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.
Why generalist marketers need practical AI operating stacks that connect strategy, execution, approval gates and customer signal rather than isolated tool lists.
Why early-stage companies need senior marketing judgement that reaches beyond campaigns into positioning, product, pricing, customer evidence and AI-enabled operating systems.

Vercel and Railway can both support websites, backend applications and AI agents. This guide explains their operating models, costs and practical marketing use cases.