I'm Tiffany Graham, a product operations leader, AI enthusiast, and lifelong builder of systems that help organizations move faster and smarter. Welcome to where I share what I'm learning.
I currently lead a team of 40 at Instacart, responsible for the operational backbone of one of the most complex product ecosystems in tech. Before that, I served as COO at ParentPowered, scaling operations for an edtech platform reaching millions of families, and as Chief of Staff at Fulton County Schools, one of the largest school districts in the country.
My career started in a 7th grade science classroom through Teach for America, an experience that permanently shaped how I think about building systems that actually serve people, not just look good on a slide deck. That thread runs through everything I've done since: from district operations to edtech to the product org at a major tech company.
Lately, I'm deeply interested in how AI is reshaping the way product teams operate — not the hype cycle version, but the practical reality of what it means to integrate AI into workflows, decision-making, and team dynamics. That's a lot of what I write about in Signal Takes Noise.
The problems and questions that occupy most of my professional attention right now.
Not the hype, the practical reality. How do product teams actually integrate AI into their daily workflows? What works, what doesn't, and what's just theater? I'm interested in the messy middle between "AI will change everything" and the day-to-day of making it useful.
Product Ops is still defining itself as a function. How do you build it from scratch? How do you make the case for it? Where does it sit in the org? I've built this function multiple times and I'm always learning what makes it work and what makes it political.
The hardest part of operations leadership isn't the systems, it's the people and politics. Cross-functional influence, building trust across orgs, navigating ambiguity, and leading teams through change without burning them out.
Cutting through the hype on AI, product operations, and what it actually takes to build things that work.
Most product orgs blame engineering velocity when launches slip. The real issue is almost always upstream: unclear handoffs, missing feedback loops, and process debt nobody wants to own.
Before you buy another AI tool, make sure your processes are actually ready for automation. A framework for knowing when AI will help and when it'll just automate your mess faster.
Too many companies treat Product Operations as project management with a fancier title. Here's how to think about the function as a genuine strategic lever.
I'm always happy to connect with people thinking about product operations, AI, and leadership.
Whether you're building a Product Ops function, navigating a complex organizational challenge, or just want to trade notes on what's working, I'd love to hear from you.