We Run Our Own Marketing With AI
Most AI agencies outsource their marketing to freelancers. We built two autonomous agents that plan, write, and publish our content — and they're better at it than any human team we've had.
See It LiveThe Content Scaling Problem
Four articles a month. That's what we managed with human writers. Each piece cost $200–$500, took a week from briefing to publication, and needed two rounds of editing because the writers didn't understand our domain deeply enough.
The content wasn't bad. It was generic. Surface-level thought leadership that read like every other AI consulting blog. No original data, no internal links strategy, no keyword architecture — just isolated articles published whenever someone had time.
We needed 10x the volume at higher quality with a systematic approach to organic growth. So we built what we'd build for a client — but for ourselves.
Meet Mitra — The Strategist
Every Sunday, Mitra pulls real performance data from PostHog, audits all existing content, identifies gaps, and creates a 7-day publishing calendar. No duplicates. No guessing.
Mitra doesn't guess what to write. It looks at what's actually driving traffic, what's declining, what keywords competitors are targeting that we haven't covered — and plans accordingly. Every piece it schedules has a data-backed reason to exist.
Meet Adam — The Writer
Adam executes Mitra's calendar daily. Each piece goes through a 12-step pipeline with two quality gates that reject generic, predictable content.
Expert Panel
Before writing, Adam generates 3 expert personas who debate the topic. The synthesis becomes the article's unique angle — ensuring every piece has a genuine thesis, not just a topic.
Surprise Test
Would a domain expert find this angle surprising or insightful? If the score is below 60/100, the content gets regenerated with a stronger thesis. No predictable takes get published.
Triple SEO Validation
Every piece passes three checks: technical SEO (meta tags, schema, structure), content SEO (keywords, readability), and AEO (AI engine optimization for citation readiness).
AI Content That Doesn't Read Like AI
The hard part of AI content isn't generation — it's quality control. Anyone can prompt an LLM to write a blog post. The output will be fluent, structured, and completely forgettable.
We spent months hardening our framework until generic content physically cannot get through the pipeline. Here's what enforces quality at every step:
Don't Take Our Word for It. Read It Yourself.
Every blog post, glossary entry, and audio summary on this site was planned, written, validated, and published by Mitra and Adam. No human writers. No editors. Just the framework.
Blog
40+ articles on AI implementation — comparisons, case studies, academy lessons, weekly roundups. Each with auto-generated audio summaries you can listen to on the page.
Browse the blog →Glossary
AI/ML glossary entries optimized for AI engine citation. Concise definitions, real-world context, and structured for both human readers and LLM retrieval.
Browse the glossary →What Two AI Agents Deliver
From 4 articles a month to 40+. From generic content to data-driven pieces with unique angles. From manual publishing to fully autonomous — plan, write, validate, generate audio, commit, deploy. Every piece on our blog is proof it works.
Let's Talk
Have a challenge that needs AI? We'd love to hear about it.