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1 episodes · 23 quoted claims
Dave Glick took a new role leading a global team responsible for Walmart's growth businesses: advertising, data ventures, Walmart Plus and marketplace.
“I took a new role in a new global team responsible for our growth businesses. And so that's advertising, uh, data ventures, Walmart Plus and marketplace.”
Dave Glick says he joined engineering about 25 years ago and has always faced pressure from business and product teams to add features.
“I've joined engineering, which was about 25 years ago, there's always been the pressure on the business and the product team.”
Raising a seller image-upload size limit was a one-line code change that Dave Glick says reduced errors and seller frustration.
“going from X to Y megabytes means that we have less errors and the sellers are less frustrated. That seems like a good thing to do, and it was like a one line code change.”
Dave Glick says Walmart once had a team doing 'ticket diving', manually reviewing tickets and writing a weekly summary report, work AI can now do in minutes.
“When I started, we had a whole team whose job it is, we called it ticket diving, right? And go in and look at what the tickets are and write a summary report every week for that.”
During testing of Walmart's careers site, the team had 15 open bugs and was closing about 15 a day, but product and customer teams said edge cases were missing.
“we were launching, uh, our careers site, and, you know, we were in the testing process. And my team was like, we have 15 bugs open, we're closing about 15 bugs a day, so we should be okay.”
A Walmart engineer used a coding agent on the careers site's GitHub repository to write tests, which took about a week and which Dave Glick says would otherwise have taken months.
“it ended up taking a week to get it really dialed in. But that would have taken us months to write all those tests, and we would have never hit the date.”
Dave Glick says Walmart's mission about 18 months before the interview was to put AI in the hands of every campus associate every day.
“we wanted to say, like, how do we put AI in the hands of every campus associate every day. That was the mission 18 months ago.”
Dave Glick says Walmart initially thought its AI mission meant giving everyone licenses to Gemini, ChatGPT and Copilot.
“we thought that was like getting everybody licenses to Gemini, ChatGPT and copilot.”
Walmart wrote its own coding agent called Code Puppy, which was expected to be used by engineers.
“We we wrote our own coding agent, it's called Code Puppy, and we thought it was gonna be for the engineers.”
Code Puppy began when a couple of Walmart engineers who wanted a command-line tool wrote it over a weekend.
“a couple engineers wanted a command line interface tool, and they wrote it over the weekend.”
Dave Glick says operations staff using Code Puppy wrote a report in three hours that they had requested from engineering for three years.
“We've got folks who are writing their own reports, and they said, we've been asking for the for this from engineering for three years, and I was able to write it myself in three hours.”
Walmart built an internal agent registry so employees can check whether an agent for a task already exists before building one.
“we've built a registry so that people can say, I want an agent that does this. Let's go see if there's already one.”
Walmart created a launch pad to move AI tools that employees built on their local machines into production and make them shareable.
“We've got what's called a launch pad because we had a lot of people building things on their local machines. But how do we get that into production?”
Dave Glick says Walmart governed its AI experimentation by applying its existing data privacy and data governance policies and adding to them over time.
“we already had data privacy policies, we already had data governance policies. Let's use those and then see how it goes.”
Walmart's compliance team uses the company's coding agent, which Dave Glick says helps them understand what it can do.
“got a compliance team who is also using our coding agent, and so they know what it can do.”
Dave Glick says friends at other large companies were still trying to get ChatGPT through their security review.
“I talked to my friends at other big companies, and they're still trying to get, you know, ChatGPT through their security process.”
A Walmart community member built an agent-sharing mechanism that was incorporated into Walmart's coding agent.
“one of the people in the community built like a sharing mechanism, and we crowdsourced that into our agent.”
Dave Glick describes large companies' annual operating plan process, in which business teams submit requests and engineering commits to only a few, leaving the rest below the line.
“every year we get together and do an annual operating plan or an operational plan, one or whatever you want to call it. And the business team submits, here's all we want you to do engineering.”
Dave Glick cited globalizing about 400 services as a big engineering project where AI could help engineers.
“what if the AI can go through and help the engineer globalize each of those 400 services? Now we've got a global platform.”
Dave Glick holds weekly Monday-morning AI office hours where employees demo what they built with AI.
“started creating AI office hours. And so every every Monday morning, if you've created something with AI in the last week, you can come in and demo it to me”
Dave Glick says about three quarters of the AI projects presented at his office hours reduce toil rather than add production features.
“About three quarters of the things people present are things that are helping them reduce toil and not production features.”
Walmart held a hackathon the week before the interview with the theme 'remove toil'.
“we actually had a um a hackathon last week and the the theme was remove toil.”
Dave Glick says Walmart aims to consolidate on one release manager agent and a few test-building agents rather than 100 duplicates.
“we do need one release manager that we bet on. We need one test building thing, or, you know, maybe two or three, but not 100.”