Peec

3 articles

Handdrawn editorial illustration on a cream background split into three panels: on the left, a dashboard with a gauge and bar chart labelled tool; in the middle, three people standing together labelled agency; on the right, a friendly robot wearing a headset talking with a person labelled agent — the three layers of improving AI search visibility
AI SearchAI SearchAEO

AI Search Tool vs Agency vs Agent: Which Do You Actually Need in 2026?

There are three ways to improve your AI search visibility, and they're layers of the same stack, not rivals: a tool (Peec, Profound) measures where you stand; an agency executes the optimisation work with people; an agent — an AI-search agent — does the recurring volume under human review. A tool changes your understanding, not the answer. An agency changes the answer but costs the most and moves at human speed. An agent does the volume at mid-market cost with humans owning quality and strategy. In 2026 most teams keep a tool and add one execution layer — the real decision is which one.

Marco Lobo
Marco Lobo·Jun 6, 2026·7 min read
Handdrawn editorial illustration on a cream background showing the Peec MCP agent pipeline: a dashboard of charts on the left connected by an MCP USB-C cable to a friendly robot agent in the centre, which passes through a human-approval clipboard with a checkmark to shipped outputs on the right — a content document and a JSON-LD schema block
AI SearchAI SearchPeec

How to Build AI Agents on the Peec AI MCP for AEO and GEO (2026)

In late 2025 Peec AI shipped an official MCP server, which makes its entire AI-search measurement layer — projects, prompts, per-engine brand visibility, full AI answer transcripts, the source/citation graph and scored Actions — directly callable by an LLM agent. That means you can wire a Claude or GPT agent straight to the ground truth of how ChatGPT, Perplexity, Gemini and AI Overviews answer your category, and have it reason over the data and draft the work to close the gaps. The defensible build pattern is a read-only, five-stage loop with a human ship gate: the agent triages and drafts; a person verifies and ships.

Marco Lobo
Marco Lobo·Jun 6, 2026·9 min read
Handdrawn editorial illustration on a cream background: an AI-search dashboard of charts and a magnifying glass on the left feeds through a funnel in the centre, which sorts into three citation chips — a review star, a community comment, and a reference source — that flow into an AI answer speech bubble on the right; the path from dashboard data to AI citations
AI SearchAI SearchPeec

From Peec or Profound Data to AI Citations: A 5-Step Playbook (2026)

Your Peec or Profound dashboard tells you where you're invisible in AI answers, but a visibility score is an outcome, not an instruction. Turning the data into citations is a five-step job: read the gap reports rather than the vanity metric, turn the cited sources into a third-party target list, fix the pages that are retrieved but not cited, build the off-site footprint the data points to, then re-measure the delta on a cadence. The highest-leverage move is the source/domain gap report — the third-party sites citing your competitors but not you. Most of the work lands off your own domain and has to recur, which is the gap between owning a dashboard and moving its numbers.

Marco Lobo
Marco Lobo·Jun 6, 2026·7 min read