Lead and market intelligence
Agents monitor target markets, identify useful prospects, collect evidence and prepare founder-ready outreach briefs.
I build growth systems where agents handle the repetitive research, monitoring, drafting and reporting work, while founders and marketers keep control of judgement, positioning and approval.
Built around real operating loops: inputs, scoring rules, approvals, storage, review and iteration.
Designed for commercially useful work: better leads, stronger content, clearer reporting and improved AEO visibility.
Uses Mark OS, Hermes, Claude/Codex, GitHub, Slack and workflow automation as a practical marketing operating stack.
Agents monitor target markets, identify useful prospects, collect evidence and prepare founder-ready outreach briefs.
Turn expert input, social posts and market research into approved articles, LinkedIn angles and distribution assets.
Build the technical and editorial loop for pages that search engines and answer engines can find, understand and cite.
Give the team a small number of clear daily actions rather than another analytics surface nobody uses.
• You already know AI should change marketing operations, but you need a working implementation.
• Your team wastes time on repeated research, reporting, content and lead-prep tasks.
• You need approval gates, audit trails and feedback loops rather than unsupervised automation.
• You want a system that creates sharper commercial decisions every week.
What this week’s LinkedIn posts showed me about llms.txt, AEO loops and the practical work required to make a brand easier for AI systems to find, trust and cite.

AI marketing systems fail when approval design, state, audit trails and publishing gates are too loose for real brand work.
How I use Hermes, Tavily, MailerLite and a human approval gate to turn weekly AI marketing research into a newsletter and blog workflow.