This is the takeaway episode with David Krauza, VP of Data Strategy and Governance at Comcast who makes the case that AI doesn't create your problems, it inherits the business choices you never made and the results nobody owns. David joins Juan and Tim and discuss the accountability problems, definition problems, assumption problems, and what-are-we-even-measuring problems.

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Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo, recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems.

In this episode, Mohammed lays out a framework for talent in the AI era. Automation is already taking over the known, repeatable work. What remains is the unknown, and that takes people who keep learning and who take initiative. The framework plots people on two dimensions, learning and drive. You have Doers, Philosophers, Commanders, Hackers, Strategist, Innovators, Game changers and more. Topics discussed

• Automation and the innovation engine
• The known versus the unknown
• Two dimensions of talent
• The talent quadrants
• The multiplier effect
• Commanders and scaling
• Environments that don’t build initiative
• Rarity of high-potential people
• Investing in human potential
• The human mind as the limit
• Critical thinking through discomfort

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This is the takeaway episode with Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo. He recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems.

See omnystudio.com/listener for privacy information.

How do leaders preserve executive trust and credibility? Dora Boussias, executive advisor and former data executive returns to the podcast to unpack this question. Her answer: protect your judgement.

In this episode, Dora presents the trust equation that most leaders grew up with: expertise + track record + judgment. Dora’s point is that the equation still holds, but each part now means something different. Nobody will out-know AI, so expertise is less about what you know and more about asking the right questions and challenging assumptions. A track record is harder to read when you can’t tell whether a good result came from you or from the model. Judgment carries the most weight now, and it’s the part leaders are most likely to hand off without noticing. Topics discussed:

• Trust equation under AI
• Expertise is changing
• Track record is harder to read
• Judgment carries the most weight
• Decision fog
• Speed isn’t everything
• Ford’s rehiring of experienced engineers
• Business fundamentals matter more
• Alignment and accountability are cross-functional
• Real value is “so what”

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This is the takeaway episode with Dora Boussias, executive advisor and former data executive. We unpack the question "How do leaders preserve executive trust and credibility?" Her answer: protect your judgement. In this episode, Dora presents the trust equation that most leaders grew up with: expertise + track record + judgment. Don't miss it!

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#Localization #Globalization #ServiceNow #AI

A translation can be word-for-word accurate and still be completely wrong. In this episode, Bobby Brill sits down with Sam Smyth, Product Manager on the globalization side at ServiceNow, to get into what happens after you decide to go multilingual — the tools, the governance, and the quiet work nobody sees until it breaks.

Sam spent fifteen years in localization operations and management before joining ServiceNow, and he's blunt about what actually goes wrong: it's rarely the translator. It's the content you sent them. We get into Localization Workspace, the new globalization agent that builds a glossary from your knowledge articles in minutes, why every customer still insists on a human in the loop, and the one mistake that will break your product UI in six languages at once.

Past Localization episodes:
https://youtu.be/4ka4qLk8Uj0
https://youtu.be/cGXCnABXKow

Guest: Sam Smyth, Product Manager - ServiceNow

Chapters
00:00 "People don't see localization until it goes wrong"
00:22 Translation vs. localization — a quick recap
00:56 Meet Sam Smyth: fifteen years in localization
01:37 When a perfect translation is still wrong
03:34 Why customers don't want to leave the platform
04:07 Localization Workspace: no more spreadsheets and email chains
05:13 The surprise: everybody still wants a human in the loop
05:38 Speed, cost, quality — picking all three
06:55 Inside the globalization agent 08:50 Who approves the terms? (And which shade of green?) 09:55 Language governance and the invisible costs
11:49 AI, volume, and doing the work upstream
13:02 Where to actually start with a glossary
16:28 A day in the life of a localization program manager
18:56 Shifting left: from firefighting to strategy
20:35 The one mistake: never hardcode your UI
22:10 Wrap-up

ServiceNow Training and Certification:
https://www.servicenow.com/services/training-and-certification.html

ServiceNow Insights podcast playlist:
https://www.youtube.com/playlist?list=PLCOmiTb5WX3qvGq7Cp3o2KkCiplJyqQOK

Servicenow.com: https://www.servicenow.com

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Agents will build data infrastructure at every layer and become its primary consumers. Tristan Handy, President and Co-founder of Fivetran / dbt Labs joins Juan and Tim where we unpack the big shift that is happening: teams need to move from working in the process (picking up individual tickets) to working on the process (building the factories that handle those tickets). In this episode, we break down what this means for data roles, why open components matter more than vendor stacks, and the socio-political problem nobody's talking about, deciding what counts as truth so your agents (and humans) ask the right questions in the first place. Topics discussed:

• Agents as builders and consumers
• Data roles are collapsing
• From working IN to working ON
• Loop building as the competitive advantage
• Business understanding beats technical specs
• From humans in the loop to humans out of the loop
• Open components over vendor stacks
• Defining truth is a political problem
• Data observability becomes business observability
• Real-time becomes necessary
• Humans delegate outcomes, set goals, sit in control

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This is the takeaway episode with Tristan Handy, President and Co-founder of Fivetran / dbt Labs where he joins Juan and Tim to discuss how agents will build data infrastructure at every layer and become its primary consumers. We unpack the big shift that is happening: teams need to move from working in the process to working on the process, what this means for data roles, why open components matter more than vendor stacks, and the socio-political problem nobody's talking about, deciding what counts as truth so your agents (and humans) ask the right questions in the first place.

See omnystudio.com/listener for privacy information.