Fractional AI GTM Leader · Builder · Knoxville, TN
Jay
Campbell
He shipped AI products before most companies finished their AI strategy deck.
The builder who ships
Fractional AI GTM Leader · Builder · Knoxville, TN
He shipped AI products before most companies finished their AI strategy deck.
The builder who ships
Profile
Jay Campbell has a Computer Science degree, fifteen years of sales team management experience, and a GitHub repository called JARVIS that runs 40+ automated tasks for him every day. He is not waiting for the AI era to arrive. He is already three products ahead of it.
The specific detail that defines him: when he built Cadence - his personal AI operating system - it was not a product pitch or a side project with investor ambitions. It was a tool he needed for himself, wired into 50+ APIs, handling pipeline triage, email management, and daily briefings before anyone knew the product existed. The version he released publicly was already road-tested on his own operations for months.
That is how he works. Build it for yourself. Verify it is real. Then ship it.
He spent seven years in enterprise GTM at Staffmark (VP-level sales operations in traditional staffing), Avionte (head of sales enablement in staffing software), and Sense (AI GTM executive at one of the leading recruitment AI platforms). Across those three stops he influenced over $75 million in revenue pipeline and managed teams ranging from three people to 110. He left each role knowing more about what enterprise sales actually requires, at the system level, than any consultant who never held a quota.
"Most companies are trying to use AI to do the same things faster. The teams that win are the ones who use AI to do things they could never do before."- Jay Campbell
The shift from operator to builder was gradual, then total. His Indie Hackers bio records the moment of clarity in one sentence: "the sales career funded the builder habit. the builder habit is the point now." That is not a pivot announcement. It is an honest account of how the priorities actually switched.
He is now a fractional AI GTM leader - a real operating role, not a strategy workshop - working with SaaS and staffing companies in focused three-to-six-month engagements to build the AI infrastructure that their revenue teams actually run on. He takes ownership of a GTM function, builds the systems end-to-end, and develops the people who will run them after he leaves. The product he brings to each engagement is not a deck. It is the same toolkit he built for himself.
He writes Selling with AI, a weekly newsletter covering practical AI motions for enterprise sellers. It runs a 70% open rate against an industry average of 21%. The gap between those two numbers is a reasonable proxy for the gap between what he writes and what most people publish about AI in sales.
Built by Campbell
He does not prototype. He deploys. Every product on this list was built to solve a real problem in enterprise sales or GTM, run on his own workflows first, and then made available to others. The signal-to-noise ratio on his GitHub is unusually high.
Cadence / JARVIS
Personal AI OSA personal operating system with 50+ API integrations running 22+ automated jobs daily - managing pipeline, inbox, calendar, and deal signals. Started as a personal experiment. Became a category.
DealIQ OS
AI CRM · B2B SalesMEDDPICC-native deal coaching with call transcript sync and AI scoring. Built for enterprise sellers who need intelligence delivered at the right moment, not another dashboard.
Selling with AI
Weekly NewsletterPractical AI playbooks for enterprise sales professionals. 70% open rate. Published weekly at sellingwithai.vip. The newsletter is itself a product - structured, not rambling.
getaFNjob
AI Career ToolAn AI-powered job search assistant for role-fit scoring and targeted outreach. One of his GitHub bios notes that "one of those products is currently job hunting on my behalf" - this is it.
Blair
AI CMO AgentStrategy, campaigns, content, copy, and audits in one conversation. An AI Chief Marketing Officer agent for any brand. Available on GitHub as open source.
Chase + RepoRanker
Signal + Dev ToolsChase monitors Reddit for deal signals and coaches engagement. RepoRanker provides AI-powered peer reviews for open-source repositories. Two more entries in the portfolio.
In His Own Words
Most companies are trying to use AI to do the same things faster. The teams that win are the ones who use AI to do things they could never do before.
The sales career funded the builder habit. The builder habit is the point now.
I build what most companies are still trying to whiteboard.
Career Arc
Three career chapters, one thesis: real systems beat real talk. The progression from staffing ops to SaaS sales to AI product builder was not a career pivot. It was compounding.
Early Career
Staffmark - VP-level National Accounts and Sales Operations in traditional staffing. Built the operator instincts that every later role was grounded in. Managed teams of 110.
~2015
Avionte - Head of Sales Enablement at a staffing software company. Crossed from operator to SaaS seller. Still thought like an operator.
~2019
Sense - AI GTM Executive / Director of Revenue Ops at the leading AI-driven talent engagement platform. $75M+ pipeline influence. Built AI GTM infrastructure from inside a fast-scaling Series D company.
2022
Started building AI products in earnest. Cadence, DealIQ OS, and getaFNjob all emerged from this period. The builder habit, funded by fifteen years of sales, became the main event.
2023
Launched Selling with AI newsletter. Reached 70% open rate. Began sharing the playbooks publicly that he had been running privately.
2024-2025
Launched Blair, Mason, Chase, and JARVIS. Crossed 45+ AI products shipped, 12+ GitHub repos. Transitioned to fractional AI GTM model for SaaS and staffing companies.
Notable Achievements
Anecdote
"One of those products is currently job hunting on my behalf." - His GitHub bio refers to getaFNjob, an AI career tool that scores job fit and drafts outreach - running on his behalf while he builds the next product.
The Work
Most fractional executives write documents. Campbell takes ownership of the GTM function, installs systems, and leaves the team equipped to run them. The engagement model is three to six months. The deliverable is infrastructure, not a slide deck.
He works specifically with SaaS and staffing companies - the two sectors where he has spent his entire career - building the AI GTM systems that sales teams actually use: pipeline intelligence, deal coaching, outreach automation, signal monitoring, and enablement tooling built on the same stack he uses himself.
The thesis is consistent across everything he does: AI does not just accelerate what already exists. Applied correctly, it enables work that was never possible before - personalized outreach at scale, deal intelligence without manual data entry, hiring pipelines that do not require recruiter bandwidth to stay warm. He is building toward that version of the capability, not the shortcut version.
The staffing and recruiting sector is where his background at Sense is most directly applied. Sense - now a Series D company with $106M in total funding and 380 employees - is one of the leading AI talent engagement platforms, working with enterprise recruiting teams on AI-driven candidate communication, screening automation, and recruitment marketing. Campbell's years there gave him a front-row view of what AI can actually do when deployed at scale in enterprise hiring.
Engagement Model
Active operating role · Own a GTM function · Build systems end-to-end · Develop the people who run them
Work With JaySense · Series D
Sense is the AI-driven talent engagement platform that Campbell worked at as an AI GTM executive. The San Francisco-based company has raised $106M in total funding (including a $50M Series D), employs 380 people, and generates approximately $75M in annual revenue.
Its platform handles conversational AI for candidate communication, automated screening, interview scheduling, recruitment marketing, and talent analytics - serving enterprise recruiting teams across staffing, healthcare, logistics, financial services, and technology sectors.
Campbell's GTM role at Sense gave him direct experience deploying AI at enterprise scale in the recruiting sector - one of the largest and most data-intensive applications of conversational AI in the workforce economy.
Field Notes
Connect