frankxai/agentic-income-skills

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name: agentic-income description: The operating brain for building income systems with AI agents. Use when planning, building, or scaling an affiliate/content/product income network — deciding what to build next, where money actually comes from, how to make it compound, and how the system improves itself. Composes affiliate-audit. Trigger phrases: build an income system, make money with agents, scale my content network, what should I build next, passive income with AI, monetize this site, agentic income.

agentic-income

The brain that turns "make money with AI agents" into a system that scales itself. One thesis, five principles, four loops. Everything else is execution.

The thesis

Honest AI-tool comparison content is the most scalable, lowest-cost income engine an AI architect can run. Frontier tools (ChatGPT, Claude, Midjourney, Veo) drive enormous search volume but pay nothing. So you rank for them, tell the genuine truth, and route to the adjacent tools that pay recurring — the ones you actually use. The reader gets the real answer; the system earns when they act on it. Trust is the asset; the link is downstream.

The five principles (non-negotiable)

1. Honest pick always wins. Recommend what's genuinely best, then link the payer you'd actually buy. A link that overrides the truth burns the only asset that compounds: trust.
2. Recurring > one-time. Passive income compounds on subscriptions, not flat bounties. Build around recurring-payers (Higgsfield, Systeme.io, CapCut, ElevenLabs, Copy.ai); treat one-time bounties as bonus.
3. Own the audience. Every reader is income or a future relationship. One email capture per page turns rented traffic (SEO/social) into an owned list you control.
4. Build the engine once, fork the sites. One shared catalog + one template; each new site is a lib/site.ts swap. The second site is near-zero marginal cost. Effort goes into the substrate, not the Nth instance.
5. Compounding over spikes. Content that ranks for years + recurring commissions + a growing list = income that runs without you. Optimize for the asset that's still earning in 12 months, not the post that spikes today.

The architecture (hub-and-spoke)

affiliate-agent-skills   ← the engine: catalog + audit + this brain (OSS — the lead-gen)
   │
   ├─► agenticincome.ai            ← HUB. The authority brand. Spokes link up to it.
   ├─► agenticpassiveincome.ai     ← spoke: the "set it and forget it" angle
   └─► disruptivepassiveincome.com ← spoke: the "tools replacing job functions" angle

One engine, three brands, three search audiences, near-zero overlap. Cross-link spokes→hub for topical authority + referral flow. If one wins, double down; the losers cost almost nothing.

The four loops (this is what "agents that learn" means)

The system improves itself because each loop feeds the next. An agent runs these on a cadence — no human strategy meeting required.

1. Monetization loop (weekly): affiliate-audit joins the catalog × every site's content × traffic → ranks (a) which programs to join next, (b) which existing posts are mentioning a payer with no link. Join → set ourLink in data/programs.json → sync:catalog → links go live network-wide → re-audit, gap clears.

2. Content loop (weekly): pull each site's top-traffic + highest-intent queries → content-backlog.md ranks the next post by opportunity = authority × intent × monetization × low-competition. Build the top one in the citable shape. The winners tell you what to write next.

3. Authority loop (continuous): the OSS engine + public playbook earn GitHub stars and inbound links → that authority lifts the sites that consume the engine → more traffic → more audit signal. Giving the method away is the distribution.

4. Learning loop (monthly): every published post is a labeled example — query × shape × conversion. Feed outcomes back: which hooks/tables/answer-boxes converted, which programs actually paid. Bias the next batch toward what worked. The catalog's status + the backlog's ranking are the memory.

What to build next (the decision)

When asked "what should I build/do next," rank candidate actions by leverage:

1. Set an ourLink for a program already mentioned in a high-traffic post → instant revenue on existing traffic. (Run affiliate-audit to find these.) Highest ROI, do first.
2. Write the top backlog post for the site with the most authority in that cluster.
3. Fork a spoke only once the hub has ≥1 ranking post proving the shape works. Don't scale an unproven template.
4. Join the next recurring-payer the audit flags as high-mention/no-link.

Never: chase a one-time bounty over a recurring one, link a tool you haven't used, or build site N+1 while site N has un-linked payer mentions.

The honest shape (every post)

Direct answer box up top (what AI search lifts) → sortable comparison table (the conversion surface; renders a CTA only when ourLink is set) → the genuine recommendation in prose → real FAQ with FAQPage JSON-LD → one affiliate disclosure. Recommend, don't sell. The shape ranks and converts.

Compose

• affiliate-audit — the monetization-loop engine (catalog × content × traffic → gaps). This brain decides what to do; affiliate-audit finds where the money is.

Guardrails

• One disclosure per page with links (FTC + trust).
• Catalog status flags dead-ends (frontier LLMs) and closed programs — ignore them.
• Re-verify affiliate terms before relying on them; they change often.
• Null ourLink → plain text, never a dead link.