AI Search / 04 · AI Agents
Agents draft. Humans decide.
NMG runs AI visibility as an operation: specialized agents read live data on fixed cadences and draft work at machine speed, and a named human gate reviews every task before it ships. The same model of agents, gates, and a closed measurement loop runs across AI search, SEO, PPC, and CRO.
The four-layer operating model
The operation runs on four layers. First, a data and intelligence stack of ten-plus triangulated sources; no task reads from one tool alone. Second, a 29-agent fleet organized into five task clusters, led by a flagship orchestrator. Third, a named human gate on every task across six roles; nothing ships unreviewed. Fourth, the production teams that ship the approved work: content, links and PR, technical.
The division of labor is strict. Agents read feeds, detect change, and draft at machine speed; humans make the calls and own the result. A platform measures one slice of AI visibility. The operation runs the whole loop, from measurement to shipped fix and back to measurement.
- One job, one cadence, one output per agent
- A named human gate on every task
- A weekly action queue ranked by revenue relevance
One job, one cadence, one output, one gate
Every agent owns exactly one job with one feed, one cadence, one output, and one named reviewer. A visibility monitor reads per-prompt, per-engine deltas daily and files drop alerts with a diagnosis attached. A citation agent maps the domains AI cites on money prompts weekly; its gap list becomes the PR target list. An accuracy agent checks how models describe the brand monthly and traces every wrong claim to the source responsible for it. A crawler agent verifies which AI bots hit which URLs and separates real crawlers from fakes.
The flagship AEO/GEO Agent orchestrates the layer on a reads-decides-delivers pattern. Reads: the measurement platform daily, every tracked prompt and engine cell, the competitor cohort, the citation graph, crawler telemetry. Decides: what changed, why, and which task closes the gap, ranked by the revenue relevance of the prompt. Delivers: a weekly action queue, drop alerts within 24 hours, and a monthly one-slide scorecard verified before leadership sees it.
Human gates: nothing ships unreviewed
Six named roles gate the fleet: an SEO strategist who validates outputs and sequences the playbook, an AEO/GEO lead who owns the platform and verifies the queue, an editorial reviewer for accuracy and compliance, a technical engineer who ships schema and crawl fixes, a data analyst who cross-checks every number, and a program manager who owns outcomes. Every agent output routes to its named gate, never straight to production.
Orchestration is Slack-native and logged, so every hand-off between agent, reviewer, and production team stays readable, and clients keep direct access to the measurement workspace. The same numbers we read, unedited.
The governance loop, across SEO, PPC, and CRO
New work enters through a five-stage governance loop. Detect: an agent flags a rising prompt theme and a second confirms competitors capture it. Propose: agents draft the cluster spec, pages, target prompts, schema plan. Gate: the strategist approves, and compliance-sensitive additions clear editorial review. Spawn: the cluster enters the registry; sitemaps and briefs queue automatically. Verify: its prompts join the tracked set and movement reports to the scorecard.
The same one-job pattern runs beyond AI search. In SEO, agents mine content gaps, declining pages, page-two opportunities, link prospects, and cannibalization. In PPC, the pattern covers query mining, budget pacing, and creative-test queues. In CRO, experiment backlogs and funnel diagnostics. Wherever a feed can be read on a cadence and reviewed by a named human, an agent can take the job, and the gate model keeps every discipline accountable.
Everything closes one loop: measure, prioritize, execute, ship, re-measure. Daily prompt runs feed the ranked queue, teams ship through their gates, and the same prompts re-run the next day. Visibility is not a vibe; it is a number.
The method behind the numbers.
Instrument
Measurement platform, crawler telemetry, analytics, and search data connected; every tracked prompt baselined before anything runs.
Deploy the fleet
Agents assigned one job each, with feed, cadence, and output format defined per agent and mapped to your revenue priorities.
Name the gates
A named human reviewer per agent, with review rules, escalation paths, and compliance checks agreed with your team.
Run the loop
Daily reads convert movement into a ranked action queue; drops trigger alerts with a diagnosis within 24 hours.
Ship through teams
Gated actions route to content, link and PR, and technical teams, with every hand-off logged where you can read it.
Verify & expand
Shipped work re-measured against the same prompts; the scorecard reports monthly; new clusters spawn through the governance loop.
Straight answers.
How do AI agents do SEO?
Each agent reads one data feed on a fixed cadence and produces one reviewable output: a content-gap report, a declining-page list, a citation gap list, a crawl anomaly report. Named humans review every output before anything ships. The gain is coverage and speed, the full data surface read daily instead of quarterly, while judgment stays with people.
Do AI agents replace your human team?
No. The fleet has a named human gate on every task, across six roles: SEO strategist, AEO/GEO lead, editorial reviewer, technical engineer, data analyst, program manager. Agents draft at machine speed; humans make the calls and own the result. What agents replace is the waiting, the weeks between something changing and someone noticing.
What does the AEO/GEO Agent do?
It orchestrates the AI-search layer on a reads-decides-delivers cycle. It reads every tracked prompt and engine cell, the competitor cohort, the citation graph, and crawler telemetry daily. It decides which changes matter, ranked by the revenue relevance of the prompt. It delivers a weekly action queue, drop alerts within 24 hours, and a monthly one-slide scorecard.
Can AI agents run PPC and CRO work too?
Yes. The pattern of one job, one feed, one cadence, one output, one gate applies to any discipline with readable data: search-query mining and budget pacing in PPC, experiment backlogs and funnel diagnostics in CRO, alongside the SEO and AI-search clusters. The gates change per discipline; the operating model does not.
How do we know what the agents are actually doing?
Every hand-off is logged in a shared, readable channel, and clients keep direct access to the measurement platform, the same workspace our team reads. Outputs arrive as named deliverables on named cadences: the weekly queue, the drop alerts, the monthly scorecard. If it is not in the log, it did not happen.
The AI visibility cluster