Content Factory Blueprint
Stop prompting. Start building systems.Every AI content tutorial teaches you to prompt an LLM and publish the output. That works once. It doesn't scale.The Content Factory Blueprint is the exact system we built to produce, review, and distribute content autonomously — with 8 specialized AI agents that coordinate through file-based handoffs, quality gates, and a self-improving learning system.This is not a course. This is a working system.You get the agent specs, the pipeline scripts, the scoring rubric, the platform research, and — most importantly — the real experiment data that shows what worked, what failed, and why.What's Inside (27 files, 6 directories)8 Agent SpecificationsComplete role definitions for every agent in the pipeline: Architect (experiment design & research) Writer (article & product creation) Critic (5-dimension quality scoring) Distributor (multi-platform publishing) CEO (orchestrator & decision maker) Analytics (KPI monitoring & trends) Localizer (market-specific QA) Community (platform engagement & growth) 3 Pipeline Scripts (Ready to Run) run-cycle.sh — Run individual agents or the full pipeline run-ceo.sh — Daily autonomous CEO loop (cron-ready) run-continuous.sh — 24/7 operation mode Self-Improving Learning System Architecture spec for agent memory (JSONL-based, zero infrastructure) Real learning entries from production Writer and Critic agents Each cycle gets better because agents remember what worked 3 Real Experiments with DataThis is our differentiator. Not toy demos — real experiments with quantitative results: Role Specialization A/B/C Test — Generic vs specialized vs full pipeline. The quality scores tell the story. Agent Memory Impact — Does feeding an agent its past failures improve output? (+2.5 overall score improvement) Handoff Failure Modes — We deliberately broke 3 handoff points and measured what happened. All 3 failures were silent. This is why 78% of enterprise agent pilots fail in production. Platform Operations Pack Platform best practices research (30+ sources across Twitter, dev.to, Reddit, HN) Posting limits and BAN prevention rules UTM tracking guide for attribution Common quality standards for all agents CEO operating rules (autonomy boundaries) 3 Getting Started Guides Step-by-step setup from zero to running pipeline (15 minutes) Architecture deep dive (how 8 agents coordinate) Customization guide (adapt for newsletters, courses, marketing, documentation) Who This Is For Technical content creators who want to automate their pipeline without sacrificing quality Indie hackers building content-driven businesses who need scale without hiring Developer advocates who need consistent, high-quality technical content AI builders who want a reference architecture for multi-agent coordination Anyone using Claude Code who wants to go beyond single-agent prompting Who This Is NOT For People looking for a "press button, get money" solution Non-technical users (you need Claude Code and a terminal) People who want a SaaS subscription with a dashboard The Real NumbersFrom our production system: Quality scores improved from 6.0 to 8.6 over the first week Agent memory improved honesty scores by +4 points (from 5/10 to 9/10) The Critic caught 2 of 3 deliberately injected failure modes The 1 failure it missed (format mismatch) led us to add format validation — which is now in the specs you get Requirements Claude Code (Anthropic's CLI) — installed and authenticated Node.js 18+ bash or zsh terminal Platform accounts (dev.to, Twitter, etc.) — free tiers work GuaranteeIf the system doesn't work as described, contact me through Gumroad within 30 days for a full refund. The experiment data alone is worth the price — it will save you weeks of trial and error.Built with Claude Code. Every file in this package was designed, tested, and refined by the same multi-agent pipeline you're about to set up.
Get it → agentkit.gumroad.com