelines. Cal AI won on distribution as much as product; I've shipped distribution as an engineering system. That's rocket fuel.

I ship things that run without me

Self-healing services, idempotent pipelines, real verification, evidence for every action. I build for production and for the on-call at 3am, not for the demo.

Credentials-out, output-in

I did two years of a CS degree and left to build. Like you, I bet on shipped work over pedigree. This whole page is the argument, made in the medium.

I'll relocate and go all-in

Guatemala City → anywhere your small team is. Well-funded, stealth, shipping to real users, hardware on the way — that's the room I've wanted to be in my whole life.

"Why work on an AI product you can't see yet?"

Because I've spent years quietly building the exact kind of thing you're now funding — with nobody watching and no equity in the upside. You're offering the one thing I've been missing: the best team in the world at this, a real product, and a reason to go all the way. I don't need to see it. I already believe in the shape of it.