About Zach Varney.

I'm Zach Varney, a product leader in Kansas City. Over the last decade I've taken software from concept to acquisition twice — once as an engineer, once running the entire product function — and founded Ranger Ventures, an AI consulting and ventures practice.

My operating thesis hasn't changed in ten years: hire the right people, set clear expectations, and let good work happen.

AI didn't change that job. It changed what skilled people can do — which makes judgment about what to build, what to buy, and what to delegate the scarcest resource in the room.

I started as an engineer at EyeVerify, a biometric authentication company, and rode it through its acquisition by Ant Financial — then spent the months after close in China, handling implementation and knowledge transfer between the US and Chinese engineering orgs. I've been the skilled person a leader bet on. I know what that trust looks like from both sides of the table.

At DivvyHQ I owned the product function end to end for six years — a content-operations platform at $16–20M ARR, with distributed engineering teams across three continents. When COVID hit and marketing budgets were the first thing cut, we held 96% customer retention by trimming spend and refocusing a leaner team on what clients actually needed. When the board wanted AI features in-house, I made the build-vs-buy call and led the company's first generative AI partnerships instead — early positioning without the cost of a buildout. And when acquisition talks started, I was in every exploratory conversation, ran the buyer-facing demos, and delivered the integration plan that helped close the deal.

After the acquisition, I stayed on with the acquiring company. Their dev org hadn't shipped a major feature in five months. I pitched the CEO that the AI shift wasn't optional, and got a ten-person innovation team with an open mandate. I ran it on two rules: show, don't tell — every finding demoed and documented for the whole org — and no wrong findings, because mapping the dead ends mattered as much as the paths through. For the first two months that made us slower, and I took real heat for it.

Then it compounded. In seven months the team shipped the product's full AI feature set, a public API, an MCP server, and Slack and Teams integrations — and cleared a 186-bug backlog, some of it three years old, in two. We also killed five prototyped AI features that weren't ready to sell, because shipping AI theater is worse than shipping nothing. Then we dissolved the team on purpose: the point was never a special team, it was proving everyone should work this way. That company now operates as an AI-first org, and the API foundation has since enabled integrations that would have been impossible before.

Ranger Ventures is the current chapter — an AI consulting and ventures practice where I design and ship production systems end to end, and keep testing what these tools can actually do.

I still build — the projects on the Work page, the open-source package running this site's hero, an agent platform that runs my actual day. Not because shipping code is the job I'm after. The job I'm after is the one where I hand work to people better than me and clear their path.

The building is the floor under the judgment. It's how I can evaluate an AI engineering hire, call BS on a timeline, or prototype the thing that unblocks a roadmap decision instead of scheduling a quarter of discovery.

Fluency is cheap to claim and expensive to fake. So I keep receipts.

I'm open to the right Director- or VP-level product role, and Ranger takes a small number of consulting engagements. Either way, what you get is the same operating thesis — and the evidence is all over this site.