--- name: consumer-ai-factory-distribution-learning description: Capture, generalize, and reuse distribution learnings across Consumer AI Factory ventures while preserving venture/category nuance. tags: - consumer-ai-factory - distribution - gtm - outreach - channels - messaging - growth-learning --- # Consumer AI Factory Distribution Learning ## Session references - `references/work-agents-landscape-viktor-2026-06-04.md` — work agents / Viktor landscape note: Viktor’s Slack-native coworker packaging, adjacent competitors, demand/WTP signals, and the factory decision rule to use AgentAppStore as the work-agent intelligence/distribution surface before considering any narrow workflow build. - `references/agentic-venture-studio-landscape-2026-06-03.md` — autonomous/agentic venture studio landscape note: credible software-agent capabilities, thin “AI-native studio” claims, Anthropic Project Vend cautions, and the Consumer AI Factory rule to keep agents as internal operating leverage while HappyCouple stays consumer-facing around concrete relationship repair moments. - `references/happycouple-moment-of-need-acquisition-2026-05-26.md` — reusable moment-of-need acquisition pattern from Emma/HappyCouple: intercept acute help-seeking language, build exact-intent tool pages, use creator comment-to-tool bridges, and launch social as `Emma by HappyCouple` rather than generic relationship advice. - `references/agentappstore-weekly-autosend-2026-05-21.md` — pattern for moving AgentAppStore Weekly from signup/archive to scheduled Beehiiv autosend: deterministic generator script, dry-run gate, sent ledger, repo archive commit, no-agent cron, and precise reporting of signup vs issue-send automation. - `references/agentappstore-newsletter-manual-first-send-2026-05-29.md` — manual first-send/review checklist for AgentAppStore Weekly: pick the intended issue #1, dry-run the provider payload, inspect Beehiiv `draft` vs `confirmed` behavior, and avoid using the autosend cron to send a historical first issue. - `references/agentappstore-newsletter-provider-gated-package-fallback-2026-05-29.md` — fallback pattern when Beehiiv/provider API sending is plan-gated: fail loudly, do not mark as sent, rename autosend jobs honestly as package/draft builders, and generate send-ready manual/dashboard packages. - `references/agentappstore-buttondown-newsletter-autosend-2026-05-29.md` — Buttondown fallback path for true AgentAppStore Weekly autosend when Beehiiv send is enterprise-gated: provider selection, first-party signup migration, Vercel env rollout, subscriber import caveats, and API verification sequence. - `references/agentappstore-newsletter-launch-signup-sprint.md` — AgentAppStore Weekly launch/signup learning: treat newsletter as distribution-learning product, use category-intelligence positioning, verify signup/provider baseline, distinguish autonomous monitoring/assets from posting, and respect channel identity constraints. - `references/agentappstore-newsletter-launch-signup-sprint.md` — AgentAppStore Weekly launch/signup learning: treat newsletter as distribution-learning product, use category-intelligence positioning, verify signup/provider baseline, distinguish autonomous monitoring/assets from posting, and respect channel identity constraints. - `references/agentappstore-seo-newsletter-publishing-loop-2026-05-21.md` — reusable AgentAppStore content-distribution launch pattern: on-site newsletter archive + provider signup embed + category SEO pages + scheduled repo-commit publishing loop, with verification and Beehiiv API plan-gate reporting rules. - `references/agentappstore-brand-led-distribution-2026-05-18.md` — brand-led distribution correction: when Antoine disallows personal-account posting, create/operate venture-owned accounts and native credibility posts instead of defaulting to founder social/DM blasts. - `GTM Execution Batch - 2026-05-18` (vault artifact) — executed GTM-stack expansion across HappyCouple, AgentAppStore, and Start Small: creator kit, outreach v2 queues, market-map lead magnet, founder notification loop, and GPT lead-magnet/probe specs. Key lesson: separate prepared assets/queues from sent outreach; X API may still 403 on brand posts despite valid `whoami`. - `references/agentappstore-consumer-category-first-reddit-2026-05-18.md` — Antoine correction on AgentAppStore GTM: founder notification/repost loops are secondary; lead Reddit/social with consumer-facing category/job posts, and do not treat founder silence as consumer-demand signal. ## New reference artifacts - `references/agentappstore-newsletter-playbook-2026-05-17.md` — playbook for turning AgentAppStore market research into a weekly consumer AI intelligence newsletter with provider-powered sending, AgentAppStore-owned archive, and category/venture learning loop. - `references/agentappstore-newsletter-automation-2026-05-17.md` — implementation notes for the AgentAppStore newsletter research/write engine: CSV-to-Markdown issue generation, category-alignment scoring to avoid noisy public picks, provider-gated sending, and Claude Code handoff shape for website integration. - `references/agentappstore-newsletter-editorial-feedback-2026-05-17.md` — Antoine's v2 newsletter editorial direction: intro + section list, category teardown first, apps second, category-focused issues, every-third comparison/trends issue, and richer app teardown fields including users/downloads/reviews, surface, solved job, and category role. - `references/agentappstore-beehiiv-provider-setup-2026-05-17.md` — Beehiiv setup and safety pattern for AgentAppStore Weekly: local-only env vars, publication verification, dry-run before send, no key preservation, and approval gates before public publishing. - `references/agentappstore-reddit-founder-notification-loop-2026-05-18.md` — AgentAppStore market-map distribution pattern: beautiful native visual + taxonomy conversation on Reddit, dedicated venture account only, no-link first-wave comments, and correction-first founder notification loop with contact-confidence tracking. ## When to use Use this skill whenever Antoine asks to: - Run, review, or log distribution experiments for any Consumer AI Factory venture. - Send outreach, test a channel, or evaluate creator/community/partner tactics. - Generalize learnings from HappyCouple or another venture into reusable factory doctrine. - Compare channels, tactics, messaging patterns, creator archetypes, or conversion paths across ventures. - Preserve what worked/failed after a campaign, outreach batch, Reddit test, SEO test, community post, paid test, or creator partnership. ## Core principle Distribution is a compounding factory asset, not a one-off task inside a venture. Every venture should improve the factory’s understanding of: - channels - tactics - messaging patterns - partner archetypes - community norms - activation paths - trust objections - conversion mechanics - industry-specific nuance Do not blindly copy tactics across products. Preserve enough nuance that a winning pattern can be adapted intelligently. ## Canonical factory artifact Primary doctrine note: ```text /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/00 Operating System/Distribution Learning System.md ``` Related notes: ```text /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/00 Operating System/Messaging and Outreach Doctrine.md /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/01 Playbooks/Creator Contact Verification Playbook.md /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/01 Playbooks/Email Reply Monitoring Playbook.md /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/00 Operating System/Company Factory Principles.md /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/00 Operating System/Consumer AI Company Factory - Build Log.md /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/05 Ventures/Venture 001 - HappyCouple/03 GTM/01 Distribution Experiment Ledger.md /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/05 Ventures/Venture 001 - HappyCouple/03 GTM/02 Interaction Ledger.md ``` HappyCouple venture-specific logs: ```text /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/05 Ventures/Venture 001 - HappyCouple/05 Build Logs/HappyCouple - Organic Distribution Process Log.md /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/05 Ventures/Venture 001 - HappyCouple/03 GTM/Email/HappyCouple - Creator Outreach Queue.md /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/05 Ventures/Venture 001 - HappyCouple/03 GTM/Reddit/HappyCouple - Reddit Draft Queue.md ``` ## Required two-layer logging Every meaningful distribution experiment should produce two outputs: 1. Venture-specific execution log. 2. Factory-level learning if the pattern could transfer. For example: - HappyCouple creator outreach details stay in the Venture 001 GTM notes. - Reusable lessons about creator outreach in trust-heavy consumer AI categories go into the factory distribution/messaging/contact-verification notes. ## External tool / capability landscape rule When Antoine asks what tools, APIs, frameworks, or agent skills we can leverage for distribution, product research, SEO/AEO, Reddit, TikTok, Product Hunt, partnerships, ads, creative production, autonomous companies, AI-run startups, or agentic venture studios, do **not** answer with only an external shopping list. First inventory what the factory already has: - existing Hermes skills/playbooks - active cron jobs and scheduled loops - local CLIs / installed packages / configured integrations - Obsidian/factory-vault artifacts and command-center ledgers - venture-specific workflows that can be promoted to reusable class-level agents Then classify the answer as: ```text Already have: Partially have / should generalize: Missing external integrations: Build first: Do not buy/build yet: ``` Key session lesson: Antoine pushed back on a pure external-tool landscape with “but dont we already have some of these”. For this class of work, the right frame is a **capability-maturity matrix**, not a vendor list. For agentic/autonomous-company landscape questions, separate: ```text Credible current capabilities: Mostly narrative / branding: Internal factory leverage: Consumer-facing positioning risks: Experiment implied for the active venture: ``` For work-agent / AI-coworker landscape questions, do not treat “AI employee” as one horizontal category. Separate: ```text Surface: Slack / Teams / Gmail / browser / workspace suite / system of record Job or function: sales / marketing / admin / support / finance / engineering / ops Named output artifact: brief / report / ticket pack / CRM update / resolved conversation / follow-up draft Integration depth: read-only, draft, approved action, autonomous action Trust layer: permissions, approvals, audit logs, recovery, compliance Pricing model: seat, credits, outcome, workspace, enterprise Distribution route: SEO comparison page, marketplace, existing suite, founder/operator community, partner channel ``` Do not default to building a broad Viktor-style clone. The default Consumer AI Factory move is to use AgentAppStore as a category intelligence/distribution surface first, then build only if a narrow high-intent workflow emerges. Preferred probe pattern: ship comparison/category pages, track qualified traffic and “tell us your workflow” submissions, then manually test one named workflow artifact. Do not let “autonomous company” research turn into agent theater. The Consumer AI Factory should use agents as internal leverage for pain mining, build/QA, content, experiment analysis, and safety review; consumer products like HappyCouple should still lead with a concrete human life-job, not agent infrastructure. References: - `references/agent-usable-product-growth-tools-landscape-2026-05-17.md` captures the first landscape scan and the recommended reusable agents: Consumer Reddit Opportunity Miner, SEO/AEO Brief Generator, Product/Competitor Research Agent, UX/UI Audit Agent, Short-Form Creative Factory, and Partnership/Creator Discovery Agent. - `references/agentic-venture-studio-landscape-2026-06-03.md` captures the autonomous/agentic venture studio scan and the HappyCouple implication. - `references/work-agents-landscape-viktor-2026-06-04.md` captures the work-agent/Viktor landscape scan and the AgentAppStore-first decision rule. ## What to track ### Distribution identity Before selecting tactics, record who/what the market will see. ```text Distribution identity: Allowed account types: Disallowed account types: Brand/project account needed: Personal-account approval status: ``` If Antoine says nothing can come from his personal accounts, do not recommend founder social posts, personal DMs, or personal email. Build venture-owned distribution assets instead: account handles, profile copy, avatar/banner, pinned launch post, native credibility posts, community posture, and monitoring. ### Channel Track the channel, not just the campaign name. ```text Channel: Venture: Audience/community: Why this channel might work: Observed norms: Risks / anti-patterns: ``` Example channels: - Reddit useful-answer comments - creator/specialist outreach - podcast guest pitches - newsletter swaps - SEO pages - TikTok/Instagram creator partnerships - community posts - cold email - paid tests - app-store/search surfaces - referral loops ### Tactic Track the exact tactic. Bad: ```text Reddit ``` Better: ```text Answer acute relationship-conflict posts with useful no-link founder comments for 7 days before mentioning product anywhere. ``` Template: ```text Tactic: Target user moment: Execution steps: Volume: Time window: Success metric: Failure metric: ``` ### Messaging pattern Track the structure and why it works, not only the words. ```text Message pattern: Example: Why it should work: What it avoids: Where it is industry-specific: Where it might generalize: ``` A winning message pattern is often reusable logic, not reusable copy. ### Partner / creator archetype ```text Partner archetype: Audience pain: Why they care: Why they might not build it themselves: Best ask: Bad ask: Proof needed before outreach: ``` ### Results ```text Date: Experiment: Sent / posted / launched count: Replies: Positive replies: Booked calls: Traffic: Activation: Qualitative signal: Objections: Decision: ``` ## Nuance rule Do not over-generalize. A useful factory learning should preserve: - industry/category - audience sophistication - trust/safety constraints - channel norms - why the message worked or failed - exact user pain language - stage of product maturity - whether the motion requires founder credibility, creator credibility, or product proof Bad factory learning: ```text Creator outreach works. ``` Good factory learning: ```text For emotionally sensitive consumer AI categories, creator outreach should not lead with sponsorship or data. It should ask for private feedback on one concrete user moment, show a live product link, and position the creator as helping evaluate a bounded AI tool in their field. This may transfer to parenting, health-adjacent, dating, grief, career, and other trust-heavy consumer categories only if the ask respects expert boundaries. ``` ## HappyCouple first patterns ### Moment-of-need acquisition motion When Antoine asks for smarter acquisition, do not default to broad content or generic posting. Start by identifying people who are actively asking for help now. For HappyCouple/Emma, prioritize exact user-language triggers such as `what do I say`, `how do I respond`, `am I overreacting`, `partner asked for space`, `left on read`, `how do I bring this up`, `how do I apologize`, `mental load`, and `partner shuts down`. Translate the same trigger set across channels: - Reddit fresh-post/comment mining: useful native answer first; transparent Emma link only where safe and allowed. - SEO: exact-intent tool pages, not generic blog posts; pages should route quickly to `paste your situation`. - Instagram/TikTok: mine creator comments for acute asks and reply helpfully; profile/bio carries the link. - Creator outbound: pitch a comment-to-tool bridge for their audience’s repeated `what do I say?` questions. For HappyCouple social identity, prefer `Emma by HappyCouple`: Emma is the memorable consumer persona/product, while HappyCouple is the parent trust/domain wrapper. Avoid launching a generic relationship-advice page. See `references/happycouple-moment-of-need-acquisition-2026-05-26.md` for the session-specific detail and reusable trigger template. ### Reddit useful-answer motion Pattern: - Transparent founder/operator account. - No fake neutral identity. - No links/product mention by default while trust/account health is being established. - First week: useful comments only unless a thread is explicitly feedback/showcase/tool-request friendly. - Answer acute posts with a concrete script and underlying-issue framing. - Read actual replies to our comments; judge qualitative validation by follow-up questions, thanks, objections, and requests for wording/help — not only by upvotes. - Reply-to-replies is part of the core loop. People who reply to our useful comments are higher-intent than cold thread authors. - After real engagement appears, add a controlled traffic loop: one safe link-bearing touch per run only where the user asks for a tool/resource or the community is product-feedback/self-promo friendly, with transparent founder/product disclosure and UTM tracking. - Add controlled self-post tests in feedback/building-friendly communities; do not force product posts into sensitive support/advice subs. Reusable hypothesis: Trust-heavy consumer AI categories may need useful public participation before product mention. The channel can provide pain language and moment taxonomy before it drives traffic, but no-link validation should not become a permanent comfort zone. Once replies validate the advice pattern, explicitly test whether warm moments convert to clicks and activation. Reference: `references/happycouple-reddit-engagement-to-traffic-2026-05-17.md`. ### Creator/specialist outreach motion Pattern: - Antoine sends personally. - Contact paths verified from official sources. - Message reads naturally, not with mechanical callout labels. - Message states what the product does, why this creator came to mind, and a small ask. - Product link included: https://www.happycouple.ai - Ask is feedback/private review first, not sponsorship or promotion. - Avoid abstract founder-y lines like “chance to be involved early in an AI project” unless made concrete and natural. Reusable hypothesis: For consumer AI products in creator-led expert categories, the first ask should often be: help evaluate a bounded AI experience around one concrete user moment. Promotion comes later if value is proven. ## Contact verification requirement Before creator/specialist sending, load or follow: ```text /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/01 Playbooks/Creator Contact Verification Playbook.md ``` Do not guess emails. Verify from official site/contact/media/press pages or official-site-linked media kits/social profiles. Respect role restrictions; if a site says an email is only for media/events and guest pitches will be deleted, use the form instead. ## Reply monitoring requirement If Hermes sends venture outreach, also set up or check reply monitoring. Use thread-based monitoring, not broad inbox search. Canonical playbook: ```text /Users/antoinelevy/Documents/Obsidian Vault/Consumer AI Company Factory/01 Playbooks/Email Reply Monitoring Playbook.md ``` Reusable pattern: 1. Store Gmail message IDs / thread IDs in the venture outreach queue after sending. 2. Monitor only those known threads, inside the venture label namespace. 3. Ignore Antoine's own sent messages. 4. Classify inbound messages as human reply vs auto-response. 5. Log both, but only count/label human replies as real distribution signal. 6. Never auto-reply without Antoine approval. 7. Schedule a recurring monitor when outreach is active; for HappyCouple the working implementation is `/Users/antoinelevy/.hermes/scripts/monitor_happycouple_outreach_replies.py` with cron job `HappyCouple outreach reply monitor`. Important experiential finding: auto-responses can arrive immediately and look like replies. Do not mark them as positive signal or update partner status to `replied`; log them separately with a next step like `wait for human reply`. ## Agent directory / MCP discovery surfaces Some projects are distribution infrastructure rather than normal one-off consumer apps. When reviewing or operating an agent directory, marketplace, MCP catalog, plugin store, or AI-to-AI routing surface, use `references/agent-directory-mcp-distribution-surfaces.md`. Key rule: evaluate both the **human directory** and the **machine-readable discovery layer**. The latter may be the stronger wedge if AI systems need to route tasks to specialized agents/tools. Check endpoint health, domain/count/protocol consistency, task-search quality, developer submission funnel, and badge/backlink loops. ### AgentAppStore / consumer-agent research surface When operating AgentAppStore for Antoine, do not treat it as a generic dump of AI agents. Antoine's chosen direction is for AgentAppStore to become the public front for the Consumer AI Factory's ongoing research into **true consumer AI agents**: relationship, dating, style, travel, life admin, family, finance, learning, career, health, shopping, home, and companion/life-coach products. Use `references/agentappstore-consumer-agent-research-surface-2026-05-17.md` for the canonical taxonomy, artifact locations, weekly refresh cadence, inclusion/exclusion filter, and first cleanup scope. Operating rule: ```text consumer AI landscape research → AgentAppStore SEO/category/comparison content → qualified traffic to factory ventures → product signal → refreshed research ``` Every Consumer AI Factory venture should eventually be listed, compared, and routed from relevant AgentAppStore surfaces. For example, HappyCouple should appear in relationship-agent pages and comparisons once its listing is ready. If Antoine says to "clean AgentAppStore," prioritize repositioning, taxonomy, category pages, snippets, teardowns, and consistency fixes before starting any new product probe. ### AgentAppStore / consumer-agent research surface pattern When operating AgentAppStore or any AI-app/agent directory for the Consumer AI Factory, treat it as a compounding research and distribution system, not a static list. Use `references/agentappstore-consumer-agent-research-surface.md`. Operational rule: ```text weekly consumer-agent landscape refresh → canonical XLSX/CSV + markdown note → category-focused AgentAppStore newsletter / SEO / comparison / teardown backlog → implications for active ventures and next validation candidates → public SEO/discovery surface routes qualified traffic back into factory ventures ``` For consumer-demand validation, do not lead with founder-notification loops or founder-facing market maps. Lead with consumer-native category/job posts that answer a concrete life problem, e.g. `5 AI apps for couples who don't know what to say next` or `5 AI apps for job searching without spreadsheet hell`. Founder outreach is useful for corrections, first-party listing data, app submissions, and occasional shares, but founder silence is not evidence that consumers don't care. See `references/agentappstore-consumer-category-first-reddit-2026-05-18.md`. For AgentAppStore Weekly, do **not** default to a generic multi-category "5 AI tools" roundup. Antoine's preferred editorial format is category intelligence: short intro, explicit issue map, `1) Category teardown`, `2) Apps`, then richer app teardowns. Each normal issue should focus on one category so the analysis is precise; approximately every third issue can compare categories, trends, and builds. See `references/agentappstore-newsletter-editorial-feedback-2026-05-17.md`. For newsletter sending, treat signup capture, issue-send delivery, and on-site archive publishing as separate systems. Beehiiv can remain useful for signup/welcome flows, but its programmatic broadcast sends may be blocked on non-enterprise plans with `403 SEND_API_NOT_ENTERPRISE_PLAN`; never label a Beehiiv-gated package builder as autosend. If a provider send/publish API is gated, first fail loudly and generate a deterministic handoff package (`subject.txt`, `preheader.txt`, `body.md`, `body.html`, provider paste file, metadata/zip`) without updating the sent ledger. For true autosend fallback, prefer Buttondown before raw email infrastructure: it is newsletter-native and supports subscriber creation plus create/schedule/send email APIs using `NEWSLETTER_SEND_PROVIDER=buttondown`, `NEWSLETTER_SUBSCRIBE_PROVIDER=buttondown`, and `BUTTONDOWN_API_KEY`. Before claiming autosend is live, verify provider auth, create/delete a safe draft, run a sender dry-run, update Production env, redeploy, test live signup, and confirm the cron name/schedule reflects reality. See `references/agentappstore-beehiiv-provider-setup-2026-05-17.md`, `references/agentappstore-newsletter-provider-gated-package-fallback-2026-05-29.md`, and `references/agentappstore-buttondown-newsletter-autosend-2026-05-29.md`. For AgentAppStore SEO/newsletter publishing loops, use `references/agentappstore-seo-newsletter-publishing-loop-2026-05-21.md`: publish the archive/index/pages on-site, add provider signup, create category/job SEO routes, schedule repo-committing article generation, then verify build, live HTTP, sitemap domain/inclusion, and scheduler state before reporting the machine as live. When Antoine asks for weekly autosend, distinguish the signup/welcome-email flow from the issue-send flow. A live Beehiiv signup form plus Vercel env vars does not mean weekly issues are scheduled. Use `references/agentappstore-weekly-autosend-2026-05-21.md`: create a deterministic no-agent cron backed by a script that generates the next issue, dry-runs payloads, keeps a sent ledger, sends through Beehiiv, commits the markdown archive, and reports the next run time. When Antoine asks how to send the **first** AgentAppStore Weekly issue, do not trigger the weekly autosend job by default. First inspect the existing newsletter markdown, identify the intended issue #1, run the manual sender with `--dry-run`, and check whether Beehiiv non-dry-run creates a draft or uses a send/publish status such as `confirmed`. Prefer a Beehiiv draft/dashboard review before any live send unless Antoine explicitly approves immediate sending. See `references/agentappstore-newsletter-manual-first-send-2026-05-29.md`. For AgentAppStore Reddit / community distribution, do **not** lead with a link, generic newsletter CTA, or founder-facing market map. Lead with a beautiful consumer-native category/job artifact and a taxonomy/trust question: `5 AI apps for couples who don't know what to say next — what am I missing?`, `does this consumer AI taxonomy make sense?`, or `how should a directory stay trustworthy once vendors want paid placement?` Use a dedicated AgentAppStore/ConsumerAIStore identity; never reuse warmed accounts from other ventures. Founder notifications should be correction-first, not share-first: tell founders how they were categorized and invite factual/category corrections. If a founder shares anything, the shareable object should be a consumer-facing category slice/list, not just `we made a map`. Treat founder shares/backlinks as secondary upside only; founder silence is not consumer-demand signal. See `references/agentappstore-reddit-founder-notification-loop-2026-05-18.md` and `references/agentappstore-consumer-category-first-reddit-2026-05-18.md`. Focus the public taxonomy on **consumer life jobs**: relationship/dating, style, travel, life admin, family, finance, learning, health, shopping, career, home, and companion/life coach. Exclude or demote enterprise/dev/infra/MCP/generic content tools unless they clearly solve a consumer life task. Every factory-built consumer venture should be listed and compared honestly in AgentAppStore, with category placement, SEO pages, API/MCP/llms discoverability where applicable, and routing paths back to the live product. ## Operating cadence after a distribution batch 1. Update the venture process log. 2. Update channel/tactic/message results. 3. Promote reusable patterns into factory doctrine or this skill. 4. Record what failed, including weak messages and dead channels. 5. Decide whether the pattern is venture-specific, category-specific, or factory-wide. 6. If a new repeatable workflow emerged, patch/create a skill immediately. ### Cadence audit rule When Antoine asks for current posting/commenting rate, separate **actual active rate** from **planned/intended cadence**. Do not infer “we are posting N/day” from old sprint plans, stale cron IDs in notes, or historical execution logs. Verify what is currently active, then report: ```text Current active automated rate: Last intended cadence: Last observed execution: Visibility/filtering status: Recommended next safe cadence: ``` If a venture has a planned Reddit loop but no active scheduler, state it plainly: `actual active rate is 0/day`. For a concrete example from the 2026-05-16 HappyCouple / Start Small audit, see `references/traffic-cadence-audit-2026-05-16.md`. ### Reddit platform engagement quality gate When Reddit loops are running across multiple ventures but Antoine says there is little on-platform engagement, do a cross-product account-history audit before recommending more cadence. Pull recent authenticated histories for each venture account and compute comments/posts, score sum, share of comments with score <= 1, removals, replies/comments-on-posts, and subreddit concentration. Factory rule: score-1 visible comments with no replies are not distribution. They are at best research/listening and often noise. A cron job that posts safely but earns no replies, no upvotes beyond baseline, no qualified visits, and no activation should be downgraded or paused rather than celebrated as motion. Use the `consumer-traffic-sprint` reference `references/reddit-platform-engagement-quality-gate.md` for the detailed pattern. ## Guarded aggressive automation pattern When Antoine asks to make a distribution sprint more aggressive, prefer increasing cadence and surface area through guarded scheduled loops rather than one-off manual bursts. Reusable structure: 1. Convert the sprint into cron jobs with self-contained prompts and explicit source artifacts. 2. Split loops by motion so each can fail safely: Reddit/community posting, directories/listings, creator target expansion, reply/follow-up checks, and source triage. 3. Add hard stop conditions inside each loop before increasing volume. 4. Separate actions that can be taken autonomously from actions requiring Antoine approval. 5. Schedule learning/triage jobs that decide what to double down on, not just jobs that report metrics. Guardrails that should be explicit in the cron prompt: - For Reddit/community motions: obey channel rules, verify public visibility after each action, stop the run if a fresh action is hidden/filtered/rate-limited, avoid sensitive contexts where product/linking is unsafe, and cap link-bearing activity while account trust is low. - If Antoine asks for aggressive Reddit cadence that includes links, split the automation into two separate jobs instead of mixing behaviors: a high-frequency no-link useful-answer loop and a lower-frequency link-bearing loop. Example working pattern from 2026-05-13: no-link every 3 hours, link-bearing every 12 hours, with the link job capped at maximum 1 link-bearing post/comment per run. - Link-bearing Reddit jobs must be allowed to skip a run when no safe opportunity exists. The prompt should explicitly say not to force links; only link where subreddit rules/context clearly allow it or where a user explicitly asks for a tool/resource. Require transparent founder/product disclosure, UTM links, public visibility verification, and immediate stop on filtering/mod pushback/rate limits/ambiguity. - Keep link and no-link job prompts mutually exclusive: no-link jobs should explicitly forbid product links/CTAs, and link jobs should not try to satisfy useful-answer volume. This prevents accidental link drops while still satisfying Antoine's desire for aggressive distribution velocity. - For directories/listings: skip CAPTCHA/login/paywall flows rather than bypassing them; log skipped opportunities separately. - For creator/specialist expansion: verify official contact paths; draft or queue outreach unless Antoine has explicitly approved sending; avoid unverified guessed emails. - For follow-ups: check known threads/labels first, distinguish human replies from autoresponders, and draft follow-ups without auto-sending unless approved. This pattern is especially useful for trust-heavy consumer AI distribution: aggressive enough to create learning velocity, but not so reckless that accounts, communities, or creator relationships get burned. ## Start Small / ADHD-task-paralysis Reddit-community pattern For ADHD, executive dysfunction, task paralysis, and productivity-adjacent Consumer AI probes, do not treat Reddit as one generic launch surface. The highest-fit communities are often the least safe for direct links. Reusable findings from Start Small research: - Large ADHD/support/productivity subs often explicitly ban advertising, self-promotion, feedback requests, surveys/research, app promotion, or “I made this” posts. Do not link-drop into r/ADHD, r/productivity, r/getdisciplined, r/selfimprovement, r/adhdwomen, r/AutisticWithADHD, or r/Neurodiversity without explicit mod approval. - Use direct posts first in feedback/building-friendly communities such as r/alphaandbetausers, r/SideProject, and, when relevant, specific allowed app/project threads like r/adhd_programmers monthly app threads. - For high-fit support communities such as r/ExecutiveDysfunction or r/AdultADHDSupportGroup, send modmail first with full disclosure, no medical claims, and an offer to post without a link or skip if inappropriate. - In restricted support subs, make only helpful no-link comments. Never use unsolicited DMs, never comment with product advice in crisis/medication/diagnosis threads, and avoid covert “search for my app” behavior. - Use community language: task paralysis, brain buffering, invisible wall, tiny starter step, first visible step, permission to stop, no-shame version. Avoid lazy, discipline, willpower, no excuses, productivity hack, optimize, crush, 10x, and any claim that the product treats/cures ADHD or executive dysfunction. - For 24h qualified traffic, prioritize: direct feedback subreddits, SideProject/builder communities, allowed ADHD-programmer/project threads, modmail to high-fit support communities, and existing founder/ADHD/productivity communities where Antoine already has social permission. Treat HN/Indie Hackers as optional builder-feedback spikes, not necessarily target-user traffic. - Always use UTM links per channel and monitor activation, not just visits: landing_viewed → plan_generated → step_started → step_completed. Interpret high visits with weak plan generation as copy/input failure; strong plan generation with weak step starts as output/first-action failure; and feedback saying “generic/ChatGPT” as a product-quality blocker before more traffic. Reddit account creation and API-auth caveats: - Hermes/browser automation may be blocked by Reddit network-security before signup forms load, showing only a “You’ve been blocked by network security” page. Do not attempt to bypass Reddit anti-bot/security. Ask Antoine to create/verify the account manually in his normal browser/device, then use the account transparently (e.g. founder/operator identity) and proceed with manual posting or official API auth if needed. - Keep Reddit identities venture-specific. Do not reuse an authenticated Reddit account from one venture to post for another venture, even if the API credentials technically work. Example: do not use `u/HappyCoupleFounder` to post Start Small content; it confuses identity, increases spam risk, and can burn the warmed account for the original venture. - Before any API posting, verify the authenticated username immediately before action and abort on mismatch. For Start Small, the intended account is `u/StartSmallFounder`; for HappyCouple, the intended account is `u/HappyCoupleFounder`. - If a new venture account is created manually, set up OAuth/API auth only after the account is verified. Generate the Reddit authorization URL, have Antoine approve it while logged into the correct account, then exchange the redirected URL and store the resulting token in a venture-specific token path. Never overwrite another venture’s token/config by accident. - For brand-new Reddit accounts, prefer the first 2-3 posts/comments manually in Antoine’s normal browser rather than immediate API posting. New-account API link activity can look automated and may be filtered; if API posting is used anyway, cap actions tightly and verify public visibility after each post. - Fresh-account Reddit API link posting can degrade fast: in the Start Small sprint, r/alphaandbetausers stayed clean, but r/SideProject, r/IMadeThis, and r/TestMyApp were all flagged with `removed_or_spam=reddit` after link-bearing posts, and an r/ADHD_Programmers thread comment had suspicious public visibility (`public_author=[deleted]` despite auth showing the comment). After the first automated filtering pattern appears, stop blasting. More link posts are negative expected value because they train the account/subreddit filters against the venture. - If Antoine pushes for speed after filtering starts, satisfy the impulse with channel switching, not more of the same API blasts: monitor/reply on the one clean post, use manual browser posting where flair/UI context is needed, ask mods for permission in high-fit support subs, post helpful no-link comments to warm the account, and move to existing trusted communities/DMs for immediate traffic. - In Start Small's 2026-05-13 sprint, the best recovery path after link-post filtering was a batch of no-link helpful comments in high-fit threads. r/ExecutiveDysfunction comments about planner trauma, task paralysis, admin backlog, and permission to stop were publicly visible; a r/GetMotivatedBuddies accountability-buddy comment was publicly visible; a r/productivity no-link comment existed in authenticated history but did not appear in public thread JSON. Reusable rule: prefer smaller/high-fit support or accountability communities for account warming; large productivity subs may still filter fresh accounts even without links. - Visibility checks should distinguish authenticated visibility from public visibility. A post/comment can appear normal to the logged-in account while being removed, spam-filtered, or oddly represented in public lookup. Report statuses as “clearly live,” “filtered,” or “ambiguous/suspicious,” not just “submitted.” - Some subreddits require flair and block API posting unless flair metadata is accessible; if `SUBMIT_VALIDATION_FLAIR_REQUIRED` or flair API 403 occurs, do not force/retry blindly. Switch to manual browser review or skip. ## Verification before final response Before reporting completion: 1. Read the modified venture log or queue. 2. Read the relevant factory artifact if updated. 3. State exactly what was changed and where. 4. Distinguish sent/launched actions from drafts or planned actions. 5. If emails/messages were sent, list recipients, subject/channel, and tracking label/status.