Agent 2 / YouTube Research Agent
Runs three Playwright passes on YouTube using the top 15 keywords: default sorting, filtered to the last 12 months, and filtered to the last month. For each search, it plays a "Ceiling/Floor Game" — comparing high-view titles against low-view titles to extract what copy patterns are earning clicks.
Agent 3 / X (Twitter) Research Agent
Pulls roughly 5,000 tweets across five searches: viral brand mentions, competitor frustration, trending conversations, customer pain language, and launch post formats. Every tweet gets tagged by function: WEAPON, HOOK-AMMO, BODY-AMMO, CTA-AMMO, or CONTROVERSY-AMMO.
Agent 4 / Reddit Research Agent
Mines the top 6 subreddit threads for high-upvote comments about frustrations, failed alternatives, and "I'm about to quit" scenarios. Every quote gets an emotion tag (FRUSTRATED, DESPERATE, ANGRY, HOPEFUL) and a usage note explaining how it can be deployed in the script.
Agent 5 / Industry Research Agent
Hits competitor pricing pages, G2 and Trustpilot review pages, and industry stat sources. Extracts exact pricing tiers, hidden fees, top complaints, and market-level numbers with full source attribution.
Agent 6 / Research Compiler Agent
Waits for all four research agents to finish, then synthesizes everything into a 50-to-100-nugget base organized by what each downstream writer needs: hook ammo, body ammo, proof ammo, CTA ammo, and controversy ammo. Nothing gets invented. The compiler sorts and prioritizes what the research already found.
Key Takeaway The research phase produces real language from real people on real platforms. No AI-generated assumptions. Every nugget traces back to a tweet, a Reddit comment, a YouTube title, or a verified stat.
Writing and War-Testing Every Hook
The hook pipeline and the giveaway pipeline run in parallel. Each goes through its own adversarial review cycle.
Agent 7 / Hook Writer
Writes 5 distinct hooks, each built on a different framework: Standard Raise, Visual Demo, Mission-Based, Creative Format, and Wild Card. Each framework gets filled with brand-specific details pulled from the brief and the nugget base.
Agent 8 / Hook Manager
The adversarial gatekeeper. Reviews all 5 hooks against a 10-point binary checklist:
- Does it contain a specific number?
- Does it use a violent verb?
- Does it name an enemy?
- Is it under the character limit?
- Does it avoid every banned word?
- Is it specific to this brand, not a generic template?
Then it runs a Library Dominance Test, comparing each hook against their best-performing historical hooks. Default position is REJECT. The writer gets up to 3 rounds of revisions with surgical instructions.
Agent 9 / Giveaway Writer
Writes 2 CTA options following the Sacred CTA Flow: named giveaway, specific contents, proof stat, dollar outcome, platform-specific trigger words.
Agent 10 / Giveaway Manager
Pulls real high-performing giveaway posts from X as live benchmarks, then adversarially reviews both CTA options against a 15-point checklist. Also runs a Library Dominance Test and an X Reference Comparison Test. Default: REJECT. Max 3 revision rounds.
The Hook Agent alone writes 4 hooks with 3 full rewrites each. Nothing moves forward until it scores 10/10. This is why their hooks consistently outperform — they are tested against real data before anyone ever films.
Seven Agents Refine Every Line of the Script
This phase runs sequentially. Each agent receives the body from the previous one and makes targeted upgrades before passing it forward.
Agent 11 / Body Writer Writes the full demo walkthrough: 7+ narrated steps, 2+ "intelligence moments," and a specific business scenario grounding the demo. Agent 12 / Weapons Specialist Upgrades 2-4 lines using Economy Killers, Savage Comparisons, Subtle Controversy, Mission Alignment, Technical Flex, and Confidence Bets. Agent 13 / Controversy Specialist Inserts 1-2 subtle controversy lines tied to who loses when the product wins. Tests for screenshot-worthiness and taste. Agent 14 / Technical Specialist Upgrades every technical line to name specific technologies, data sources, and counts. No vague language allowed. Agent 15 / Flow Specialist Scans for AI-written tells: repeated starters, fake drama, banned transitions, corporate filler, passive voice, and hedging. Agent 16 / Body Manager Final adversarial gate: 15-point checklist, Library Dominance Test against the 2 best library bodies. Default: REJECT.
Agent 17 / Fathom Checker (Brand Advocate)
Re-reads the full client transcript from the intake call and acts as the brand's internal advocate. Default position is REJECT. It asks: Does this script capture what actually makes the product special? Does it use the founder's exact phrases? Does it reflect what the client emphasized on the call?
The Fathom Checker does not write. It only routes surgical fix instructions back to the specific agents who need to make changes. This keeps the brand voice authentic to the founder, not the AI.
Three Final Gates Before Delivery
Agents 18 and 19 run in parallel. Agent 20 runs last.
Agent 18 / Mom Test
A binary clarity check on every sentence. Flags anything a non-technical 55-year-old would not understand: jargon, acronyms, industry shorthand, assumed knowledge. Rewrites flagged sentences using plain-language patterns.
Agent 19 / Call Supervisor
Checks the full assembled script against the Fathom transcript one more time: feature coverage, emphasis alignment, hook-to-body expectation matching, giveaway logic, and tone recognition. Flags genuine misrepresentations or important omissions.
Agent 20 / Final Review
Three passes:
1
Slop Scan
16-point check for filler words, vague language, and anything that sounds like it was written by a chatbot.
2
Phase Completeness Check
Confirms every required element made it through the pipeline. No missing hooks, no dropped CTA options, no gaps.
3
Character Count + Style Match
Enforces 1,400-character max and scores against the style library. Assembles the final script with all approved hooks, body, and CTA options.
The Bottom Line 20 agents. 5 phases. 6+ adversarial gates. Default position: REJECT. What survives this system is a script that has been researched against real platform data, war-tested line by line, and verified against the founder's own words. That is why their launches average 2 million views per video.