AI agents for marketing & sales

The problem

Marketing and sales teams want concrete leverage from AI — not another demo, not another platform to learn. They usually have one painful number they need to move (response rate, content output, leads qualified per week) and a stack of generic “AI for marketing” tools that promise everything and move nothing. The gap is between a shiny capability and an agent built to actually shift one specific metric inside one specific workflow.

What I built

A library of bespoke agents, each one scoped around a single team, a single workflow, and a single number to move. No platform play, no agent-of-agents architecture — just the smallest agent that earns its keep.

• Lead qualification. Agents that triage inbound, enrich each lead from public signals, and route warm ones to the right person with the context already pulled together.
• SEO content at scale. Research → outline → draft → internal-link pass, chained together, with a human review step where it matters.
• Always-on assistants. Internal copilots on Slack or in-app that answer the same questions the team keeps fielding, grounded in the company’s own docs.
• Adaptive follow-up. Sequences that change their next message based on what (or whether) the prospect replied — replacing “did you see my last email?” templates.

Every engagement starts the same way: pick the one team, the one workflow, the one painful number. Then I scope the smallest agent that can move it, ship it in weeks, and measure what changed.

The result

Engagements typically deliver a working agent in production in weeks, not quarters, with a before / after measurement built in so the value is visible.