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Most AI tools guess. Chord doesn’t. Built for commerce, Chord AI combines a trusted data foundation with a copilot so every answer, recommendation, and activation is grounded in truth, not guesses.

Meet Chord AI—our all-in-one data platform and copilot built for commerce. Unlike most AI tools, it’s powered by a commerce-native foundation, so every answer, recommendation, and activation is grounded in truth—not guesses.

In my 2nd board meeting as Glossier’s CTO, a major investor asked me how I split my time. I told him I spent (roughly) 60% being an exec, 40% writing code. He told me to stop coding. I disagreed. And while that 60/40 split evolved to less "hands-on-keyboard" time in the years since, I stand by the reason I was so committed to it back in 2017. The critical piece of my career over the past 30 years has been my fluency in both technology and business. I credit much of the success I’ve had to being able to bridge those two worlds. I told that investor as much at the time. I told him that being hands-on kept me technically relevant with my team. It’s an awful lot easier to lead when I know it's actually possible (and just how long "possible" might take). I also knew that we couldn’t build without urgency, because I was keenly aware of the responsibility we had to the business. If it would take us 60 days, I’d push us to do it in 30. Over my career, I mostly had no choice but to do both things. Today, I know not everyone has to. But I actually think most people should. We have these incredible AI tools at our fingertips now. To get the most out of them, it’s helpful to look through both a technical lens and a business lens. If you want to be the best possible builder, you should be able to commercially assess: Is this a thing I should be building? Or, is there something that I can buy that is going to make the thing I'm building even more powerful? That balance is a lesson that I've been learning for the last 3 decades. Back at Glossier, I’d check in with that investor at every subsequent board meeting. By the time we met the second time, my time looked more like 70% leadership, 30% coding. Then 80-20… and so on. We’d both chuckle about it over the years. He was right about the percentages (eventually). But I still think staying close to the code made me a better CTO and leader. And as more of us get further away from the code, I’m even more convinced of that than I was in 2017.

Full disclosure: I'm not a women's health expert. (Shocking, I know.) So sitting down with Priyanka Jain recently meant I had a lot to learn. One story stuck with me. The day after Evvy launched five years ago, an OBGYN published a takedown saying she had no business weighing in on healthcare. Not a doctor. Not a PhD. Five years later, Evvy holds the world's largest real world data set on the vaginal microbiome and serves over 100,000 patients and 2,000 doctors across the country. Her fix for imposter syndrome: stop trying to become the expert, and bring the experts together. I've been a founder for 30 years and still wake up with imposter syndrome every day, so that one landed. The other thing that surprised me is that women were never hard to find. They were already searching and asking each other in Reddit threads and Facebook groups, mostly getting served ads for products that make you smell like a flower. Evvy met them with real science and education instead. Now the first reply on a new post in some of those communities is "what are your Evvy results?" That's what it looks like when education is the acquisition strategy. Our full conversation is in the comments 👇

Back in 2009 (I remember it like it was yesterday 😅), I pulled Jenna Holcombe 🏴 into a meeting room at Dynamo in Montreal and spent hours unpacking responsive design. It didn’t take her long to wrap her brain around it, and hours later, she was already shipping designs our customers loved. I continue to be amazed and inspired by the incredible talent I’ve been lucky enough to cross paths with over the years. Jenna is one for those incredible talents. Today she's co-founder and Chief Brand Officer at Centra, the commerce platform built specifically for global fashion brands. We caught up recently, and she walked me through the hardest call they ever made. Around 2019, Centra decided to stop selling to all industries and focus only on fashion. This took me all the way back to the Dynamo days and an early “embrace constraints” mantra we had. As she tells the the story, there were some internal skeptics. In her words: Saying no to business is difficult and scary, but we did it, and I think it's the best thing we could have done.” What struck me was how she described the payoff. Marketing got sharper. The product got better. And the customers they stopped chasing? They were never as happy on the platform as the fashion brands anyway. One of my favourite take aways from our episode was this: the tighter you understand the problem, the clearer it becomes what you should build and why. That's a tough lesson for anyone with agency roots (hi, it's me). Agencies are wired to say yes. Focus asks you to say no, often, and mean it. Boundaries don't limit creativity! Jenna and her team are such a great example of this lesson that I’m happy to keep learning. Curious: what's the hardest "no" you've said that ended up paying off? (Our full conversation is in the comments if you want more of Jenna’s story.)

Most teams using AI right now are generating faster mediocrity. It’s starting to feel a lot like the sea of sameness we saw when everyone rushed to launch on Shopify with the same templates. It can draft a go-to-market plan in five minutes, but if you don’t know what a good one looks like, you’ve just produced polished nonsense at speed. This came up repeatedly in my conversation with JP Beeghly (Sonos) and Josh Maynard (MrBeast). The teams that are actually winning with AI aren’t the ones automating their brand. They’re the ones who came in with clean data, clear metrics, and enough business judgment to know when the output is wrong. AI is an incredibly fast intern with no context. If your data is messy, it amplifies the mess. If your thinking is shallow, it accelerates the shallowness. The dirty secret is that AI doesn’t replace judgment — it just exposes whether you had any to begin with. Commerce was never a solved problem. You can’t just AI your way to the solution! Love this episode? Get notified of each new drop here: https://lnkd.in/eTXq5Kkz