Engineering AI GTM Systems That Drive Revenue
I design AI workflows, agents and GTM systems that help modern revenue teams eliminate manual work, move faster and scale efficiently.
Currently building outbound engines.
Latest Case Study
{ Fresh from the lab }A synthetic-persona outbound engine
Days → 15min per campaignAn internal sales-enablement tool. I took transcripts from the team's real sales conversations and synthesised them into 5 synthetic buyer personas — then let those personas write the outbound: a unique email + LinkedIn sequence per contact, in the persona's own language, grounded in real transcript quotes.
Business problem
Every campaign took days of manual copywriting and still sounded generic. What convinces a CIO vs. a CFO lived only in scattered sales calls — and never reached the emails prospects actually received.
Outcome
Every first line opens with the recipient's role-specific pain, in their own language. Per-campaign effort collapses to a 15-minute review — scaling the team's best hand-written outreach to 500+ contacts.
Case Studies
{ Systems that moved the number }Business problem
Right-fit companies visited the site and left anonymously — intent went cold before anyone noticed.
Outcome
New conversations every day from a visitor → outreach system with a human approval gate.
Business problem
Leads from every source landed in different tools and inboxes; hot demos went cold in queue.
Outcome
Every source unified, scored and routed. Median response fell from 4 hours to 11 minutes.
Business problem
Thin, stale CRM data — and enrichment tools that couldn't answer real qualification questions.
Outcome
Agents research like an SDR would. SQL → opportunity conversion up 38%.
Business problem
Execs walked into conferences with zero booked meetings and no context on who mattered.
Outcome
Calendars filled before the event, briefing tool in hand, follow-ups fired automatically.
Business problem
Spend decisions ran on last-touch guesses; marketing and finance argued over what drove pipeline.
Outcome
One source of truth in SQL/dbt. $1.1M moved to the channels that actually close.
Business problem
Every dashboard, list pull and report waited on ops or engineering — a constant bottleneck.
Outcome
Dashboards, Slack apps and data tools made in-house. The team self-serves in seconds.
Business problem
Campaigns took days to write and still sounded generic — what convinces a CIO vs. a CFO lived only in scattered sales calls.
Outcome
Real sales transcripts become 5 synthetic personas that write per-contact copy. Per-campaign effort dropped to a 15-minute review.
Great GTM isn't a deck — it's a system. Functional, instrumented, made to compound.
The Stack
{ Capabilities first, tools second }AI
Claude
OpenAI
Clay agents- AGCustom agents
Automation
n8n
Make.com
Zapier
Lemlist
HeyReach
Smartlead
CRM
HubSpot
Salesforce
Apollo
Gong
LinkedIn
Data
dbt- SQLSQL
Segment
HockeyStack
Developer Tools
- </>Claude Code
Python- APIAPIs & Webhooks
- RReact
About
{ Marketer → Engineer }My background in growth marketing taught me how companies generate demand. GTM engineering taught me how they scale it. Today I design AI-powered systems that connect people, data and workflows — so revenue teams operate better.
More about me →Let's ship.
Whether you're hiring, shipping AI workflows or rethinking your GTM infrastructure — I'd love to hear what you're working on.