Distribution Strategy
Distilled viral-engineering knowledge from every reel Tommi has sent into @jarvis.moove. Pattern-level operational learnings, organized to actually use before shipping a piece of content.
Who Cicero is for
Before the playbook: the customer. Cicero is the travel software layer — vertical on the user, horizontal on the use case. Consumer + enterprise on the same rails.
Vertical on the user. Horizontal on the use case.
Cicero is the travel software layer, not a vertical app. One person travels many times a year — Rome in April, Cortina in December, Seychelles next summer, a Tuesday business trip to Berlin. Every trip is a different surface. Cicero is the constant companion across all of them.
Competitors pick a category and serve it well — itinerary, audio guide, booking, group ops. We bet on the user instead. Same user, many trips, many contexts. The cost of switching apps is the wedge.
The traveler, every trip they take
Lifestyle-first brand. Travel-as-lifestyle, Nude-Project-tier register. The app becomes the muscle memory of “I'm going somewhere — open Cicero.” KPI: visit → install (8% target), install → activated (50%), D30 → refer (15%).
Agencies, hotels, schools, destinations
Cicero as software-as-service for travel businesses: Cicero for schools, Cicero × Terralto, Cicero × Manerba del Garda, Cicero per Ideeperviaggiare. The B2B layer that compounds against the consumer brand. Pricing model: SaaS + per-trip + revshare hybrid.
Trastevere walks with audio narration. Louvre off-hours playbook. Marais coffee crawl. Micro-routes around opening hours, the right gelato every 400m. Cicero as live guide.
Offline-first island map, conservation context, reef briefings before each spot. Cicero as remote concierge.
Rifugi route + weather window + via-ferrata grading. Cicero as alpine companion when signal is bad.
Lift map, wind exposure, après-ski curation. Different season, same Cicero, different surface.
Whatever the user's traveling for, Cicero adapts. Example: school trips — per-class itinerary, parent visibility, supplier coordination · cicero-schools-agency lives here.
Every trip type is a Cicero context. We don't pick verticals — we adapt to the user's verticals.
The 5 distribution layers
Before tactics: the taxonomy. Every dollar and every post belongs to one of five layers, differentiated by who produces the content and how trust transfers. Same TikTok video has different math depending on which layer posted it.
Media company
· Our own productionEverything we publish directly. Brand-owned channels + founder personal brands. The editorial layer — register, voice, taste sit here.
Ambassadors · UGC
· Creators making for usPeople (and synthetic actors) who produce content we sponsor or commission. Not their own audience — our brand's. Volume layer that the media company curates.
Influencers
· Their audience, our messageCreators who own their own audiences. We borrow that trust. Strategic — opens markets, builds permission. Most expensive per view but highest conversion quality.
Paid
· Buying the reachDirect ad spend. Not for raw view volume (CPM is uncompetitive vs organic) — for conversion, retargeting, amplification of organic winners, and search intent.
Non-linear
· Compounds over timeNot a posting cadence, not a $/view buy. Long-tail surfaces that pay back over months and years. The layer that creates institutional gravity.
Why layers, not channels. Channels are where content shows up (TikTok, IG, LinkedIn). Layers are who's producing it and how trust transfers. The same TikTok video is layer 1 if our brand posts it, layer 2 if a UGC creator does, layer 3 if an influencer does. Different math, different conversion, different cost — same platform.
How to begin
Cross-source distillation: Hormozi, Chris Chung, Quinn Fulmer, Jordan Watkins, Emonee LaRussa, Martin Wang, James Ricci.
- 01First 3 seconds own everything — visual pattern break, tone shift, or unusual claim.
- 02Clarity beats cleverness. 3rd-grade reading level (Hormozi: 'the swamp' > 'are you a unicorn').
- 03Speed-to-value. Zero intro. Hook → benefit → substance.
- 04Impact audio: quiet intro → abrupt loud transition shocks attention onto the video.
- 05High-contrast visual: light↔dark, location shift, color swap.
- 06Weird behavior or relationship angle triggers comments + shares.
- 07Swap trick: cut the outro, put it first. Old intro at the end loops it back.
- 1.Action hookVisual stopping power
- 2.Big ideaFrame of the video
- 3.Huge claim + statMakes the promise concrete
- 4.First-person footageAuthenticity
- 5.Tone shift"But what you don't see…"
- 6.Coming-up sectionHooks the scroll-stayer
- 7.Dark-psychology exposureCreates WTF curiosity
- 8.Roadmap"Today I'll show you…"
- 9.Unique mechanismWhy only this video delivers
High-TAM idea · Curiosity hook · Super hook · Speed-to-value · Net-new value · Tension script.
POV mouth-open · objects appear · blow-into-camera · feet-to-person whip-pan · appear-from-clothes.
Find a song with quiet intro → abrupt loud chorus. Use the transition as your hook. Contrasting visual on the beat. Ship.
Carry the promise, resolve the loop
No filler. Cause → effect chains. End on a positive note so the dopamine of the payoff converts to a follow.
- • No filler / no “white bread” words (Ronny Mitchell).
- • Logic chains: cause → effect → cause → effect. Each sentence sets up the next.
- • B-roll every 0.5–1s keeps scroll-stayers engaged.
- • Delayed music: hold silence until the interesting beat, then music drops.
- • Non-obvious take: earn the “never heard it said that way” dopamine.
- • Authenticity cues: fake Snapchat overlays, candid framing, imperfect lighting.
- • Resolve the hook. If you promised “how I hit 10M views”, the last 5s must land it.
- • Positive conclusion. The Guy's 119M-view video ends giving money to a tow-truck helper → viewer feels good → follows.
- • Don't deliver curiosity too early.
- • Never “like and subscribe” filler — kills the watch-through.
- • Viral loop option: end with something that loops back into the hook (swap trick).
- • Non-obvious take as closer. Not “follow me” — a line that makes them want to.
The 4 drop-off patterns
Oney Araújo's diagnostic — read the retention graph, find the shape, apply the fix.
A/B-test 3-5 per day, change one word / music / clip-order. Elijah Sullivan: 5k → 25k followers in 4 months on this. Sam Gaudet: 50M views in 2025 by shipping variants repeatedly.
Post two versions same day — one fast-speech / clean background, one slow / messy — read the delta. Clean BG + faster speech wins statistically.
The 8-step operational playbook
Tommi's directive (2026-04-23): we copy the day after a viral pops, or a couple hours after if it’s that viral. Infrastructure must support 2-24h turnaround.
- 01Cancel ChatGPT sub, move to Claude.
- 02Open IG, follow 10 biggest accounts in our niche (travel + AI tourism + Italy).
- 03Engage with 5 pieces of content per account → program the For-You page.
- 04Scroll FYP — any video > 10k views gets flagged.
- 05Pull account → Instagram-TikTok-Sorter (free tool) ranks their top content.
- 06Each viral video = a problem. Give it to Claude + our unique methodology.
- 07Remove all filler. Apply cause→effect logic chains.
- 08Post 2/day minimum for 3 months. Guaranteed viral.
AI face-swap account hit 2.7M followers + 324M-view videoin one month by copy-remixing real creators. Direct proof speed-to-copy wins.
1M-likes viral travel reel. Perfect template to adapt per-city across the 26 EU countries.
Pre-made CapCut travel template — 22k likes — literally copy-paste. Speed-to-ship infrastructure embodied.
The production menu
Six AI-UGC stacks, all proven. Human UGC pricing benchmarks. Chase Chappell's 6-step automation playbook — the engine that makes 26 countries × 2B views possible.
- 1.Launch on TikTok Shop, automate thousands of creator invites.
- 2.Let sales data reveal the top 1% creators — rank by actual sales, not views/likes.
- 3.Move the top 1% into a private community (output-optimized).
- 4.Share the top-performing videos; community studies + learns the pattern.
- 5.Each creator delivers 5–10 more videos; Meta co-creation follows.
- 6.Automate the whole loop. Build a UGC library of thousands of unique ads.
| 1 video + 2 hooks + 3mo usage | $600–900 |
| 1 ad + 6mo usage | $600–750 |
| 2 ads + 60d whitelisting | $1,900 |
| 3 videos + 3 months | $2,160 |
| 4 videos (scope-creep) | $2,770 |
Brian Blum economics: brands now pay zero-follower creators $1,500 / 10 videos + 10% commission. The follower game is dead in the creator-economy subsegment.
How many of each, posting how often
The math behind 2B views. Cadence is fixed by channel type (AI UGC 2/day, UGC 1/day, influencer 1/2wk, AI influencer 4/day). Pick the mix and median views; the rest computes.
Channel mix calculator
Pick a view target. Adjust share + median views per post per channel. Posts/month per account is fixed by cadence. The math shows accounts needed, monthly cost, and blended CPM.
Higgsfield / Arcads — face-talking AI actors on brand accounts. Layer 2.
Real creators on contract · €99/mo + €20/video · 24 EU countries. Layer 2.
Strategic. 1 post / 2 weeks. Their audience, our message. Layer 3.
Persistent personas (Fluently-style). 4 posts/day. Layer 3.
Reach.cat · Lumina · TT/IG Shop affiliates · paid per view. Layer 2 + 3.
Meta · TikTok · Google · YouTube. Usually amplifies organic winners. Layer 4.
Defaults are realistic, not aspirational: TikTok median views are falling (-23% YoY per 2026 benchmarks); 2-5K views is the actual middle of the distribution. AI UGC 26% at 8K median. Human UGC 14% at 18K (trust signal lifts it). Influencers 7% at 250K (upper-micro tier). AI influencers 25% at 7K (warmed personas, not greenfield accounts). Clipping 25% at Reach.cat economics ($650/1M). Paid ads 3% at $5 CPM — small share because paid is for conversion not raw views.
AI influencer personas
A distinct goal from AI UGC. Persistent characters that own audiences in their own right. Fluently is the reference we'll build on.
AI personas as their own channel.
Separate from AI-UGC (face-talking actors on existing brand accounts). AI influencers are persistent persona accounts— named characters, consistent voice, recognizable look, posting continuously over months. Each persona is its own micro-brand. The emerging stack we'll evaluate: Fluently (the Tommi-flagged reference), plus TheInfluencer.AI, Higgsfield personas, and the character-consistency stack underneath (Nano Banana 2 + Kling 3.0 + ElevenLabs voice clones).
Higgsfield Supercomputer ships persona-consistent series at agentic-pipeline speed — proof point: a 23-minute sci-fi pilot in 96 hours with consistent characters. For AI influencers, this means one persona × hundreds of in-character posts/month at unit costs approaching zero. The 3-layer memory (brand-library persists the persona) is the unlock.
Higher than human UGC (1/day) and AI UGC (2/day) because cost floor approaches zero. Posting frequency becomes the volume lever.
Fluently-style — character is the asset, generation is near-free. ~$140 / persona / month at 120 posts.
One persona per major market, voiced and styled native. Same storyworld, country-specific surface. Stack against 26 EU + 10 world tier.
AI UGC is a creative format — face-talking actors for ad variants on brand accounts. AI influencers are an independent distribution surface— characters who own audiences in their own right and link back. They're only possible once the character-consistency stack (Fluently + Higgsfield) is reliable enough that the same persona shows up credibly across 100 posts. That moment is now.
26 EU countries + World tier
The verticalization map. 4 waves across the EU during 2026, World tier opening once Europe is at-regime.
Tier 1 · EU hero
5 highest-leverage EU markets. Where the AI-UGC engine runs first and the playbook hardens.
Tier 2 · EU expansion
High GDP-per-trip + outbound-tourism volume. Same playbook, localized creator pools.
Tier 3 · EU completion
Filling the 26 EU map. Lower priority, smaller creator pools, run lean.
Tier 4 · World
Outside the EU verticalization. Highest-LTV English speakers and outbound-tourism giants. Different playbook tuning.
How a new country opens
Influencer-first to earn cultural permission → activate TT/IG shops → open affiliates → layer AI-influencer persona for volume. Skip a step and the next is leaner.
Influencer-led entry
Open a new market with 2–3 strategic influencer collaborations. Trust + cultural fit > reach. Use the post to validate ICP and harvest the comments for next-wave AI-UGC scripts.
Shop activation
Once a market is warm, activate TikTok Shop + Instagram Shop with localized affiliate offers. The shop becomes the conversion surface for everything organic flowing in.
Affiliate flywheel
Open the affiliate program. Pay $1,500 / 10 videos + 10% commission (Brian Blum economics). Top 1% by sales joins a private community → 5–10 more videos each.
AI-influencer scale
Layer in Fluently-trained AI-influencer personas at 4 posts/day. Each persona is a localized character with consistent voice. This is the volume multiplier when the playbook is proven.
The order matters. Influencers buy us cultural permission. Shops give people a buy button while attention is high. Affiliates multiply the ad pool by the right kind of trust. AI influencers ride the proven playbook at fractional cost. Skip a step and the next one is leaner.
Where each layer ships
One brand, many surfaces — each with a distinct purpose and content shape. Layer assignment shows which production layers feed into each platform.
Mass-attention (lifestyle)
Where the 2B-views target actually lives. Algorithmic, short-form, high-replay.
Algorithmic discovery · #1 for cold reach
Content: Hook-led short-form · trial reels · sound-driven · 9:16
Aesthetic + saves + Reels engine
Content: Reels (trial) · carousels · stories · Shop integration
Long-tail SEO + Shorts engine
Content: Shorts for top-funnel · 8-15min for retention + ad rev
Travel-niche search + planning intent
Content: Vertical pins · destination boards · long-tail SEO
Brand voice · low-pressure ambient
Content: Witty short text · IG carryover · personality
Institutional / B2B
Where founders position. Lower volume, way higher per-impression value.
Founder positioning · enterprise pipeline · AI-SEO juice (50-66% of LLM citations)
Content: Long-form articles · founder essays · build-in-public · 1/week minimum
Niche · founder + dev community · earned media warming · open-source algorithm (engineer for replies, not likes — see strategy §17)
Content: Threads · build updates · contrarian takes (positive tone) · reply-bait open questions · API dead for new
Owned audience · long-form · email primitive
Content: Founder essays · weekly cadence · feeds LinkedIn + Reddit
AI-SEO #1 surface (40.1% of LLM citations) · long shelf life
Content: Native problem-first comments · never URLs · aged accounts
Vertical · techy · differentiator
Niche platforms that signal builder-credibility. Asymmetric — small audience, high trust.
Skills-as-distribution · install IS activation · dev-community trust
Content: Public Claude skills · `cicero-route-draft` style drops · READMEs
Designer community · brand-aesthetic vertical · unique-value-prop signal
Content: Community files · UI mockup posts · design-system drops
Traditional / non-linear
High-trust, slow-build. Where Cicero becomes a name your parents recognize.
Forbes · TechCrunch · Wired · Wall Street Journal Travel · institutional gravity
Content: Founder profiles · launch press · partnership announcements
Condé Nast · National Geographic · Travel + Leisure · category authority
Content: Itinerary features · destination guides · branded inserts
Corriere · Repubblica · TG1 · local TV · highest trust per unit
Content: Founder interviews · feature segments · local-pride angles
Per-country local media · per-city integrations · drive-time radio
Content: Cicero × [city] partnership announcements · seasonal stories
Who else is in the way
Researched May 2026 — actual products and creators we're competing with, not memory-guesses. Roamy + TripBff own the social-discovery overlap; Layla + Mindtrip lead AI planning; meta-search (Skyscanner/Kayak/Hopper) owns price-anxiety; Duolingo + Babbel + Lingoda are playbook sources we steal from.
Social-discovery → trip apps
Closest behavioral overlap. Like us, they turn social discovery into trips. Same user, same moment, different shape.
AI travel assistants
AI-first itinerary + booking. Well-funded category leaders own the chatbot/planning entry-point.
Audio guide / live narration
Same format space as Cicero's lifestyle layer — but mostly file-based, not contextual.
Tours & activities marketplaces
Supply giants. We don't compete on inventory — we compete on layer.
Travel meta-search / OTAs
They own price-anxiety attention; we want to own the trip itself. Sit upstream and downstream of Cicero.
Enterprise / agency software (B2B)
Where cicero-schools-agency, cicero-x-terralto, cicero-per-idv compete.
Travel-creator cultural surface
Not products — they compete with Cicero for the cultural surface area. Where attention sits if we don't show up.
Playbook sources (steal-from)
Adjacent verticals running the distribution playbook we want. Not competition — inspiration. Language learning has dominated TikTok-led growth for years.
Find the dominant format · industrialize it
The pattern Roamy and Duolingo both run: identify the 2-3 winning formats in your niche, mass-distribute them, become the niche's default. Format wins, then variation wins — the originator gets remembered.
Scan
Monthly format audit per niche × per channel. Spy on category leaders' last 30 days. Tools: SpyTok (TikTok creator-median outliers) · Vertical Viral (IG Reels · 300-10,000% baseline) · Meta Ad Library · BigSpy. Output: top 5 outperforming videos per category leader.
Identify dominant format
Across the top videos, find the 2-3 recurring formats. Roamy: "save TikTok spot → app demo → built-itinerary reveal" repeated across hundreds of variants. Duolingo: "Flicker / Flash / Flare" model — trend riff, episodic character beat, campaign surge. Look for what's repeated, not what's most-viewed.
Mass-distribute
Push the chosen 2-3 formats through 200+ Layer-2 UGC creators (Influee + AI UGC pool). Same skeleton, per-creator personality. The format is the carrier; the creator is the variation. This is Roamy's actual playbook — same format, hundreds of voices.
Become the niche default
When 200 creators in a niche use the same format for 60 days, the niche's algorithm-trained audience expects it. Other big players adopt it (free amplification). The format becomes synonymous with the category — and Cicero is the originator everyone's copying.
850M organic views · 143 videos >1M · ~$10K budget
Format model: Flicker / Flash / Flare.Flicker = high-frequency trend content. Flash = mid-effort episodic storylines (Duo · Legal Steve · Lily — sitcom universe). Flare = major campaign surges triggered by the “Pineapple” emergency button.
Workflow: “Spark to Post in an Hour” — draft to publish in 15-60 minutes. Top hits: 25M (Barbie premiere riff), 12M (World Cup meme), 1M in 3 minutes (twerking video). OKR: one viral moment per quarter.
Distribution model: in-house, not creators.Misfits team (illustrator + full-time trend creator + contracted college student + production assistant). Strategy: “Be the thing and subvert the thing.” Earned-media value: $6.5M against ~$10K spend.
Build a 4-person Cicero in-house Layer-1 team. Pick a recurring character beat (the lifestyle persona). Ship the “Spark to Post in an Hour” pipeline as our 24h-copy infra.
One format · 2-3 variations · ~200 creators
The dominant format: save-IG/TikTok-spot → app screen-record → auto-built-itinerary reveal. Roughly 2-3 visual variations of the same skeleton. Distributed across hundreds of UGC creators on TikTok over recent months.
The result:the format is now what people expect when they see “new travel app.” Other category players adopting it confirms the pattern. The originator (Roamy) becomes the association even when copies show up.
Why it works: all the value is in the demo (the screen-record). Skip the demo and the video is generic; lead with it and the value prop is self-evident in 6 seconds. Layer-2 UGC distribution is cheap because the creative load is on the format spec, not the creator.
Define 2-3 Cicero killer formats(e.g. “ask Cicero while walking → audio reveals the next 3 stops”). Ship via 200+ Layer-2 UGC creators in 60 days. Originate it before someone else does.
Format wins, then variation wins. Pick the right format-skeleton, mass-distribute the variations. The category remembers the originator. Roamy and Duolingo run different distribution models (mass UGC vs in-house team) but the underlying insight is the same: a small number of recurring formats, industrialized, beats endless one-offs.
2026-05-14 update:Higgsfield Supercomputer collapses step 03 (mass-distribute) — the agent ships 10-15 variants per scene batch, recursively QC'd, locked to a brand-library persona. The format spec becomes the only artisanal step; variation production approaches zero unit cost.
App Store Optimization
The 36-listing surface we run (26 EU + 10 World). 2026 algorithm shifts: Apple OCR-indexes screenshot text, retention now demotes installs that uninstall, 5-7 long-tail keywords beat head terms.
Keywords (the floor)
iOS gives you 100 chars of keyword field + 30 char title + 30 char subtitle = 160 indexed chars total. Long-tail beats head terms in 2026 — "audio guide florence dolomites" outranks "travel app". Google Play also indexes the long description, so write it for keywords too.
Screenshots (the conversion)
70%+ of installs are decided on screenshots alone — you never get a tap. Apple's 2026 OCR reads screenshot text and indexes it as keywords. First screenshot top-left needs the value prop + social proof (logos, user counts) — this can lift CVR up to 90%. Localize per market.
Ratings + retention (the gate)
2026 algorithm shift: Apple + Google now demote apps with high uninstall rates and low session frequency more aggressively. Ratings velocity (rate at which new ⭐s land) matters more than absolute count. Build the rating-prompt into the moment of activation, not at install.
Localization (our 26 + 10)
Each EU country = its own ASO build. Native-speaker keywords + region-specific screenshots + culturally-tuned subtitle. World tier (US/BR/JP/UAE/SA/AU/MX/KR/CA/IN) needs full localization too. Cicero's surface = 36 store listings, not 1.
ASO compounds — every install dropped by paid or organic that lands on an unoptimized page is wasted. The 36-listing surface is also a moat: per-country ASO done well is hard to copy because it requires in-language keyword research + culturally-tuned visuals at scale.
AEO + GEO · how AI engines cite you
ChatGPT cites 47.9% from Wikipedia (Bing-indexed). Perplexity cites 46.7% from Reddit (1-2 week freshness). Only 11% of domains rank on both — pick one to win first. There's a whole science: schema, refresh cadence, AI-bot allowlists, stat density.
ChatGPT
Wikipedia · Bing-indexedReal-time web search is Bing-powered — Bing indexing is non-negotiable. Bias toward established, encyclopedic authority. To rank: Wikipedia presence, schema-marked authority pages, recognized entity status.
Perplexity
Reddit · 1-2 wk freshnessHeavily weights freshness + community discussion. Indexes fresh content in 1-2 weeks. To rank: substantive Reddit comments in niche subs, rapid-refresh authority pages, sector-specific expertise signals.
Google AI Overviews
Google graph + schemaInherits classic SEO + entity signals. Schema markup (Organization · FAQPage · HowTo · TouristAttraction · LocalBusiness) is the lever. Already favored if classic Google rankings are strong.
Only 11% of domains are cited by both ChatGPT and Perplexity. Pick one to win first. Cicero defaults to Perplexity (rewards fresh + Reddit + sector expertise — our Substack + reels-research + Reddit pipeline maps cleanly). ChatGPT path is slower (Wikipedia earns out over quarters).
Schema markup as a first-class concern
Cicero needs Organization · FAQPage · HowTo · TouristAttraction · LocalBusiness · ItemList (for itineraries) JSON-LD on every relevant page. This is the structured-data layer AI engines parse directly. Most travel sites still skip it — easy edge.
robots.txt + llms.txt + AI-bot allowlist
#1 reason for zero AI citations: blocked or missing directives for GPTBot · ClaudeBot · PerplexityBot · Google-Extended. Audit cicero.app robots.txt this week. Ship llms.txt in 5 minutes — disputed efficacy, free upside.
Refresh-frequency as a citation lever
Pages updated every 7-14 days hold citation priority. Stale pages decay after 14 days in Perplexity's index. Cicero's destination pages should be on a 14-day refresh cadence — not big rewrites, just dates + new POIs + freshness tokens.
Stat density + entity claiming
Inject 1 statistic / 1 named source every 150-200 words on long-form pages. AI engines preferentially cite content with hard data. Pair with explicit entity claiming: "Cicero, the travel software layer founded 2026 in Italy by ..." — feeds entity recognition graphs.
The X algorithm is public · architect for it
xAI publishes the Grok-powered For-You algorithm on GitHub (Apache 2.0), updated every 4 weeks. Latest drop 2026-05-15: 187 files, 18K LOC. The math behind virality is now visible — and we can engineer content around it. Reply-driven conversations are 150× the leverage of likes; first 15 minutes after posting decide everything.
The order matters more than the absolute numbers. Phoenix ranks posts by predicted P(reply) + P(retweet) + P(bookmark) — each with its own learned weight. Engineering for replies (especially author-reply conversations) is ~150× more leverage than engineering for likes.
Timing · the strongest single signal
Phoenix watches the first 30-60 minutes after posting closely. A tweet that gets 10 replies in the first 15 min dramatically outperforms the same 10 replies spread over 24h. The early-engagement slope predicts everything downstream.
Sentiment · Grok damps the negative
Grok now monitors the tone of every post. Positive / constructive messaging gets wider distribution · negative / combative tones get reduced visibility even if engagement is high. This is the biggest break from the old Twitter ethos (where outrage was farmable).
Top-level orchestrator. Rust. Sequences candidate sourcing → ranking → filtering.
In-memory post storage. Holds posts from accounts you follow (the In-Network pool).
Grok-based ranker. 256-dim embeddings, 4 attention heads, 2 transformer layers. ~3 GB model shipped via Git LFS — runnable out-of-box.
Filters 500M daily posts → ~1,500 candidates from follows + ML discovery (Phoenix Retrieval for out-of-network).
xAI commits public updates every 4 weeks. Latest: 2026-05-15 — 187 files changed, 18K LOC new (end-to-end inference pipeline + content-understanding + ads + candidate sourcing components).
- 01Optimize for replies — phrase tweets as open questions or contrarian takes that demand response. 27× the like-leverage. Stop measuring likes.
- 02Engineer author-reply conversations. Tommi replies to every substantive comment within 15 min of posting. 150× leverage compounds across the thread.
- 03Post when the first-15-min audience is awake. Local launch windows per market (IT 08:30 + 18:30; DE 09:00 + 19:00; etc).
- 04Keep tone positive / constructive — outrage is now damped by Grok. Build-in-public > take-down posts.
- 05Bookmark-worthy content >> like-worthy. Carry a saveable bullet list, framework, or template in every founder post.
- 06Quote-tweet high-signal accounts in our niche to inject Cicero into their post's lift (25× like).
- 07Schedule the 1 long-form LinkedIn article/week → cross-post the punchy 5 best lines as separate X threads, each optimized for replies.
What 2B views costs
Pick a target. See the implied monthly spend at the v0 kill-condition band ($200-300 CPM) versus pure clipping ($2-4 CPM).
CPM calculator
Target band is the v0 kill-condition. CPM >$400 sustained 14 days triggers a cost audit. Clipping is the lowest unit-price distribution layer; the rest of the stack (organic + AI-UGC + creator network) is what blends the average up to $200-300.
From views to retained users
The end-to-end funnel from top of the loop. Adjust any rate; the downstream numbers recompute. If R-value > 1, refers feed the top of funnel.
Conversion funnel
Default values from the playbook: 2B views → ~10M followers (0.5%) → ~500K visits → ~40K installs → ~20K activated → ~8K D7 → ~4K D30 → ~600 refers. If R-value > 1, the refers feed back into the top.
The expensive distribution layer
Founder/CEO live-streams the actual day → clipping agency multi-cuts → distribution dashboard. The market clearing price is now known: $2-$4 CPM (76¢ was a stale 2024 anchor).
Eddie Cumberbatch · 54k clips/month possible at scale. Cheaper than Meta for top-of-funnel reach.
Live-stream → clip → distribute (paid per CPM) → dashboard reports. Don't script the live-stream.
$29 Opus Clip + $1.5K Reach.cat + $1.5K Lumina Clippers A/B. Action: get 2 quotes this week.
Skills-as-distribution channel
The strongest emergent theme of late April. A distribution channel where the install IS the activation — install rate dwarfs SaaS signup conversion because there are fewer stages. The 'comment X' reel is the new landing page.
Ship cicero-route-draftas our first skill drop — a “give me a 3-hour Florence morning route” Claude skill + 60-second demo reel + “comment ROUTE” CTA → repo install line. Same artefact powers in-app route generation.
3 brand fronts, cross-fed
Personal warms attention. Lifestyle captures intent. Product converts. Each loop feeds the next.
Personal · Tommi
Cult-of-Elon equivalent
Cicero lifestyle
Travel-as-lifestyle, Nude-Project-tier brand
Cicero product
Funnel + retention + emotional journey
“I saw a Cicero reel of someone walking in Trastevere with audio narration. Two days later Tommi tweeted why he's building this. A week later I planned a trip to Rome and downloaded the app.”
That is the design. Personal warms attention → lifestyle captures intent → product converts. Each loop feeds the next.
~/workspaces/EA/jarvis/memory/projects/distribution/playbook.md
Pattern-level frameworks. Raw reels live inreels/; pipelines inpipelines/.