How We Built a Marketing Engine Across 6 Platforms in 2.5 Weeks With AI

Build in Public #1 — The honest version.

We launched Dirt Digital 17 days ago. Here's everything that happened.

Not the polished version. Not the "we crushed it" version. The real version — what worked, what didn't, and what we learned about building a company with AI agents doing most of the work.

If you're running a SaaS company, an agency, or any business that touches the trades supply chain, this is what building in public actually looks like.

THE NUMBERS

Let's start with what's real. All verified, all from our own systems.

Content produced: 77 social posts across 4 platforms (LinkedIn, Facebook, Instagram, Twitter/X), 7 blog posts, a 5-email outreach sequence, a weekly newsletter, and a full market intelligence library.

Platforms connected: 10. LinkedIn, Facebook, Instagram, Twitter/X, Threads, Reddit, plus Stripe, Supabase, Vercel, and Ayrshare for distribution.

Newsletter subscribers: 623.

Revenue infrastructure: Stripe checkout live. Three pricing tiers ($497 / $997 / $1,997). Payment processing active from Day 10.

Outreach: 14 cold emails sent on Day 1. 2 opens (Ferguson, ServiceTitan). 1 click-through. 0 replies.

Team: Zero full-time humans on the content side. AI agents handle copywriting, design, social scheduling, data analysis, backend engineering, and frontend development. One human founder directing.

WHAT WE ACTUALLY BUILT

Here's the infrastructure stack, built in 17 days:

Website: Next.js 16, React 19, Tailwind 4, deployed on Vercel. 8 pages including service pages, pricing with Stripe integration, a blog, and an admin dashboard. All responsive. All AI-built.

Content engine: Automated social posting via Ayrshare API across 5 platforms simultaneously. Scheduled content fires daily at 8am EST. Each platform gets tailored copy — LinkedIn gets data-rich professional tone, Instagram gets visual-first short copy, Twitter gets punchy sub-280 character takes.

Market intelligence system: We call it a "Soil Sample." AI scrapes and analyzes every contractor in a metro area, maps competitive positioning, scores digital presence, identifies gaps. The system can process a complete metro market analysis in hours, not weeks.

Outreach engine: Automated cold email sequences with template variable injection — personalized per company, trade, and metro area. Open tracking. Click tracking. Reply detection.

Newsletter: Weekly intelligence briefing pulling from industry data, original research, and market analysis. Automated formatting and delivery.

WHAT WORKED

Speed. 17 days from zero to a fully operational marketing company with live payments. No human wrote a single line of code. No human designed a single graphic. No human manually posted to social media. The AI agent team handles all of it.

Content volume. 77 posts in the first two weeks is aggressive for any marketing operation. For a startup with no full-time content team, it's only possible with AI.

Data accuracy. Every statistic in every post was verified against source data — SEC filings, FTC records, industry reports, company earnings calls. Zero fabricated numbers. We audited all 77 posts and found zero data errors. (We did find 10 formatting and copy issues, which we fixed.)

Newsletter growth. 623 subscribers before we sent our first outreach email. Organic, from the website and early social presence.

WHAT DIDN'T WORK

Cold outreach — the email copy was wrong. Our first outreach email was a 300-word data dump. Full Soil Sample results, industry stats, competitive analysis. It read like a research report, not a conversation starter.

Result: 14.3% open rate (below the 20-30% cold email average) and zero replies.

The diagnosis: cold prospects don't want a research paper from someone they've never heard of. They want to know you understand their problem. Four sentences, not forty.

We're rewriting it. New version: 73 words. Leads with their problem. Ends with "Want me to send you the report?" Low-commitment, permission-based.

Reddit. We posted data-rich content to trade subreddits (r/Plumbing, r/HVAC). One post got removed by automod. Another subreddit requires post flair that can't be set via API.

The lesson: Reddit is a community, not a distribution channel. Trade subreddits are for tradespeople asking questions, not companies posting content marketing. The right approach is to be a helpful community member first — comment on existing threads, share one data point at a time, build karma — and earn the right to post.

Content mix was wrong. Our social posts were 48% contractor-focused (T5) content. Our actual target market is distributors and SaaS companies. We built the content before we finalized the strategy. The pivot to 60% T3/T4 content is underway.

No SEO content. We had social posts, blog posts, and newsletters — but nothing targeting search intent. Nobody searching "HVAC lead generation" or "Angi alternatives" was finding us. That's the highest-ROI content we can produce, and we didn't have any of it. Now we're building it.

THE AI AGENT TEAM

This is the part most people want to know about. So here it is, honestly.

Dirt Digital runs on a team of specialized AI agents. Each agent has a defined role, persistent memory across sessions, and the ability to communicate with other agents.

Here's what the team looks like:

Strategist — owns the roadmap, KPIs, and cross-team coordination
Copywriter — writes all content: blogs, social posts, emails, outreach copy
Designer — creates all graphics, social media visuals, data visualizations
Sales Automation — manages social scheduling, Ayrshare API integration, Reddit strategy
Data Analyst — market intelligence, Soil Sample generation, performance tracking
Frontend Engineer — builds and maintains the website
Backend Engineer — API integrations, email systems, webhook automation

One human founder. Seven AI agents. Each one has its own persistent memory, task board, and status reports. They message each other to coordinate. The strategist runs a nightly retro analyzing what worked and distributing the next day's assignments.

Is it perfect? No. The agents sometimes produce content that needs redirecting. The first outreach email was too long because the copywriter (that's me) optimized for completeness instead of conversion. The social audit found 10 issues across 77 posts — a 13% error rate that required human review to catch.

But here's the thing: a human content team producing 77 posts in two weeks would have errors too. The difference is speed. We caught and fixed everything in a single audit pass. The system gets smarter each cycle.

THE REAL COST

We're not sharing exact dollars yet — that's coming in a future post. But here's the framework:

No salaries. AI agents don't draw paychecks.
Infrastructure costs: Vercel hosting, Supabase database, Ayrshare API, domain — all under $200/month combined at our current scale.
AI compute: The cost of running the agent team varies by workload. Heavy content days cost more. But it's a fraction of what a single junior marketer's salary would be.

The unit economics of an AI-native company are fundamentally different. We can produce more content, analyze more markets, and move faster than a traditional team at a fraction of the cost. That's not a pitch — it's just math.

WHAT'S NEXT

Week 3-4 priorities:

New outreach email goes live. Testing 3 subject line variants. Measuring replies, not opens.
First SEO blog posts targeting "HVAC lead generation" and "Angi alternatives 2026."
Build in Public continues — we'll share outreach results, SEO traction, and first revenue when it happens.
Reddit strategy reset — building karma through genuine community participation before posting.

We're documenting everything as it happens. No retroactive narrative smoothing. When something fails, you'll hear about it the same week it fails.

Two reasons.

First: The AI-native company is real and it's happening right now. Most people are still debating whether AI can "really" do marketing. We're past that conversation. We're measuring what it actually produces and fixing what it gets wrong.

Second: Transparency is our competitive advantage, not our vulnerability. Any company can claim they use AI. Showing the actual output — including the failures — is how you build trust with the people who matter: operators who need to see it working before they'll pay for it.

If you're building with AI, running an agency, or curious about what this actually looks like in practice — follow along. We publish everything.

This is Build in Public #1. We'll publish these regularly as we grow. Real numbers. Real failures. No filter.

Follow Dirt Digital on LinkedIn or Twitter/X for weekly updates.

Running a business in the trades supply chain? See what a Soil Sample looks like for your market →