Training: AI Presence Manager

What changes when search becomes an answer. Retrieval, synthesis, citation. Entity, knowledge graph, RAG and agents. Why the brand has to exist as an entity before it exists as a page.

1. Link search and answer search: what people do differently
2. Retrieval, synthesis and citation: the path from a question to the brand showing up
3. Entity, knowledge graph and the difference between being known and being cited
4. Agents that research and buy: the customer who never opens your site

What you deliver: A map of the answer journey for a sector, with the points where the brand can get in.

Google with AI Overviews and AI Mode, ChatGPT and its search, Gemini, Perplexity, Bing with Copilot, Claude. How each one reads, what each one cites, which crawlers they use and how often they come back.

1. Google: AI Overviews, AI Mode and what is still organic position
2. ChatGPT: browsing, the search crawler and the linked citation
3. Gemini, Perplexity and Copilot: sources, frequency and the weight of each by sector
4. The AI crawlers: who they are, what they ask of your server and how to receive them

What you deliver: The engine table for the client's sector: who answers, who cites and how much each weighs.

AI presence only exists as a number when the number comes with the total of checks beside it. How to build a sector's test questions, sample regions, repeat on the right cycle and publish without making things up.

1. Test questions: how a sector really asks, in ten different ways
2. Sampling by region and by engine, and the sample size that supports a percentage
3. The cycle: every week on Google, every two weeks on the AIs, and why
4. The AI Presence Index: how the public data is built and how to use it in sales

What you deliver: The client's first measured scoreboard: percentage, checks, engines and regions.

The Technical Score as a working method. Access, entity, evidence, knowledge, external presence, content, structure and markup. The weight of each layer, what blocks the others and the order of fixes.

1. Access: robots, headers, speed and what stops the crawler before anything else
2. Structured data: what Google requires per page type, and how to validate it
3. llms.txt, sitemaps and the file that guides how AIs read
4. Entity and evidence: author, organization, proof and the page that answers

What you deliver: The client's full technical audit, ordered by impact on the score.

Making the brand exist beyond its own site: profiles, listings, mentions in sources the AIs cite, reviews and consistency of name, address and phone. What builds trust for a machine.

1. Knowledge Graph, Wikidata and the listings AIs read first
2. Mentions that count: where AIs look for proof about a sector
3. Reviews and reputation: what goes into the answer and what sinks the brand
4. Consistency: the same name, address and phone everywhere, always

What you deliver: The brand's authority plan: fifteen sources, priority and deadline.

A page that answers a whole question, with your own data, an identified author and a date. Pillar and satellite structure, updates with judgment and what to avoid: generic text, no source, no number.

1. The anatomy of the cited page: question, direct answer, proof, context, author
2. Pillar and satellite: how one topic becomes forty pages that hold each other up
3. Your own data: the one thing the AI cannot get anywhere else
4. Updates and validity: when to rewrite, when to date, when to delete

What you deliver: Ten answer pages published for the client, with author and proof.

AI presence region by region: business profile, pages per location, the right phone and address in every place. Chains with dozens or hundreds of locations, without doing them one by one.

1. The business profile as primary source: fields, photos, hours, questions
2. One page per location that answers the local question, without becoming a copy
3. Chains and franchises: import, generate in bulk and review by sample
4. Region in measurement: how the same term changes answer by city

What you deliver: A chain of locations live and measured by region.

The work of every week. What to watch, what is normal, what demands action today, and how to turn monitoring into a report the client understands without translation.

1. Citation and position by engine: the week's reading and the month's trend
2. Competitors in the answer: who got in, who dropped out and why
3. Reputation and hallucination: when the AI gets the brand wrong, and what to do
4. Environment changes: blocked crawlers, access drops, algorithm and new engines

What you deliver: The client's monthly report: one page, measured, with the month's action.

A manager does not write a thousand pages: they run a pipeline. Plan, write, review and publish with agents, deterministic gates that block what is wrong, and cost measured per unit of output.

1. The pipeline: who plans, who writes, who reviews and where the person decides
2. Gates: code-based checks before publishing, or a thousand pages become a thousand problems
3. Cost per page, per article and per monitored term, measured and not estimated
4. Autopilot with judgment: what runs on its own and what always goes through you

What you deliver: A pipeline configured for a client, with gates and a known unit cost.

A profession exists when someone pays for it. Scope, deliverables, pricing models, contract and the monthly proof of value. How to present a measured result and how to turn down the wrong client.

1. The four models: setup plus monthly, per brand, per region and per measured result
2. A scope that fits on one page: what is in, what is out and what is extra
3. The professional's math: hours, tool cost, margin and the price per client
4. Contract, minimum term, monthly report and the right moment to raise the price

What you deliver: Your service menu, with scope, deliverables and price, ready to present.