Operations Systems Leader

Stephen
Thiessen

I turn operational ambiguity into execution infrastructure — the systems, planning rhythms, and AI-native workflows that let product and delivery orgs move with precision instead of noise.

// Career snapshot
14
Years operating
5
Industry verticals
$1B+
Org scale navigated
IC→
To strategic lead

PMP — Project Management Professional
Advanced Certified Scrum Master
AI Product Management — Certified
Prompt Engineering & AI Workflow Design
Hatch DoubleVerify Drata Peloton Capital One Oracle Operating Model Design Planning Rhythms Roadmap Facilitation AI-Native Workflows Cross-Functional Alignment Hatch DoubleVerify Drata Peloton Capital One Oracle Operating Model Design Planning Rhythms Roadmap Facilitation AI-Native Workflows Cross-Functional Alignment
About
Built for the
messy middle
Stephen Thiessen

I'm a strategic operations leader with 14 years operating at the intersection of product, engineering, and go-to-market — across ad tech, security and compliance SaaS, data infrastructure, and AI-native voice systems.

My work lives one level above delivery and one level below strategy: translating complex goals into operating models, planning systems, and cross-functional rhythms that hold up under pressure and scale with the org.

I've built and rebuilt operating systems inside some of the most demanding environments in tech — joining Peloton pre-IPO and operating through hypergrowth, building compliance infrastructure at Drata during its scale-up, driving verification platform programs at DoubleVerify, and most recently designing AI-native voice infrastructure at Hatch.

More recently I've focused on one question: how do AI-native workflows change what operations looks like? Not AI as a feature, but AI as the backbone of how an org plans, decides, and executes. That's what the tools on this site are built around.

At Hatch, that question got a concrete answer: when a client issue turned out to trace back to shared platform infrastructure rather than one account's configuration, I designed a backward-compatible fix that protected every other live client and escalated it as a formal product enhancement — the kind of judgment call that sits above individual implementation work.

I'm looking for roles where I can own the operating model — not manage the execution layer, not chase teams for updates, but design and run the system that makes excellent product and operational work possible.

Operating model design
How product and delivery teams plan, decide, and run
Planning rhythms
Quarterly cycles that connect to strategy
Roadmap facilitation
Prioritization as a decision process, not a list
AI-native workflows
Embedding AI into how orgs actually work
// Operating at
Hatch DoubleVerify Drata Peloton Capital One Oracle
Product Ops Intelligence
Tools I built.
Use them.

These aren't portfolio pieces. They're working tools built on the frameworks I use to diagnose and fix product operating models. If you run a product org, they'll tell you something real.

The Product Intelligence Loop
A five-layer agentic framework

Most product ops failures trace back to five universal problems — ideas that get lost, strategy that doesn't drive decisions, planning driven by politics, execution that goes dark, and lessons that never stick. The PIL is a multi-agent system designed around all five. One layer per problem. Twelve agents. A scoring matrix, a planning lock, and a loop that closes.

// Framework documentation
The PIL Master Framework
The full system — five layers, twelve agents, eight scoring dimensions, the Planning Lock, and the exception process. Built to replace political prioritization with evidence-driven planning.
Layers
5
Agents
12
Dimensions
8
// Live demo · Layer 1 · Capture
PRD Intake Agent
A live demonstration of the PIL's Layer 1 Capture agent in action. Describe a product idea — the agent guides you through structured intake, maps it to OKRs, generates a PRD outline, and routes it to the right PM. Real AI, real output.
Mode
Live AI
Fallback
Scripted
Writing
Latest thinking
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Let's talk about
your operating model

I'm selectively exploring roles where I can own the operating model — planning systems, roadmap infrastructure, AI-native workflows, and the judgment to know when a fix is bigger than one team. Product, delivery, or operations org — the system is the point.